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Canonical URLs: definitive guide to canonical tags 

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Imagine telling someone that www.mysite.com/blog/myarticle and www.mysite.com/myarticle are actually the same page. To you, they’re the same, but to Google, even a small difference in the URL makes them separate pages. That is where the canonical tag steps in. In this guide, we will walk you through what a canonical URL is, how URL canonicalization works, when to use it, and which mistakes to avoid so that search engines always understand your preferred page version.

Table of contents

Key takeaways

  • A canonical URL is the main version of a webpage that you want search engines to index, avoiding duplicate content issues
  • The canonical tag, placed in the HTML head, signals which URL is the preferred version to search engines
  • Using canonical URLs helps consolidate link equity, improves crawl efficiency, and enhances user experience
  • Implement canonical tags in scenarios like duplicate content, URL versions, and syndicated content to inform search engines which URL to prioritize
  • Yoast SEO can automate canonical URL handling, reducing manual errors and ensuring consistency across your site

What is a canonical URL?

A canonical URL is the main, preferred, or official version of a webpage that you want search engines like Google to crawl and index. It helps search engines determine which version of a page to treat as the primary one when multiple URLs lead to similar or duplicate content. As a result, it avoids duplicate content and protects your SEO ranking signals.

All of the following URLs can show the same page, but you should set only one as the canonical URL:

  • https://www.mysite.com/product/shoes
  • https://mysite.com/product/shoes?ref=instagram
  • https://m.mysite.com/product/shoes
  • https://www.mysite.com/product/shoes?color=black

What is a canonical tag?

A canonical tag (also called a rel="canonical" tag) is a small HTML snippet placed inside the section of a webpage to tell search engines which URL is the canonical or master version. It acts like a clear label saying, “Index this page, not the others.” This prevents duplicate content issues, consolidates ranking signals, and supports proper canonicalization across your site.

Here’s an example of a canonical tag in action:

Canonical URL HTML example

This tag should be placed on any alternate or duplicate versions that point back to the main page you want indexed.

How does URL canonicalization work?

Canonicalization is the process of selecting the representative or canonical URL of a piece of content. From a group of identical or nearly identical URLs, this is the version that search engines treat as the main page for indexing and ranking.

Once you understand that, canonicalization becomes much easier to visualize. Think of it as a three-step workflow.

How the canonicalization process works

Here’s how the canonicalization works:

Search engines detect duplicate or similar URLs

Google groups URLs that return the same (or almost the same) content. These could come from:

  • URL parameters
  • HTTP vs. HTTPS versions
  • Desktop vs. mobile URLs
  • Filtered or sorted pages
  • Regional versions
  • Accidental duplicates like staging URLs

You signal which URL is canonical

You can guide search engines using canonical signals like:

  • The rel="canonical" tag
  • 301 redirects
  • Internal links pointing to one preferred version
  • Consistent hreflang usage
  • XML sitemaps listing the preferred URL
  • HTTPS over HTTP

The strongest and clearest hint is the canonical tag placed in the head of the page.

Google selects one canonical URL

Google uses your signals, along with its own evaluation, to determine the primary URL. While Google typically follows canonical tags, it may override them if it detects stronger signals such as redirects, internal linking patterns, or user behaviour.

Once Google settles on the canonical URL, search engines will:

  • Consolidate link equity into the canonical page
  • Index the canonical URL
  • Treat all non-canonical URLs as duplicates
  • Reduce crawl waste
  • Avoid showing similar pages in search results

Canonical tags are a hint, not a directive. Google may still distribute link equity differently if it deems the canonical tag unreliable.

Reasons why canonicalization happens

Canonicalization becomes necessary when different URLs lead to the same content. Some common reasons are:

Region variants

For example, you have one product page for the USA and one for the UK, like: https://example.com/product/shoes-us and https://example.com/product/shoes-uk.

If the content is almost identical, use one canonical link or a clear regional setup to avoid confusion.

Pro tip: For regional variants, combine canonical tags with hreflang to specify language/region targeting.

Device variants

When you serve separate URLs for mobile and desktop, such as: https://m.example.com/product/shoes and https://www.example.com/product/shoes.

Canonical tags help search engines understand which URL is the primary version.

Protocol variants

Sorting and filtering often create many URLs that show similar content, like:

https://example.com/shoes?sort=price or https://example.com/shoes?color=black&size=7

A single canonical URL, such as https://example.com/shoes, tells search engines which page should carry the main ranking signals.

Also read: Optimizing ecommerce product variations for SEO and conversions

Accidental variants

Maybe a staging or demo version of the site is left crawlable, or both https://example.com/page and https://example.com/page/ return the same content

Canonical tags and proper URL canonicalization help avoid these unintentional duplicates.

Some duplicate content on a site is normal. The goal of canonicalization in SEO is not to eliminate every duplicate, but to show search engines which URL you want them to treat as the primary one.

In practical aspects

In practice, canonicalization comes down to a few key things:

Placement

The canonical tag is placed in the head of the HTML, for example:

link rel="canonical" href="https://www.example.com/preferred-page" /

Each page should have at most one canonical tag, and it should point to the clean, preferred canonical URL.

Identification

Search engines examine several signals to determine the canonical version of a page. The rel="canonical" tag is important, but they also consider 301 redirects, internal links, sitemaps, hreflang, and whether the page is served on HTTPS. When these signals are consistent, it is easier for Google to pick the right canonicalized URL.

Crawling and indexing

Once search engines understand which URL is canonical, they primarily crawl and index that version, folding duplicates into it. Link equity and other signals are consolidated to the canonical page, which improves stability in rankings and makes your canonical tag SEO setup more effective.

The main rule for canonicalization is simple: if multiple URLs display the same content, choose one, make it your canonical URL, and clearly signal that choice with a proper canonical tag.

Why do canonical tags matter for SEO?

Google’s John Mueller puts it simply: ‘I recommend doing this kind of self-referential rel=canonical because it really makes it clear for us which page you want to have indexed or what this URL should be when it’s indexed.’

And that’s exactly why canonical tags matter; they tell search engines which version of a page is the real one. This keeps your SEO signals clean and prevents your site from competing with itself.

They’re important because they:

  • Avoid duplicate content issues: Canonical tags inform Google which URL should be indexed, preventing similar or duplicate pages from confusing crawlers or diluting rankings
  • Consolidate link equity: Canonicalization works similarly to internal linking; both are techniques used to direct authority to the page that matters most. Instead of splitting ranking signals across duplicate URLs, all information is consolidated into a single canonical URL
  • Improve crawl efficiency: Search engines don’t waste time crawling unnecessary duplicate pages, which helps them discover your important content faster
  • Enhance user experience: Users land on the correct, up-to-date version of your page, not a filtered, parameterized, or accidental duplicate

When to use canonical tags?

Canonical tags are useful in various everyday SEO scenarios. Here are the most common scenarios where you’ll want to use a rel=canonical tag to signal your preferred URL.

URL versions

If your page loads under multiple URL formats, with or without “www,” HTTP vs. HTTPS, and with or without a trailing slash, search engines may index each version separately. A canonical tag helps you standardize the preferred version so Google doesn’t treat them as separate pages.

Duplicate content

Ecommerce sites, blogs with tag archives, and category-driven pages often generate duplicate or near-duplicate content by design. If the same product or article appears under multiple URLs (filters, parameters, tracking codes, etc.), canonical tags help Google understand which canonical URL is the authoritative one. This prevents cannibalization and protects your canonical SEO setup.

Also read: Ecommerce SEO: how to rank higher & sell more online

Syndicated content

If your content is republished on partner sites or aggregators, always use a canonical tag that points back to your original version. This ensures your page retains the ranking signals, not the syndicated copy, and search engines know exactly where the content was originally published.

If syndication partners don’t honor your canonical tag, consider using noindex or negotiating link attribution.

Paginated pages

Long lists or multi-page articles often create a chain of URLs like /page/2/, /page/3/, and so on. These pages contribute to the same topic but shouldn’t be indexed individually. Adding canonical tags to the paginated sequence (typically pointing to page 1 or a “view-all” version) helps consolidate indexing and keeps rankings focused on the primary page.

Pro tip: For paginated content, use self-referencing canonicals (each page points to itself) unless you have a ‘view-all’ page that loads quickly and is crawlable.

Also read: Pagination & SEO: best practices

Site migrations

When you change domains, restructure URLs, or move from HTTP to HTTPS, using consistent canonical tags helps reinforce which pages replace the old ones. It signals to search engines which canonicalized URL should inherit ranking power. During migrations, canonical tags act as a safety net to prevent duplicate versions from competing with each other.

Implementing canonical URLs and canonical tags

URL canonicalization is all about giving search engines a clear signal about which version of a page is the preferred or canonical URL. You can implement it in several simple steps.

Using the rel=”canonical” tag

The most common way (as shown multiple times in this blog post) to set a canonical URL is by adding a rel="canonical" tag in the head section of your page. It looks like this:

link rel="canonical" href="https://www.example.com/preferred-url"/

This tag tells search engines which URL should carry all ranking signals and appear in search results. Ensure that every duplicate or alternate version links to the same preferred URL, and that the canonical tag is consistent throughout the site.

You can also use rel="canonical" in HTTP headers for non-HTML content such as PDFs. This is helpful when you cannot place a tag in the page itself.

Pro tip: While supported for PDFs, Google may not always honor canonical HTTP headers. Use them in conjunction with other signals (e.g., sitemaps).

Also, ensure the canonical tag is as close to the top of the head section as possible so that search engines can see it early. Each page should have only one canonical tag, and it should always point to a clean, accessible URL. Avoid mixing signals. The canonical URL, your internal links, and your sitemap entries should all match.

Setting a preferred domain in Google Search Console

Google lets you choose whether you prefer your URLs to appear with or without www. Setting this preference helps reinforce your canonical signals and prevents search engines from treating www and non-www versions as different URLs.

To set your preferred domain, open your property in Google Search Console, go to Settings, and choose the version you want to treat as your primary domain.

Redirects (301 redirects)

A 301 redirect is one of the strongest signals you can send. It permanently informs browsers and search engines that one URL has been redirected to another and that the new URL should be considered the canonical URL.

Use 301 redirects when:

  • You merge duplicate URLs
  • You change your site structure
  • You migrate to HTTPS
  • You want to consolidate link equity from outdated pages

Of course, redirects replace the old URL, while canonical tags suggest a preference without removing the duplicate.

With Yoast SEO Premium, you can manage redirects effortlessly right inside your WordPress dashboard. The built-in redirect manager feature of the SEO plugin helps you avoid unnecessary 404s and prevents visitors from landing on dead ends, keeping your site structure clean and your user experience smooth.

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Additional canonicalization techniques

There are a few more ways to support your canonical setup.

  • XML sitemaps: Always include only canonical URLs in your sitemap. This helps search engines understand which URLs you want indexed
  • Hreflang annotations: For multi-language or multi-region sites, hreflang tags help search engines serve the correct regional version while still respecting your canonical preference
  • Link HTTP headers: For files like PDFs or other non-HTML content, using a rel="canonical" HTTP header helps you specify the preferred URL server-side

Each of these methods reinforces your canonical signals. When you use them together, search engines have a much clearer understanding of your canonicalized URLs.

Implementing canonicalization in WordPress with Yoast

Manually adding a rel="canonical" tag to the head of every duplicate page can be fiddly and error prone. You need to edit templates or theme files, keep tags consistent with your sitemap and internal linking, and remember special cases, such as PDFs or paginated series. Modifying site code and HTML is risky when you have numerous pages or multiple editors working on the site.

Yoast SEO makes this easier and safer. The plugin automatically generates sensible canonical URL tags for all your pages and templates, eliminating the need for manual theme file edits or code additions. You can still override that choice on a page-by-page basis in the Yoast SEO sidebar: open the post or page, go to Advanced, and paste the full canonical URL in the Canonical URL field, then save.

  • Automatic coverage: Yoast automatically adds canonical tags to pages and archives by default, which helps prevent many common duplicate content issues
  • Manual override: For special cases, use the Yoast sidebar > Advanced > Canonical URL field to set a custom canonical. This accepts full URLs and updates when you save the post
  • Edge cases handled: Yoast will not output a canonical tag on pages set to noindex, and it follows best practices for paginated series and archives
  • Developer options: If you need custom behavior, you can filter the canonical output programmatically using the wpseo_canonical filter or use Yoast’s developer API
  • Cross-domain and non-HTML: Yoast supports cross-site canonicals, and you can use rel=”canonical” in HTTP headers for non-HTML files when needed

Both Yoast SEO and Yoast SEO Premium include canonical URL handling, and the Premium version adds extra automation and controls to streamline larger sites.

Must read: How to change the canonical URL in Yoast SEO for WordPress

rel=“canonical”: one URL to rule them all

Canonical URLs may seem like a small technical detail, but they play a huge role in helping search engines understand your site. When Google finds multiple URLs displaying the same content, it must select one version to index. If you do not guide that choice, Google will make the decision on its own, and that choice is not always the version you intended. That can lead to split ranking signals, wasted crawl activity, and frustrating drops in visibility.

Using canonical URLs gives you back that control. It tells search engines which page is the primary version, which ones are duplicates, and where all authority signals should be directed. From filtering URLs to regional variants to accidental duplicates that slip through the cracks, canonicals keep everything tidy and predictable.

The good news is that canonicalization does not have to be complicated. A simple rel=”canonical” tag, consistent URL handling, smart redirects, and clean sitemap signals are enough to prevent most issues. And if you are working in WordPress, Yoast SEO takes care of almost all of this automatically, so you can focus on creating content instead of wrestling with code.

At the end of the day, canonical URLs are about clarity. Show search engines the version that matters, remove the noise, and keep your authority consolidated in one place. When your signals are clear, your rankings have a solid foundation to grow.

The post Canonical URLs: definitive guide to canonical tags  appeared first on Yoast.

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YouTube Marketing Strategy: Grow Your Channel

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If you’re getting into video marketing, there’s no better channel than YouTube.

It’s right behind Google, and the No. 2 social media platform after Facebook. Oh, and it reaches more than 2.5 billion monthly active users (MAU).

That’s a lot of eyes. And it’s why your YouTube marketing strategy matters.

Think about it. Searchers often click video first for “how to,” reviews, and comparisons. If your video answers the question clearly, you win two placements (on YouTube AND Google) with one asset.

That search role matters more now. Google results and AI Overviews are citing YouTube videos far more often. That means the right video can earn visibility on YouTube and in Google’s AI-enhanced results. 

Here’s how to take advantage of YouTube’s massive reach and growing role in search.

Key Takeaways

  • YouTube is still a search engine first. Optimize every video like a web page. Titles, keywords, and descriptions all matter.
  • Short-form video drives discovery. Use Shorts to grab attention and push viewers toward your long-form content.
  • Consistency beats virality. One great upload won’t build your channel, but showing up weekly will.
  • Engagement fuels growth. Comments, likes, and watch time tell YouTube your content deserves more reach.
  • Cross-promotion multiplies exposure. Share clips across LinkedIn, Instagram, and email to spark early momentum and feed the algorithm. 

Why Market on YouTube?

Short-form video is where attention stacks up right now. 

More than 120 million people watch YouTube every day. That’s reach you can’t ignore. 

It also fits how people search. Viewers type questions into the platform, often searching for product comparisons or “how-to” content. That’s the magic of YouTube marketing: Your video can rank on YouTube and, increasingly, get pulled into Google’s AI results. 

The numbers are staggering. Total YouTube citations are up more than 400 percent in AI Overviews alone, per Ubersuggest data.

A bar chart showing YouTube citations in AI Overviews has increased 414 percent in total, 651 percent for how-to queries, and 592 percent for visual demonstrations.

Shorts adds even more surface area. YouTube confirmed 200 billion daily Shorts views in 2025. That’s a firehose of discovery for quick tutorials, comparisons, and teasers that push to deeper content. 

And it’s accessible. You don’t need a studio. A phone, a clear topic, and tight editing are enough to compete in most niches. 

Start with one Shorts series and one weekly long-form video. Just be sure to use chapters as well as strong titles and descriptions that read like answers. Steer clear of slogans. 

New to planning video content? This video marketing primer will help. 

YouTube gives you search demand, social discovery—and now large language model (LLM)-level visibility—all in one place. That mix is hard to match.

A chart showing YouTube SEO growth vs. blog SEO growth over a 12-month period.

Part 1: Find Your Place in the YouTube Landscape

There are now more than 100 million YouTube channels. That’s a massive jump from just a few years ago. 

You’ll find everything from tech reviews and finance breakdowns to ASMR and speed cleaning. There’s even a channel about a lawyer who picks locks.

YouTube channel page with video thumbnails for @LockPickingLawyer

With that much competition, your YouTube marketing strategy has to start with clarity: who you’re talking to, what kind of content they actually want, and where you can add something different.

That means:

  • Pinpointing your target audience.
  • Choosing the video formats that match their attention span.
  • Studying competitors to see what’s working and where the gaps are.

Once you know your lane, everything else—your topics, cadence, and growth plan—gets a whole lot easier.

Figure Out Your Target Audience on YouTube

YouTube is too big to win by going broad. “Everyone” isn’t an audience. The sweet spot is finding a niche that’s specific enough to stand out but big enough to grow.

Start with who already buys from you. Look at your website analytics and social media insights to see who’s engaging most. 

Age, interests, and location all help. Tools like Google Analytics and YouTube Studio can show you what your current audience searches for and watches next.

Then, build a quick buyer persona:

  • Who are they? (job title, interests, pain points)
  • What do they search on YouTube?
  • When and how do they watch? On desktop, mobile, or TV?
  • What tone or style do they respond to?

Once you define that persona, brainstorm content they’d actually click. If your viewers are marketing managers, short “how-to” clips might work better than 20-minute explainers.

You don’t need to reach everyone, just the right people often enough that YouTube’s algorithm starts recognizing your audience and recommending your videos to more like them.

See the Types of Videos Your Target Audience Likes

It’s not enough to know who your target audience is. You need to understand what kind of videos they like to watch. There are hundreds of different types of videos on YouTube:

Start by checking what’s already working in your niche. Search your main keywords on YouTube and filter by “Most Viewed.” Make note of formats that dominate the results:

  • How-to tutorials: Great for education-driven niches.
  • Explainer videos: Ideal if you sell products or software.
  • Case studies or success stories: Perfect for B2B audiences.
  • Listicles and tips videos: Work well for lifestyle and marketing content.
  • Shorts: YouTube’s fastest-growing format, great for quick insights, teasers, or trends.
  • Livestreams: Build community and drive real-time engagement.

Use YouTube Analytics to compare your own watch times, click-through rates (CTR), and retention graphs. You can also plug your top-performing videos into Ubersuggest and use the Content Ideas tool to see related topics gaining traction.

Ubersuggest's interface.

Don’t settle for just copying what’s popular. The goal is to spot patterns in what your audience values, and then make those formats your own.

Short-Form Videos

Short-form video is the new default. YouTube Shorts now gets over 200 billion views a day, which means your audience is already scrolling there.

People love short-form content because it’s fast, visual, and snackable. They can learn something, laugh, or get inspired in under a minute. For brands, that’s a huge opportunity to build awareness and trust without needing a big budget.

Use Shorts to highlight quick takeaways, answer common questions, or tease a longer video. Think of them as “trailers” for your main content.

Repurpose what you already have:

  • Cut 15- to 60-second clips from your best-performing videos.
  • Turn customer quotes or stats into vertical video slides.
  • Use one key insight per clip. Don’t cram in too much.

Shorts also travel well. You can cross-post them to Instagram Reels, TikTok, and LinkedIn to expand your reach without doubling your workload.

Start small, stay consistent, and you’ll see which ideas hook your audience fastest.

Check Up on Your Competition

You’re not creating in a vacuum. Every niche on YouTube already has leaders. Studying them is one of the fastest ways to sharpen your YouTube marketing strategy.

Start by searching your main keywords and noting who consistently ranks on the first page. Those are your real competitors. 

Then use tools like vidIQ or TubeBuddy to see what’s driving their performance. Pay particular attention to metrics like average views per video, upload frequency, engagement rate, and keyword use.

Go beyond views, too:

  • What video formats do they use most? Tutorials, reviews, Shorts? 
  • How do they open and end each video? 
  • What topics or questions show up repeatedly in their comments?

Your goal isn’t to find the gaps. If competitors focus on broad topics, go deeper. If they post irregularly, show up consistently. 

Learn the playbook, then rewrite it in your own voice.

Part 2: Create A Great Channel Layout and Organize Your YouTube Content

First impressions matter. 

When people land on your channel, they should instantly know who you are, what you talk about, and why they should subscribe.

Here’s my channel:

The home page for Neil Patel’s YouTube channel.

My value proposition and color scheme are simple and match my website. The banner says how often I publish new videos. My trailer is like an extension of the value prop.

A clean, consistent channel layout builds trust fast. 

Start with a short trailer that introduces your niche and what viewers can expect from you. Use a simple banner that matches your website’s look and feel, and make sure your “About” section includes a clear description, publishing cadence, and links to your website or lead magnets.

Videos sorted by the categories “past live streams” and “multiple playlists” on Neil Patel’s YouTube channel.

Group your videos into playlists organized by topic or intent, by tutorials, product demos, case studies, or Shorts, for example. Playlists help with binge-watching and signal YouTube that your content fits together, which improves discoverability.

The goal is to make your channel feel like a well-organized library, not a random drop box of uploads. 

Next, I’ll show you how to plan your upload schedule and design thumbnails that get clicks.

Create Regular YouTube Content With a Content Calendar

The algorithm rewards consistency. So does your audience.

A good posting rhythm might be one long-form video per week and two to three Shorts. That balance keeps your channel active without burning you out.

A content calendar helps you make that consistency sustainable. Tools like Notion, Trello, or Google Sheets work fine for scheduling. 

Plan your topics by theme (e.g., SEO tips one week, case studies the next) and map your filming and editing days so uploads never sneak up on you.

Track ideas that come from your comments or analytics. If a video starts outperforming, use it as a springboard for spinoff Shorts or deeper follow-ups.

Think of your calendar as a publishing system and pillar of your overall content marketing strategy. It keeps you accountable and makes sure every video ladders back to your larger YouTube marketing strategy.

Design the Right YouTube Thumbnails

Your thumbnail is the visual hook. It’s what earns the click.

Today’s best-performing thumbnails are simple, bold, and emotionally clear. 

  • Avoid clutter and heavy text. 
  • Focus on one focal point: a face, an object, or a clear action shot. 
  • Add minimal copy (four words or fewer) that reinforces the video title rather than repeating it.

Bright, high-contrast colors still grab attention, but brand consistency matters more. Stick to the same font, color palette, and framing so viewers instantly recognize your channel.

Latest video thumbnails on MrBeast’s YouTube channel

(Image Source)

Pro tips:

  • Faces win. Thumbnails with expressive faces tend to get higher click-through rates.
  • Use visual contrast. Use a light subject and dark background (or the reverse).
  • Keep it honest. Don’t mislead viewers with clickbait. You’ll hurt retention and trust.
  • Design mobile-first. Nearly 70 percent of views happen on phones, so test how your thumbnails look small. According to NP Digital, B2C content gets nearly 60 percent of views on mobile, with just under 50 percent for B2B content.
A graph showing the mediums via which people consume YouTube content, broken down by B2B and B2C content. Mobile leads the way, followed by computer, TV, and tablets.

Tools like Canva and Figma make quick testing easy. Create two to three versions, check CTR in YouTube Studio, and double down on what performs.

Part 3: Use YouTube SEO to Increase Traffic

YouTube is more than a social platform. It’s the second-largest search engine after Google, with more than 20 million videos uploaded every day. 

That’s your competition.

The good news? You can still rank high without ads if you know how to optimize your videos for search.

In this section, we’ll cover the basics, like how to research keywords, write clickable titles and descriptions, and structure your videos for discoverability. 

If you want a deeper dive into the full process, check out my full guide on YouTube SEO.

Keyword Research on YouTube

Every strong YouTube SEO strategy starts with keyword research. You can’t optimize what you haven’t defined.

Look for keywords your audience is already searching for. Tools like Ubersuggest, TubeBuddy, and vidIQ can show search volume, competition level, and related keyword ideas directly from YouTube data.

Here’s the key: YouTube search intent isn’t always transactional. It’s informational. 

So, focus on “how to,” “best,” “tutorial,” and “review” phrases. They’re gold because they match how users search when they’re ready to learn or buy.

Writing Great Descriptions

Your description is prime SEO real estate. YouTube gives you 5,000 characters to work with. Use it.

Start strong. Mention your focus keyword in the first 25 words and naturally repeat it two or three times throughout. Use short paragraphs or bullet points so it’s easy to skim.

Structure your description like this:

  1. Hook: One or two sentences that summarize the value of the video.
  2. Context: Expand on the topic, naturally using keywords.
  3. Next steps: Include links to related videos, your website, or lead magnets.
A video description for “The ChatGPT Study That Could Explode Your Traffic” on Neil Patel’s YouTube channel.

Add timestamps for long-form videos and external links above the fold (before the “Show More” cutoff).

Above all, don’t keyword stuff. Write like you’re helping a person, not an algorithm. The algorithm will notice anyway.

How to Write a Great YouTube Title

This is one area you cannot ignore. Even if your content is great, it won’t matter if you can’t get people to actually click on your video in the first place.

A strong title can make or break your video’s performance. You only get about 50 to 55 visible characters on desktop, so every word counts.

Good titles combine clarity, curiosity, and keywords. For example:

  • “SEO for Beginners: 5 Fast Ways to Rank Higher on Google”
  • “I Tried YouTube Shorts for 30 Days. Here’s What Happened”

Keep it natural, and don’t force full keyword phrases if they sound robotic. Use parentheses or numbers to add clarity:

  • “Email Marketing Tips (That Actually Work in 2025)”
  • “Top 10 Tools for Video Editors”

Business Insider does a solid job of writing concise, compelling (and clickable) titles:

Thumbnails and titles of various videos on the Business Insider YouTube channel.

Avoid ALL CAPS or excessive punctuation. It reads like spam.

Pair your title with a strong thumbnail so the story connects visually. YouTube reads that combination as a signal of quality and relevance.

Add Closed Captions and Transcripts on Videos

Captions do more than make your videos accessible. They make them searchable.

When you upload closed captions or full transcripts, YouTube indexes that text. That means every word in your video becomes a keyword opportunity.

Turn on auto-captioning, but always edit the results for accuracy. If you already have a script, upload it as a transcript to save time.

Bonus: Captions help with international reach. You can upload translated subtitles for new audiences without creating new videos.

Think of captions as the hidden SEO layer that boosts both accessibility and discoverability.

Use YouTube Tags

Tags used to carry major weight in YouTube SEO; now, they play a smaller but still useful role.

Use tags to help YouTube understand your video’s context, especially if your topic has alternate spellings or similar keywords.

Start with 5 to 8 targeted tags, mixing broad and long-tail terms. For example:

  • “Video marketing”
  • “YouTube marketing strategy”
  • “How to grow on YouTube in 2025”

Avoid adding dozens of unrelated tags, as it can dilute your relevance score. 

Drive Likes, Comments and Subscriptions

Engagement is fuel for the YouTube algorithm. When people like, comment, and subscribe, YouTube sees your content as valuable and pushes it to more viewers.

But don’t just say, “Like and subscribe.” Give people a reason. For example:

  • Ask a question mid-video to prompt comments.
  • Add a simple end-screen with a subscribe CTA.
  • Thank viewers for specific feedback in your next upload.

Subscriptions signal trust, comments signal community, and likes signal quality. Each tells YouTube, “This video was worth watching.”

Track engagement in YouTube Studio, and use those patterns to adjust your intros, pacing, and calls to action (CTAs).

Part 4: How to Produce a Great YouTube Video

Every strategy we’ve talked about so far leads here: the video itself. Your titles, thumbnails, and descriptions only work if the video delivers real value and keeps people watching.

Think of this section as the engine behind your YouTube marketing strategy. It’s where ideas turn into content that earns retention, watch time, and trust—the three metrics that drive long-term growth.

Let’s break down how to build better videos from script to finish: how to structure your story, hold attention, and guide viewers to take the next step.

Build Your Video Script

You don’t need a Hollywood script, but you do need a plan. Even spontaneous creators outline what they’ll say before hitting record.

A good YouTube script keeps your message tight, your pacing smooth, and your delivery confident. An outline like this is a good starting point:

  1. Hook (0-10 seconds): Why this topic matters now.
  2. Setup: What you’ll cover and what viewers will get from it.
  3. Main content: Teach, demonstrate, or share insight clearly.
  4. CTA: What to do next. That might be to watch, subscribe, or click a resource.

Write in your speaking voice. In other words, lean into short sentences and natural pauses.

The best videos feel conversational but stay focused. Always come back to why your audience should care. If a line doesn’t serve that, cut it.

Pro tip: record a test run. If your energy dips or you ramble, your audience will, too.

Create a Great Opening and Sustain Viewer Attention

YouTube’s data says the first 15 seconds of a video is your make-or-break moment.

So, start fast. Skip the long intro slides or slow fades. Jump straight into the payoff: the problem you’re solving or the question you’re answering.

Great openings often share three traits:

  • Strong hook: Lead with curiosity or a bold promise.
  • Visual movement: Add a quick cut, prop, or change in camera angle early.
  • Context: Tell them what they’ll learn and why it matters, quickly.

A good example is my video titled “How to Master Social Media in 2025.” 

Here, I:

  • Lead with the outcome (“Master Social Media in 2025”), not just the topic.
  • Open with quick b-roll of trending social platforms before it cuts to me on camera; the motion and pattern change instantly catches the eye.
  • Establish relevancy and immediacy within the first few seconds.

In your videos, keep the momentum with pattern shifts every 15 to 20 seconds: zooms, graphics, or scene changes. 

An average view duration of 50-60 percent is considered good, while anything above 70 percent is considered excellent. Hitting at least that 50 percent mark is key to YouTube continuing to push your video to new audiences.

Create Calls to Actions Through Info Cards and End Screens

A video without a next step is a dead end.

Use info cards and end screens to guide viewers while attention is still high.

  • Info cards: Add mid-video links to related videos or playlists. Drop them right after a key insight, not randomly.
  • End screens: Use the last 20 seconds to point to one next video, a playlist, or a subscribe button, but never all three.

Keep CTAs natural. Instead of “Please subscribe,” try, “If this helped, you’ll love my next video on [topic]. It’s linked right here.”

Check out this example from TPMvids.

An end-screen CTA for a TPMvids YouTube video titled “Top 10 Disney Fails & Animatronics Malfunctions.”

These small nudges turn casual viewers into repeat watchers and subscribers, which boosts session time. And that’s one of the biggest ranking signals in YouTube’s algorithm.

Part 5: Promoting Your YouTube Channel

YouTube’s recommendation system drives most discovery, but it’s not magic. You still have to push your videos into the world. 

While most YouTube traffic comes from internal algorithmic recommendations, external shares and embeds drive some of the most engaged views, around 8–15 percent of total watch time. 

And that can kickstart the algorithm to promote your video further, making promotion off-platform invaluable.

Promotion is where strategy meets visibility. In this section, we’ll cover four proven ways to get your channel in front of more viewers: 

  • Cross-promotion on other platforms
  • Collaborations
  • Influencer partnerships
  • Community engagement

Using Cross Promotion With Your Other Social Media Accounts

Don’t just drop your YouTube link everywhere. Tailor it. Each platform favors a different video format and audience mindset:

  • Instagram Reels / TikTok: Slice up your most shareable Shorts or punchy moments. Add captions and a CTA like, “Full breakdown on my channel.”
  • LinkedIn: Share thought-driven clips or behind-the-scenes content that adds professional context.
  • Facebook / X (Twitter): Post native teasers or thumbnails linking directly to your newest upload.
  • Blog or email list: Embed full videos to keep people on-site longer.

Here’s an example of a short clip my team dropped on TikTok.

Neil Patel speaks in a video clip posted on TikTok.

Cross-promotion works best when each post feels native to the platform. Don’t treat it like a copy-paste link dump.

Cross-Promote With Other Channels

Collaborations are the fastest way to borrow trust. Find channels with overlapping but not identical audiences. In other words, look for similar topics or complementary angles.

Start by searching your niche keywords and filtering by upload date to spot active creators. Tools like Social Blade can reveal engagement and audience size before you reach out.

Pitch collaborations that add value to both sides:

  • Co-host a live Q&A or short challenge.
  • Swap “guest clips” where each creator adds one insight to the other’s video.
  • Build a joint playlist that benefits both channels’ discovery.

When you collaborate, you tap into built-in credibility. It’s one of the most cost-effective ways to introduce your content to qualified viewers.

Consider Influencer Marketing

One of the fastest ways to grow a YouTube channel is to borrow someone else’s audience. 

Influencer marketing makes that possible.

You don’t need to work with A-list creators to see results. In fact, micro-influencers often drive better engagement than large creators. Their audiences feel more connected, which means more real traffic for you.

BusinessInsider's YouTube Page.

Start by looking for creators in your niche who share your target audience but don’t post the same type of content. 

If you teach SEO, partner with a design or copywriting channel. You’ll both reach new viewers without stepping on each other’s toes.

Collaboration videos still work great. Film a challenge, swap expert tips, or make a guest appearance on each other’s channels. Just make sure the partnership feels natural and mutually beneficial. Forced collabs turn viewers off.

As your channel grows, return the favor. Supporting smaller creators builds goodwill and can bring you some of the most loyal fans you’ll ever get.

Build a Community on YouTube By Engaging With Your Audience

Community is what turns viewers into advocates.

Reply to comments within the first hour of posting. It boosts engagement signals and shows you’re active. Use the Community tab to post polls, updates, or behind-the-scenes thoughts between uploads.

Other smart plays:

  • Host live streams or ask-me-anythings (AMAs) to build real-time interaction.
  • Shout out viewer ideas or feedback in future videos.
  • Ask your audience for input on new topics or titles.

Channels with active comment threads and regular audience participation tend to hold viewers longer. Engagement sends a strong signal to YouTube that your content is resonating, which helps videos appear more often in recommendations. 

Your videos start the conversation that your community keeps going.

Part 6: YouTube Marketing Tools

Even great ideas fall flat without the right setup. 

The good news? 

You don’t need a production studio to run a professional channel. But you do need the right stack of tools.

Start with video creation and editing.

  • Descript lets you edit videos by editing text. It’s perfect for quick cuts, captions, and repurposing clips for Shorts or LinkedIn.
  • CapCut and Premiere Rush are ideal for mobile and social-first editing, simple, fast, and powerful enough for branded content.
  • If you’re producing tutorials, tools like Loom or ScreenPal (formerly Screencast-O-Matic) make screen recording easy.

Next, focus on optimization.

  • TubeBuddy and vidIQ plug directly into YouTube Studio to help with keyword suggestions, tag ideas, A/B testing for thumbnails, and SEO checklists.
  • Canva streamlines thumbnail design with preset YouTube templates and brand color kits.

For analytics, lean on data:

  • YouTube Studio gives detailed retention graphs and click-through data, but pair it with Ubersuggest or Google Analytics to see how YouTube traffic flows to your website.
  • Tools like Social Blade let you benchmark against competitors and spot growth trends.

Part 7: YouTube Paid Advertising

Organic reach takes time, but YouTube ads can fast-track visibility when done right. Paid campaigns let you target by audience, topic, and intent. That way, your content reaches the people most likely to act.

Let’s break down the core ad types and how to make them work.

Understand the Main YouTube Ad Formats

YouTube offers several ad options, but these three drive the most results for marketers:

  • Skippable in-stream ads: Appear before or during videos. Viewers can skip after five seconds, so make your hook count. The first line and first visual should tell them why to keep watching.
  • Non-skippable in-stream ads: Capped at 15 seconds; best for brand awareness or quick product demos.
  • In-feed video ads: Show up in search results and “related videos” sections. These work like organic videos, ideal for promoting tutorials or long-form educational content.

Best Practices for YouTube Ad Success

  • Hook immediately. Your first five seconds decide everything. Lead with a visual or statement that grabs attention.
  • Target precisely. Use audience segments—custom intent, remarketing lists, or lookalike audiences—to reach people ready to buy.
  • Keep it short and focused. Under 30 seconds is best for direct-response goals; longer formats work for storytelling or education.
  • Add a clear CTA. Whether it’s “Learn More,” “Subscribe,” or “Shop Now,” make it obvious and actionable.
  • Test variations. Run A/B tests on thumbnails, headlines, and CTAs. Even small tweaks can double performance.

Pairing paid ads with your organic content strategy multiplies reach. You build awareness fast and nurture those viewers with helpful videos afterward.

Frequently Asked Questions

What is the best strategy for YouTube?

The best YouTube strategy starts with clarity. Know exactly who you’re creating for and what value you bring. Focus on consistent uploads, strong storytelling, and search-optimized titles and descriptions. Promote your videos across other channels, collaborate with related creators, and use analytics to refine what’s working. When your content and audience focus align, growth follows.

How to grow your YouTube channel?

Growth comes from momentum. Post regularly (at least once a week), engage with your community, and optimize each video for SEO. Create a mix of long-form and short-form content, and always include clear calls to action that turn viewers into subscribers. Collaborate with other creators to tap into new audiences and expand reach faster.

How do you attract subscribers on YouTube?

Creating highly engaging videos is the first step to attracting subscribers. But you also need to write great titles and descriptions, work hard to promote your videos, and collaborate with other YouTubers to raise brand awareness.

How to gain subscribers on YouTube?

Viewers subscribe when they trust your content and know what to expect. Make your videos clear, consistent, and valuable from the start. End each one with a reason to subscribe, like “new videos every Tuesday” or “more quick tips coming next.” Reply to comments, mention loyal fans in videos, and use playlists to keep new viewers watching longer.

What is the best content to create on YouTube?

The best content teaches, entertains, or solves a problem—ideally, all three. Tutorials, reviews, and “how-to” videos tend to perform best, especially when tied to specific search intent. Short-form videos (YouTube Shorts) are perfect for quick tips and discovery, while longer videos build authority and watch time. Test formats, watch your analytics, and double down on what your audience finishes watching.

Conclusion

Congrats on making it through this full YouTube marketing guide. Now you’re set to become the next YouTube star.

Start small, stay consistent, and focus on value over virality. Every upload teaches you something about your target audience and sharpens your message.

So grab your camera and get your ideas out there. Your next great video could be the one that changes everything.

You might not see huge traction after your first video, and that’s okay. Keep showing up with quality, purpose, and a plan. Over time, those small wins compound into serious momentum.

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Google Ads quietly rolls out a new conversion metric

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How Google Ads’ AI tools fix creative bottlenecks, streamline asset creation

A new column called “Original Conversion Value” has started appearing inside Google Ads, giving advertisers a long-requested way to see the true, unadjusted value of their conversions.

How it works. Google’s new formula strips everything back:

Conversion Value
– Rule Adjustments (value rules)
– Lifecycle Goal Adjustments (e.g., NCA bonuses)
= Original Conversion Value

Why we care. For years, marketers have struggled to isolate real conversion value from Google’s layers of adjustments — including Conversion Value Rules and Lifecycle Goals (like New Customer Acquisition goals). Original Conversion value makes it easier to diagnose performance, compare data across campaigns, and spot when automated bidding is boosting value rather than actual conversions.

In short: clearer insights, cleaner ROAS, and more confident decision-making.

Between the lines:

  • Value adjustments are useful for steering Smart Bidding.
  • But they also inflate numbers, complicating reporting and performance analysis.
  • Agencies and in-house teams have long asked Google for a cleaner view.

What’s next. “Original Conversion Value” could quickly become a go-to column for:

  • Revenue reporting
  • Post-campaign analysis
  • Troubleshooting inflated ROAS
  • Auditing automated bid strategies

First seen. This update was first picked up by Google Ads Specialist Thomas Eccel when he shared spotting the new column on LinkedIn

The bottom line. It’s a small update with big clarity. Google Ads is giving marketers something rare: a simpler, more transparent look at the value their ads actually drive.

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I Tested 11 AI Search Engines: Only These 4 Made the Cut

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Ask the same question in 11 AI search engines, and you’ll get 11 different answers.

Sometimes wildly different.

Some engines focus on visuals and shoppable results. Others go deep into research. A few just try to get you an answer, fast.

Each platform prioritizes and presents it differently.

And those differences matter.

Not just for users, but for brands trying to get discovered in AI search.

So, I tested popular and lesser-known AI engines on accuracy, depth, user experience, and other factors.

Only four made the cut.

In this guide, you’ll learn which AI search engines came out on top, including pros, cons, and pricing. I’ll also share which engines didn’t make my list, and why.

Along the way, you’ll get a few tips on using these insights to improve your AI visibility.

Start with a quick overview of my findings below. Or jump straight to the #1 AI search engine on my list: ChatGPT.

What Are the Best AI Search Engines?

Tool Best for Pros Cons Price
ChatGPT Comprehensive research and shoppable product comparisons Visual layout with tables and images; remembers context across follow-ups; direct purchase links Overwhelming results for broad queries; accuracy issues; overly agreeable Free or $20+/month
Google AI Mode Quick product searches with real buyer reviews Fast product results with pricing and reviews; integrates Google ecosystem Vague on informational queries; no comparison tables; unavailable in some regions Free
Sigma Chat (Formerly Bagoodex) Research deep dives that build on previous questions Strong conversational memory; suggests follow-up questions; content creation prompts Weak product presentation; no pricing or buy links; poor visuals Free or $10+/month
Microsoft Copilot Fast answers in clean, skimmable formats Clean categorization; fast responses; easy to skim Surface-level depth; no product links; weak for shopping Free

How I Tested 11 AI Search Engines

To keep things consistent, I ran the same set of prompts across 11 AI search tools.

Note: For this article, I defined “AI search engine” as any generative AI platform that can understand queries, pull information from sources, and deliver answers in natural language.

This included big names like ChatGPT, AI Mode, and Perplexity.

And newer players like Arc, Andi, and Sigma Chat.

Andi Search – How long do running shoes last

I focused on one topic (running shoes) and tested a range of prompts across different search intents.

This showed how well each engine handled the full customer journey, from research to shopping.

This included:

  • “Best running shoes”: Assesses top-level recommendations and how each engine handles broad prompts
  • “Best running shoes for beginner marathon training”: Evaluates personalization and context handling as the prompt narrows
  • “How long do running shoes last?”: Gauges accuracy on general product knowledge and durability expectations
  • “Of the trainers you’ve recommended, which ones will last the longest?”: Tests the accuracy of product details and the engine’s ability to remember details from previous prompts
  • “Can I wear any of these running shoes recommended for hiking?”: Assesses how each AI handles reasoning, real-world nuance, and potential safety considerations

ChatGPT – Shoes for hiking

I evaluated each tool on five factors:

  • Accuracy: Did it understand the intent and get the facts right?
  • Depth: Did it add helpful context or just summarize existing content?
  • Transparency: Did it credit or link to its sources?
  • User experience: Was the output fast, skimmable, and well-organized?
  • Adaptability: Could it handle follow-up questions naturally or refine vague prompts?

After testing all 11 AI search engines, these four stood out as the best for different reasons.

1. ChatGPT

Best for comprehensive research and shoppable product comparisons

ChatGPT – Homepage

ChatGPT came out on top overall.

It delivered the best balance of accuracy, organization, and depth. Plus, it showed an “understanding” of search intent and included helpful visuals.

What ChatGPT Does Well

ChatGPT provides detailed, well-formatted answers.

This is true whether you’re comparing products, researching topics, or looking for a step-by-step tutorial.

ChatGPT – Best running shoes

It also remembers context across follow-up questions.

I started with a broad prompt and added specifics as the conversation progressed. ChatGPT remembered key details without making me repeat myself.

For shopping queries, the visual presentation stood out.

When I searched for running shoes, for example, ChatGPT returned products with images, prices, reviews, and short descriptions.

It also included links to retailers and external articles. This made verifying product details and purchasing easy.

ChatGPT – Links to external articles

The summary tables were particularly useful.

After inquiring about shoe lifespan, ChatGPT delivered a clean comparison table with products and their expected mileage.

ChatGPT – Summary Table – Running shoes

For brands: ChatGPT’s visual layout isn’t just useful for shoppers. If you’re trying to get your brand referenced by AI search engines, it also reveals what these models prioritize. Use tables, clear specs, and organized categories on your product pages to help both shoppers and AI find your information faster.

ChatGPT is also evolving quickly.

Features like Instant Checkout (currently limited to select Etsy sellers in the United States) let users complete purchases directly inside the chat.

ChatGPT – Full shoping destination

Great for shoppers — and even greater for the brands featured in ChatGPT’s recommendations.

Where ChatGPT Falls Short

When I tested ChatGPT, I got what most people want from AI search: answers that feel confident and complete.

But not every response was perfect.

Broad prompts, such as “Best running shoes,” resulted in lengthy lists of brands, product categories, and features.

The information took real effort to digest.

ChatGPT – Top picks by category – Running shoes

Specific prompts worked much better.

I also noticed minor inaccuracies in some instances, like when I asked about shoe lifespan.

After fact-checking the replies, some details didn’t match the manufacturer’s specifications.

For example, ChatGPT said the Brooks Ghost running shoe has a lifespan of 450 to 500 miles. But the actual range is 300 to 500 miles.

ChatGPT – The longest lasting trainers

This also highlights a larger problem.

ChatGPT pulls information from multiple sources, such as blog posts and brand sites.

But it also relies on forums like Quora and Reddit, where users share personal experiences.

Reddit – Relies on forums

It then aggregates the information into its responses. This can lead to inaccurate and misleading information.

For brands: Provide clear answers to common user questions on your site. Otherwise, AI search engines may turn to other, potentially inaccurate sources for this information. Add tables with specifications, be explicit about ranges and measurements, and use structured data so AI can extract and cite your product information correctly.

ChatGPT also tends to be overly agreeable.

Whatever you prompt, ChatGPT will lean toward flattery and agreement — even when it involves safety.

For example, when I asked, “Can I wear any of these running shoes recommended for hiking?”

ChatGPT’s response was:

“Good question 👍 — you can hike in road running shoes, but whether it’s a good idea depends on the terrain and how far you’re going.”

Not the worst.

But not as good as other AI search engines in this aspect, like AI Mode, which was more cautious.

AI Mode said:

“It is not recommended to use the road running shoes previously mentioned for hiking…they lack the key features that provide the necessary grip, protection, and stability for off-road trails. Using them for hiking could lead to injury.”

Overall, ChatGPT is fast, detailed, and helpful.

But it can be too generous with information — and too polite to push back.

Pricing

ChatGPT – Pricing

ChatGPT offers three plans based on your needs.

  • Free: Limited access to some features
  • Plus: $20/month
  • Pro: $200/month for extended features

Further reading: Google Gemini vs. ChatGPT: Which AI Chatbot Is Better?

2. Google AI Mode

Best for quick product searches with real buyer reviews

Google AI Mode – Homepage

Google’s AI Mode is built for speed.

It pulls product listings, prices, and reviews directly into the search interface. This makes it ideal for shoppers who want to quickly compare products before purchasing.

What AI Mode Does Well

AI Mode shines when you have clear buying intent.

It instantly surfaces product options with images, prices, star ratings, and quick links to retailers. And it’s all in a clean, scrollable layout.

Google AI Mode – Best running shoes

When I searched “best running shoes,” it showed a curated carousel of options with price comparisons across multiple sites.

Google AI Mode – Open drop down on the right

I especially liked how it paired Google Reviews with its recommendations — a small detail that makes decision-making faster and builds trust.

Google AI Mode – Google reviews & recommendations

For me, that worked perfectly.

Getting straight to the products moved me faster toward a decision.

But some users may prefer more background or context for researching and weighing options. ChatGPT’s research-style answers still win in this regard.

For brands: AI Mode pulls heavily from Google Reviews and structured product data. Focus on getting detailed, positive reviews and keeping your product schema markup up to date. These signals can influence whether your products appear in AI-generated results.

Where AI Mode Falls Short

AI Mode is not yet available in all countries, although it’s rolling out quickly.

And unlike ChatGPT, it didn’t provide any comparison tables for any of my prompts. Just products and bullet points.

This meant more scrolling and clicking to find and digest the information.

Google AI Mode – Bullet points

This was evident when I asked which of the recommended shoes would last the longest.

AI Mode’s response was vague and unhelpful. It said the Brooks Ghost shoe was “exceptionally long-lasting.”

It didn’t provide any of the specifics that would make me want to purchase this shoe. Like mileage range and how it differed between the options.

Google AI Mode – Listings on the left

If you’re early in the evaluation phase, AI Mode can feel limiting.

But it delivers when you want a shortlist of top contenders.

Pricing

AI Mode is available for free within Google Search, depending on your region.

Further reading: LLM Seeding: A Strategy to Get Mentioned and Cited by LLMs

3. Sigma Chat (Formerly Bagoodex)

Best for research deep dives that build on previous questions

Sigma Chat – Homepage

Sigma Chat’s iterative search and in-depth replies are excellent if you love to research.

Ask a question, get an answer, then drill deeper into related topics — and it remembers the full thread.

Note: Bagoodex launched in 2024 and has since rebranded as Sigma Chat. For this review, I tested it against the standard modes of other tools. ChatGPT’s Thinking mode and Perplexity’s Research mode are designed for deep research and may perform differently.

What Sigma Chat Does Well

Sigma Chat stood out for its ability to build on previous context.

When I asked follow-up questions, it remembered what I’d already searched and adjusted its answers accordingly.

No need to repeat myself or reframe the entire query.

For example, after I asked which of the recommended shoes would last the longest, it specifically referenced “marathons.”

(Even though I hadn’t mentioned this criterion again after the initial prompt.)

Sigma Chat – Build on previous context

Sigma Chat’s follow-up suggestions also stood out for their potential to aid deep research.

Instead of ending with one answer, it nudged me toward related questions I hadn’t considered:

  • Beginner running shoes fitting
  • Marathon training schedule
  • Foot pronation assessment

Sigma Chat – Follow upsv

Sigma Chat anticipates knowledge gaps and identifies adjacent topics worth exploring.

This makes it particularly helpful for any kind of research, whether you’re comparing products, building content outlines, or researching niches.

Sigma Chat – Foot pronation

For brands: Sigma Chat rewards depth and topic clustering. To increase visibility in AI tools like this, build content hubs around your main topics — link related pages together and cover every sub-question your audience might ask. The more complete your coverage, the easier it is for AI to surface your site in deep research queries.

Another interesting feature of this AI search engine?

It suggests prompts tailored to content creation. This is especially helpful if you’re using it for marketing purposes.

After providing search results for the best running shoes for a marathon, it offered unexpected options like:

  • “Write a blog post about this topic”
  • “Create an image on this topic”

I tested the blog prompt, and it generated a quick draft titled “Marathon Training on a Budget: Choosing Durable Running Shoes.”

It wasn’t something you’d publish as-is, but it was a decent starting point.

If you’re prone to writer’s block or need to quickly draft comparison content around competitor products, it’s a particularly helpful feature.

Sigma Chat – Blog prompt

From there, it suggested additional prompts like “Add a call to action” and “Shorten for social media.”

This makes it easy for marketers to generate content for multiple platforms at once.

Sigma Chat – Suggested additional prompts

Further reading: How to Use AI for Writing Exceptional Content

Where Sigma Chat Falls Short

Sigma Chat’s presentation still needs work.

When I searched “best running shoes,” it opened with generic photos pulled from listicles.

This is a wasted use of prime real estate — they could’ve shown real products or reviews to provide more value.

Sigma Chat – Best running shoes

There are also no pricing details, reviews, or direct purchasing links.

But Sigma Chat does cite its sources.

In fact, it cited the same comparison article multiple times. (Helpful for that site’s traffic, not so helpful for someone ready to purchase.)

Sigma Chat – Cite sources

Unless Sigma Chat improves its commercial functionality, it’s unlikely shoppers will use it.

Instead, it might carve out a niche for itself as a deep research tool.

Pricing

Sigma Chat – Pricing

Sigma Chat offers a few plans with varying access and features:

  • Free: Basic search and chat capabilities
  • SigmaChat Plus: $10/month for increased access
  • SigmaChat Pro: $75/month for unlimited access

Further reading: 6 Awesome AI SEO Tools We Love Using

4. Microsoft Copilot

Best for fast answers in clean, skimmable formats

Microsoft Copilot – Homepage

Microsoft Copilot has the cleanest layout of any AI search engine I tested.

It’s fast, structured, and organized. Perfect for people who want distraction-free takeaways.

What Microsoft Copilot Does Well

When you ask Copilot a question, it responds instantly with skimmable categories, bullet points, and emojis.

For example, when I searched “best running shoes,” it broke recommendations into helpful categories:

  • “Best overall”
  • “Best stability shoe”
  • “Best daily trainer”

Copilot Microsoft – Best running shoes

When I narrowed the query to “best running shoes for beginner marathon training,” Copilot further refined the results.

It added details about who each shoe was best for, making the advice more actionable — a nice touch for a tool focused on clarity.

Copilot Microsoft – More actionable advice

Even for informational queries like “can I wear these for hiking,” Copilot delivered a simple breakdown.

And added specific scenarios where running shoes would and wouldn’t be ideal for hiking.

Copilot Microsoft – Simple breakdown

When you want fast, direct answers without having to sift through a bunch of content, Copilot is a great option.

For brands: Pay close attention to how Copilot structures its answers — categories, comparisons, “best for” labels. Use similar formatting on your own pages to help AI tools extract and present your content more effectively.

Where Microsoft Copilot Falls Short

Copilot’s polished format comes at a cost: depth and shoppability.

Its responses are tidy but often too surface-level — especially for commercial searches like “best running shoes.”

When I tested this prompt, it didn’t link directly to any product pages or show pricing.

So, I couldn’t easily comparison shop, verify information, or choose a merchant and purchase immediately.

Instead, it summarized content from other “best” listicles and linked those sources.

Copilot Microsoft – Don't link directly & no pricing

Like Sigma Chat, unless Microsoft improves its shoppability, it’s unlikely consumers will use it for this purpose.

Instead, Copilot works better as a light research tool — especially when you want fast information with minimal reading.

Pricing

Microsoft Copilot is free to use.

Further reading: 5 LLM Visibility Tools to Track Your Brand in Search

AI Search Engines That Didn’t Make the Cut (and Why)

All of these AI search engines had their pros and cons.

But overall, they fell short for different reasons.

Claude

I really liked Claude, but the output was very similar to ChatGPT.

This isn’t a problem, but I didn’t want to list tools that were similar in functionality.

I wanted to provide only the best.

Compared to ChatGPT, Claude lacked product links and visuals:

Claude – Lacks product links & visuals

The wall of text made the information challenging to process.

I did like the categorization, but ChatGPT does this too — with tables that are easier to skim.

Perplexity

Like Claude, Perplexity came somewhat close to ChatGPT in overall performance.

When asked a prompt with buying intent, it provided a short summary along with product images, pricing, and star ratings.

No tables to help me quickly compare features and options, though.

Perplexity – Best running shoes

The summary was also fairly generic.

And didn’t feel all that tailored to my prompt, even when I used the more specific “marathon” wording.

Perplexity – Running shoes – Generic summary

Brave

Brave, a privacy-focused AI search engine, felt too much like traditional search.

Brave – Best running shoes – Ask

It features long lists of articles without any clear hierarchy or comparison features.

While this might be helpful for browsing links, it doesn’t summarize much or help you make quick decisions.

Andi

Andi, a minimal AI search tool, offered few results, sometimes just one (e.g., a single Reddit thread).

Andi Search – Best running shoes

It’s a bit like the “I’m Feeling Lucky” button on Google. Simple to use but extremely limiting for in-depth research or shopping.

Arc

Arc, a mobile- and browser-based AI search engine, requires a download to use.

Arc – Search

This is inconvenient compared to browser-based AI search.

When so many other options exist, it’s hard to justify using this AI engine for this reason alone.

You

You is a solid AI search engine that has been around for multiple years.

You – Best running shoes

But it was slow to respond and didn’t link to products in commercial searches.

Ultimately, I found it less useful than the other AI tools overall.

What This Means for Your AI Search Visibility

After testing 11 AI search engines, one thing became clear.

No matter how their formatting or preferences differ, the goal remains the same: to serve clear, credible, and well-structured content.

If your pages do that — with comprehensive coverage, positive reviews, and clean markup — you’ll be positioned to perform well across all AI search engines and LLMs.

Want to make that happen?

Our generative engine optimization (GEO) guide shows how to structure your site, earn more citations, and track your AI visibility.

The post I Tested 11 AI Search Engines: Only These 4 Made the Cut appeared first on Backlinko.

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82% of marketers fail AI adoption (Positionless Marketing can fix it) by Optimove

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Picture a chocolate company with an elaborate recipe, generations old. They ask an AI system to identify which ingredients they could remove to cut costs. The AI suggests one. They remove it. Sales hold steady. They ask again. The AI suggests another. This continues through four or five iterations until they’ve created the cheapest possible version of their product. Fantastic margins, terrible sales. When someone finally tastes it, the verdict is immediate: “This isn’t even chocolate anymore.”

Aly Blawat, senior director of customer strategy at Blain’s Farm & Fleet, shared this story during a recent MarTech webinar to illustrate why 82% of marketing teams are failing at AI adoption: automation without human judgment doesn’t just fail. It compounds failure faster than ever before. And that failure has nothing to do with the technology itself.

The numbers tell the story. In a Forrester study commissioned by Optimove, only 18% of marketers consider themselves at the leading edge of AI adoption, even though nearly 80% expect AI to improve targeting, personalization and optimization. Forrester’s Rusty Warner, VP and principal analyst, puts this in context: only about 25% of marketers worldwide are in production with any AI use cases. Another third are experimenting but haven’t moved to production. That leaves more than 40% still learning about what AI might do for them.

“This particular statistic didn’t really surprise me,” Warner said. “We find that a lot of people that are able to use AI tools at work might be experimenting with them at home, but at work, they’re really waiting for their software vendors to make tools available that have been deemed safe to use and responsible.”

The caution is widespread. IT teams have controls in place for third-party AI tools. Even tech-savvy marketers who experiment at home often can’t access those tools at work until vendors embed responsible AI, data protections and auditability directly into their platforms.

The problem isn’t the AI tools available today. It’s that marketing work is still structured the same way it was before AI existed.

The individual vs. the organization

Individual marketers are thirsty for AI tools. They see the potential immediately. But organizations are fundamentally built for something different: control over brand voice, short-term optimization and manual processes where work passes from insights teams to creative teams to activation teams, each handoff adding days or weeks to cycle time.

Most marketing organizations still operate like an assembly line. Insights come from one door, creative from another, activation from a third. Warner called this out plainly: “Marketing still runs like an assembly line. AI and automation break that model, letting marketers go beyond their position to do more and be more agile.”

The assembly line model is excellent at governance and terrible at speed. By the time results return, they inform the past more than the present. And in a world where customer behavior shifts weekly, that lag becomes fatal.

The solution is “Positionless Marketing,” a model where a single marketer can access data, generate brand-safe creative and launch campaigns with built-in optimization, all without filing tickets or waiting for handoffs. It doesn’t mean eliminating collaboration. It means reserving human collaboration for major launches, holiday campaigns and sensitive topics while enabling marketers to go end-to-end quickly and safely for everything else.

Starting small, building confidence

Blain’s Farm & Fleet, a 120-year-old retail chain, began its AI journey with a specific problem: launching a new brand campaign and needing to adapt tone consistently across channels. They implemented Jasper, a closed system where they could feed their brand tone and messaging without risk.

“We were teaching it a little bit more about us,” Blawat said. “We wanted to show up cohesively across the whole entire ecosystem.”

Warner recommends this approach. “Start small and pick something that you think is going to be a nice quick win to build confidence,” he said. “Audit your data, make sure it’s cleaned up. Your AI is only going to be as good as the data that you’re feeding it.”

The pattern repeats: start with a closed-loop copy tool, then add scripts to clean product data, then layer in segmentation. Each step frees time, shortens cycles, and builds confidence.

Where data meets speed

Marketers aren’t drowning in too little data. They’re drowning in too much data with too little access. The 20% of marketing organizations that move fast centralize definitions of what “active customer,” “at risk,” and “incremental lift” actually mean. And they put those signals where marketers work, not in a separate BI maze.

“There’s massive potential for AI, but success hinges on embracing the change required,” Warner said. “And change is hard because it involves people and their mindset, not just the technology.”

The adoption lag isn’t about technology readiness. It’s about organizational readiness.

Balancing automation and authenticity

Generative AI took off first in low-risk applications: creative support, meeting notes, copy cleanup. Customer-facing decisions remain slower to adopt because brands pay the price for mistakes. The answer is to deploy AI with guardrails in the highest-leverage decisions, prove lift with holdouts and expand methodically.

Blawat emphasized this balance. “We need that human touch on a lot of this stuff to make sure we’re still showing up as genuine and authentic,” she said. “We’re staying true to who our brand is.”

For Blain’s Farm & Fleet, that means maintaining the personal connection customers expect. The AI handles the mechanics of targeting and timing. But humans ensure every message reflects the values and voice customers’ trust.

The future of marketing work

AI is moving from analysis to execution. When predictive models, generative AI and decisioning engines converge, marketers stop drawing hypothetical journeys and start letting the system assemble unique paths per person.

What changes? Less canvas drawing, more outcome setting. Less reporting theater, more lift by cohort. Fewer meetings, faster iterations.

Warner points to a future that’s closer than most organizations realize. “Imagine a world where I don’t come to your commerce site and browse. Instead, I can just type to a bot what it is I’m looking for. And I expect your brand to be responsive to that.”

That kind of conversational commerce will require everyone in the organization to become a customer experience expert. “It doesn’t matter what channel the customer uses,” Warner explained. “They’re talking to your brand.”

The path forward

There is no AI strategy without an operating model that can use it. The fix requires three fundamental changes: restructure how marketing work flows, measure lift instead of activity and enable marketers to move from idea to execution without handoffs.

The path forward requires discipline. Pick one customer-facing use case with clear financial upside. Define the minimum signals, audiences and KPIs needed. Enforce holdouts by default. Enable direct access to data, creative generation and activation in one place. Publish weekly lift by cohort. Expand only when lift is proven.

Warner expects adoption to accelerate significantly in 2026 as more vendors embed AI capabilities with proper guardrails. For brands like Blain’s Farm & Fleet, that future is already taking shape. They started with copywriting, proved value and are now expanding. The key was finding specific problems where AI could help and measuring whether it actually did.

AI will not fix a slow system. It will amplify it. Teams that modernize the way work gets done and lift the language of decisions will see the promise translate into performance.

As Blawat’s chocolate story reminds us, automation without judgment optimizes for the wrong outcome. The goal isn’t the cheapest product or the fastest campaign. It’s the one that serves customers while building the brand. That requires humans in the loop to point AI in the ri

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Minimizing Marketing Blind Spots: The New Era of Attribution

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Attribution in the modern marketing age can be confusing. But the pressure on marketing teams to “prove what’s working” never goes away. 

Traditionally, marketers had certain data we could always rely on, but the data pool we can pull from seems to be growing and shrinking at the same time. Between privacy constraints, zero-click searches, AI Overviews, and channel-walled gardens, marketers are flying blind in more ways than they realize. Attribution has always been an imperfect science. And in 2025, it’s gone from fuzzy to fragmented.

If you’re planning marketing budgets and trying to defend where your spend is going, there’s no need to freak out. Marketing attribution is possible. It doesn’t look like it used to, though. And if you’re still only relying on touch-based models or last-click reports, you might be measuring the wrong things entirely.

Let’s break down where attribution is failing, what’s making it harder, and what forward-looking marketers are doing to close the gap.

Key Takeaway

  • Attribution challenges have multiplied due to AI, automation, and privacy shifts.
  • Walled gardens, offline sales, and dark social are major blind spots, and they often overlap.
  • Deterministic, touch-based attribution is giving way to modeled and probabilistic methods.
  • AI isn’t just the problem, it’s also part of the solution.
  • You don’t need perfect data. You need data that helps you make better decisions.

The New Face of Attribution

Attribution used to be about stitching together clicks. Now, we’re lucky if we get clicks at all thanks to zero-click search.

Today’s buyers bounce between different platforms on multiple devices and AI-curated content. They’re influenced by ads on a connected TV or product mentions in a ChatGPT thread, and neither of those leaves a clean digital trail.

Meanwhile, ad platforms like Meta and Google have leaned hard into automation. That means fewer transparent levers to optimize and more “black box” performance metrics. According to NP Digital analysis, there are over 90% fewer optimization permutations in Google and Meta Ads today compared to 2023. So yes, marketing attribution is back. But the infrastructure around it seems more broken than ever.

A graphic explaining the collapse of optimization levers.

Finding Marketing Blindspots

Unfortunately, the reality is that attribution blind spots don’t come with a warning light. You may be staring directly at your dashboard and not notice traffic is piling up in areas you’re not tracking. And the amount of potential blindspots is growing.

Here are the big ones:

  • Walled Gardens: Platforms like Google, Meta, and Amazon are all powerful, but have become much more mysterious as search evolves. You’re renting their space, but if you don’t play by their rules, you may not get complete visibility.
  • Offline Sales: Leads turn into deals in CRMs, call centers, or retail. They may have started as a click, but the customer journey ends at a brick-and-mortar location or an entirely different platform than the original click.
  • Cross-Device Journeys: That ad someone saw on mobile might convert from their phone, but they could just as easily become a sale on their desktop or smart TV.
  • Building Awareness: Upper funnel spend (like digital out-of-home (OOH) or video) gets undervalued because it rarely leads to a direct conversion.
  • Dark Social: Private sharing (think WhatsApp, SMS, Signal) shows up in attribution models as “direct”, but it’s not.
  • LLM Traffic: People are discovering brands via large language models, and those referrals are often invisible in GA4.

To make matters worse, these blind spots can stack. Before you know it, you find yourself in a nightmare marketing scenario where you’re not just missing one data signal, you’re missing combinations of them, making optimization even harder.

A graphic that explains how multiple marketing blindspots can pile up.

New Attribution Trends and Technology

You can keep up with all of this. It just requires a switch in perspective. Marketers should evaluate their campaigns using a combination of modeled attribution and traditional touch-based metrics. You may never fully connect every dot, and that’s okay. The goal isn’t perfection, just enough clarity to defend marketing budget allocations.

Modern marketers are using these tools:

  • Incrementality testing: Geo holdouts and lift studies to isolate what’s actually moving the needle.
  • MMM (Marketing Mix Modeling): Especially useful for larger budgets or mixed channel strategies.
  • Correlation analysis: Pre/post testing, contextual lift, and even proxy signals like brand search volume.
  • Unified first-party data: Clean, consistent CRM and web data feeding both your models and your platforms.

The best strategies blend these methods based on spend level, complexity, and conversion volume. Leveraging AI in your marketing efforts is one of the best ways to automate this research as much as possible and maximize the benefit of these tactics. 

AI and Blind Spots

Some marketers may feel like AI is eroding attribution. While that could be true, the technology is also helping to rebuild it.

Here’s how AI is stepping in:

  • Generative AI: LLMs like ChatGPT are now discovery platforms. They drive traffic, but don’t always identify themselves unless you tag them.
  • AI coworkers: Agentic AI simulates user behavior, tests messaging, and can even help set up GA4 tracking automatically.
  • Machine learning models: Used in MMMs and platform attribution to refine forecasts, assign contribution, and make predictions.

Still, only 55% of marketers trust AI-generated insights, according to CoSchedule. The key is to treat AI as an assistant, not the authority. Use it to speed up testing and build models, but validate with your own data.

A graphic that explains how to introduce GenAI into reporting workflows.

Analytics platforms like Adobe Analytics are also making steps to better capture attribution from AI tools. In October they released a new referrer type called “Conversational AI Tools” to segment out traffic from ChatGPT and other LLMs from the other channels marketers have historically monitored.

Closing The Gap With Attribution Strategies

So, how do you go from blind spots to better planning? You don’t need perfect clarity. You need consistent signals and a smarter strategy.

Here are some ways marketers are closing attribution gaps:

  1. Clean your first-party data: Data from internal sources like your website and CRM needs to be trustworthy. These are your most important sources of truth.
  2. Use multipliers: Adjust performance based on geo lift or experiment results. Not every click counts equally.
  3. Invite questions: Models are approximations. Encourage teams to challenge them and make improvements as time goes on.
  4. Survey your customers: Ask where they heard about you. It’s old school, but incredibly effective for context.
  5. Use offer codes and landing pages: Even if not perfect, they create new signals across dark social or offline.
  6. Track “AI Referrers”: Create custom =channels in your web analytics, including in GA4, to segment out performance from LLM-driven traffic.

Linking Attribution To Business Outcomes

Attribution and business outcomes go hand-in-hand. Understanding where your most profitable leads originate is essential to growing any business, regardless of its size.

A graphic explaining savings attributed to fixing attribution.

You want to connect your data to actual decisions, such as forecasts, budgets, and resource allocation. But, with the marketing landscape changing so quickly and drastically, how do you know which metrics to follow?

Here are the metrics that matter now:

  • Total conversions and incremental conversions
  • Conversion value over time
  • Cost per incremental conversion
  • Spend thresholds by tactic
  • Directional change (old model vs. new)

Remember: even if your models aren’t perfect, if they get you closer to optimal spend, it’s working. Continuous improvement for your attribution strategy will get you closer and closer still.

A graphic explaining the value of continuous improvement for marketing attribution.

FAQs

What is a marketing attribution blind spot?

It’s any part of the customer journey you can’t track, like dark social shares, offline sales, or LLM referrals that may be influencing conversions without showing up in your data.

Can AI help with attribution?

Yes, but only if used smartly. AI can simulate behavior and identify patterns, but it’s not a silver bullet. Use it to complement your experiments and first-party data.

What’s the best attribution model?

There isn’t one. The most effective models mix touch-based data with testing and contextual clues. Choose based on your business size, channel mix, and data maturity.

Conclusion

When it comes to effective attribution, you just need to see enough to move forward.

Mastering this skill in the modern marketing world is less about getting the credit right and more about making smarter calls with what you can measure. The key is to stop chasing perfection and start building a system that helps you plan and adapt to the data you gather from your testing in real-time. Attribution isn’t the whole picture, but it remains the best tool we have to illuminate the path forward, including its blind spots.

Naturally, we can still learn from tried and true marketing methods. We may just have to think outside the box on how to apply them to today’s search environment and customer journey. It’s worth checking out our guides on which marketing campaigns drive the best impact and how to track your marketing ROI. Combining this extra knowledge with your new attribution perspective could be the secret sauce to put you ahead of the pack in 2026. 

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Small tests to yield big answers on what influences LLMs

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Small Tests – Big Answers – Featured image

Undoubtedly, one of the hot topics in SEO over the last few months has been how to influence LLM answers. Every SEO is trying to come up with strategies. Many have created their own tools using “vibe coding,” where they test their hypotheses and engage in heated debates about what each LLM and Google use to pick their sources.

Some of these debates can get very technical, touching on topics like vector embeddings, passage ranking, retrieval-augmented generation (RAG), and chunking. These theories are great—there’s a lot to learn from them and turn into practice. 

However, if some of these AI concepts are going way over your head, let’s take a step back. I’ll walk you through some recent tests I’ve run to help you gain an understanding of what’s going on in AI search without feeling overwhelmed so you can start optimizing for these new platforms.

Create branded content and check for results

A while ago, I went to Austin, Texas, for a business outing. Before the trip, I wondered if I could “teach” ChatGPT about my upcoming travels. There was no public information about the trip on the web, so it was a completely clean test with no competition.

I asked ChatGPT, “is Gus Pelogia going to Austin soon?” The initial answer was what you’d expect: He doesn’t have any trips planned to Austin.

That same day, a few hours later, I wrote a blog post on my website about my trip to Austin. Six hours after I published the post, ChatGPT’s answer changed: Yes, Gus IS going to Austin to meet his work colleagues.

ChatGPT prompts with a blog post published in between queries, which was enough to change a ChatGPT answer.

ChatGPT used an AI framework called RAG (Retrieval Augmented Generation) to fetch the latest result. Basically, it didn’t have enough knowledge about this information in its training data, so it scanned the web to look for an up-to-date answer.

Interestingly enough, it took a few days until the actual blog post with detailed information was found by ChatGPT. Initially, ChatGPT had found a snippet of the new blog post on my homepage and reindexed the page within the six-hour range. It was using just the blog post’s page title to change its answer before actually “seeing” the whole content days later.

Some learnings from this experiment:

  • New information on webpages reaches ChatGPT answers in a matter of hours, even for small websites. Don’t think your website is too small or insignificant to get noticed by LLMs—they’ll notice when you add new content or refresh existing pages, so it’s important to have an ongoing brand content strategy.
  • The answers in ChatGPT are highly dependent on the content published on your website. This is especially true for new companies where there are limited sources of information. ChatGPT didn’t confirm that I had upcoming travel until it fetched the information from my blog post detailing the trip.
  • Use your webpages to optimize how your brand is portrayed beyond showing up in competitive keywords for search. This is your opportunity to promote a certain USP or brand tagline. For instance, “The Leading AI-Powered Marketing Platform” and “See everyday moments from your close friends” are used, respectively, by Semrush and Instagram on their homepages. While users probably aren’t searching for these keywords, it’s still an opportunity for brand positioning that will resonate with them.

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Test to see if ChatGPT is using Bing or Google’s index

The industry has been ringing alarm bells about whether ChatGPT uses Google’s index instead of Bing. So I ran another small test to find out: I added a <meta name=”googlebot” content=”noindex”> tag on the blog post, allowing only Bingbot for nine days.

If ChatGPT is using Bing’s index, it should find my new page when I prompt about it. Again, this was on a new topic and the prompt specifically asked for an article I wrote, so there wouldn’t be any doubts about what source to show.

The page got indexed by Bing after a couple of days, while Google wasn’t allowed to see it.

New article has been indexed by Bingbot

I kept asking ChatGPT, with multiple prompt variations, if it could find my new article. For nine days, nothing changed—it couldn’t find the article. It got to a point that ChatGPT hallucinated (actually, tried its best guess) a URL.

ChatGPT made-up URL: https://www.guspelogia.com/learnings-from-building-a-new-product-as-an-seo
Real URL: https://www.guspelogia.com/learnings-new-product-seo

GSC shows that it can’t index the page due to “noindex” tag

I eventually gave up and allowed Googlebot to index the page. A few hours later, ChatGPT changed its answer and found the correct URL.

On the top, ChatGPT’s answer when Googlebot was blocked. On the bottom, ChatGPT’s answer after Googlebot was allowed to see the page.

Interestingly enough, the link to the article was presented on my homepage and blog pages, yet ChatGPT couldn’t display it. It only found that the blog post existed based on the text on those pages, even though it didn’t follow the link.

Yet, there’s no harm in setting up your website for success on Bing. They’re one of the search engines that adopted IndexNow, a simple ping that informs search engines that a URL’s content has changed. This implementation allows Bing to reflect updates in their search results quickly. 

While we all suspect (with evidence) that ChatGPT isn’t using Bing’s index, setting up IndexNow is a low effort task that’s worthwhile.

Change the content on a source used by RAG

Clicks are becoming less important. Instead, being mentioned in sources like Google’s AI Mode is arising as a new KPI for marketing teams. SEOs are testing multiple tactics to “convince” LLMs about a topic. From using LinkedIn Pulse to write about a topic, to controlled experiments with expired domains and hacking sites, in some ways, it feels like old-school SEO is back.

We’re all talking about being included in AI search results, but what happens when a company or product loses a mention on a page? Imagine a specific model of earbuds is removed from a “top budget earbuds” list—would the product lose its mention, or would Google find a new source to back up its AI answer? 

While the answer could always be different for each user and each situation, I ran another small test to find out.

In a listicle that mentioned multiple certification courses, I identified one course that was no longer relevant, so I removed mentions of it from multiple pages on the same domain. I did this to keep the content relevant, so measuring the changes in AI Mode was a side effect.

Initially, within the first few days of the course getting removed from the cited URL, it continued to be part of the AI answer for a few pre-determined prompts. Google simply found a new URL in another domain to validate its initial view. 

However, within a week, the course disappeared from AI Mode and ChatGPT completely. Basically, even though Google found another URL validating the course listing, because the “original source” (in this case, the listicle) was updated to remove the course, Google (and, by extension, ChatGPT) subsequently updated its results as well.  

This experiment suggests that changing the content on the source cited by LLMs can impact the AI results. But take this conclusion with a pinch of salt, as it was a small test with a highly targeted query. I specifically had a prompt combining “domain + courses” so the answer would come from one domain.

Nonetheless, while in the real world it’s unlikely one citation URL would hold all the power, I’d hypothesize that losing a mention on a few high-authority pages would have the side effect of losing the mention in an AI answer.

Test small, then scale

Tests in small and controlled environments are important for learning and give confidence that your optimization has an effect. Like everything else I do in SEO, I start with an MVP (Minimum Viable Product), learn along the way, and once/if evidence is found, make changes at scale.

Do you want to change the perception of a product on ChatGPT? You won’t get dozens of cited sources to talk about you straight away, so you’d have to reach out to each single source and request a mention. You’ll quickly learn how hard it is to convince these sources to update their content and whether AI optimization becomes a pay-to-play game or if it can be done organically.

Perhaps you’re a source that’s mentioned often when people search for a product, like earbuds. Run your MVPs to understand how much changing your content influences AI answers before you claim your influence at scale, as the changes you make could backfire. For example, what if you stop being a source for a topic due to removing certain claims from your pages?

There’s no set time for these tests to show results. As a general rule, SEOs say results take a few months to appear. In the first test on this article, it took just a few hours to see results. 

Running LLM tests with larger websites

Working in large teams or on large websites can be a challenge when doing LLM testing. My suggestion is to create specific initiatives and inform all stakeholders about changes to avoid confusion later, as they might question why these changes are happening.

One simple but effective test done by SEER Interactive was to update their footer tagline.

  • From: Remote-first, Philadelphia-founded
  • To: 130+ Enterprise Clients, 97% Retention Rate 

By changing the footer, ChatGPT 5 started mentioning its new tagline within 36 hours for a prompt like “tell me about Seer Interactive.” I’ve checked, and while every time the answer is different, they still mention the “97% retention rate.”

Imagine if you decide to change the content on a number of pages, but someone else has an optimization plan for those same pages. Always run just one test per page, as results will become less reliable if you have multiple variables.

Make sure to research your prompts, have a tracking methodology, and spread the learnings across the company, beyond your SEO counterparts. Everyone is interested in AI right now, all the way up to C-levels.

Another suggestion is to use a tool like Semrush’s AI SEO toolkit to see the key sentiment drivers about a brand. Start with the listed “Areas for Improvement”—this should give you plenty of ideas for tests beyond “SEO Reason,” as it reflects how the brand is perceived beyond organic results.

Checklist: Getting started with LLM optimization

Things are changing fast with AI, and it’s certainly challenging to keep up to date. There’s an overload of content right now, a multitude of claims, and, I dare to say, not even the LLM platforms running them have things fully figured out.

My recommendation is to find the sources you trust (industry news, events, professionals) and run your own tests using the knowledge you have. The results you find for your brands and clients are always more valuable than what others are saying.

It’s a new world of SEO and everyone is trying to figure out what works for them. The best way to follow the curve (or stay ahead of it) is to keep optimizing and documenting your changes.

To wrap it up, here’s a checklist for your LLM optimization:

  • Before starting a test, make sure your selected prompts consistently return the answer you expect (such as not mentioning your brand or a feature of your product). Otherwise, the new brand mention or link could be a coincidence, not a result of your work.
  • If the same claim is made on multiple pages on your website, update them across the board to increase chances of success
  • Use your own website and external sources (e.g., via digital PR) to influence your brand perception. It’s unclear if users will cross-check AI answers or just trust what they’re told.

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From slow to super fast: how to boost site speed the right way

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Did you know that even a one-second delay in page loading speed can cause up to 11% fewer page views? That’s right, you might have the best content strategy and a solid plan to drive traffic, but visitors won’t stay long if your site lags. Page speed is one of the biggest factors in keeping users engaged and converting.

In this guide, we’ll uncover the most common causes of slow websites and explore proven ways to boost website performance. Whether your site feels sluggish or you simply want to make it faster, these insights will help you identify what’s holding it back and how to fix it.

Key takeaways

  • Page speed significantly affects user experience and conversion rates, with even minor delays leading to increased bounce rates
  • Improving website performance involves optimizing hosting, reducing file sizes, and enhancing code quality
  • Fast-loading sites rank better on Google, as page speed is a critical ranking factor, especially for mobile searches
  • Key metrics to monitor include Largest Contentful Paint, Interaction to Next Paint, and Cumulative Layout Shift
  • Use tools like Google PageSpeed Insights and WebPageTest to measure and diagnose performance issues effectively

Table of contents

What do we mean by ‘website performance’ and why is it important for you?

Website performance is all about how efficiently your site loads and responds when someone visits it. It’s not just about how fast a page appears; it’s about how smoothly users can interact with your content across devices, browsers, and locations. In simple terms, it’s the overall quality of your site’s experience that should feel fast, responsive, and effortless to use.

When your page loading speed is optimized, you’re not only improving the user experience but also setting the foundation for long-term website performance.

Here’s why it matters for every website owner:

Fast-loading sites have higher conversion rates and lower bounce rates

Attention spans are notoriously short. As the internet gets faster, they’re getting shorter still. Numerous studies have found a clear link between the time it takes a page to load and the percentage of visitors who become impatient while waiting.

By offering a fast site, you encourage your visitors to stay longer. Not to mention, you’re helping them complete their checkout journey more quickly. That helps improve your conversion rate and build trust and brand loyalty. Think of all the times you’ve been cursing the screen because you had to wait for a page to load or were running in circles because the user experience was atrocious. It happens so often, don’t be that site.

A fast page improves user experience

Google understands that the time it takes for a page to load is vital to the overall user experience. Waiting for content to appear, the inability to interact with a page, and even noticing delays create friction.

That friction costs time, money, and your visitor’s experience. Research shows that the level of stress from waiting for slow mobile results can be more stressful than watching a horror movie. Surely not, you say? That’s what the fine folks at Ericsson Research found a few years back.

Ericsson Mobility Report MWC Edition, February 2016

Improving your site speed across the board means making people happy. They’ll enjoy using your site, make more purchases, and return more frequently. This means that Google will view your site as a great search result because you are delivering high-quality content. Eventually, you might get a nice ranking boost.

Frustration hurts your users and hurts your rankings

It’s not just Google – research from every corner of the web on all aspects of consumer behavior shows that speed has a significant impact on outcomes.

  • Nearly 70% of consumers say that page speed impacts their willingness to buy (unbounce)
  • 20% of users abandon their cart if the transaction process is too slow (radware.com)
  • The BBC found that they lost an additional 10% of users for every additional second their site took to load

These costs and site abandonment happen because users dislike being frustrated. Poor experiences lead them to leave, visit other websites, and switch to competitors. Google easily tracks these behaviors (through bounces back to search engine results pages, short visits, and other signals) and is a strong indicator that the page shouldn’t be ranking where it is.

Google needs fast sites

Speed isn’t only good for users – it’s good for Google, too. Slow websites are often inefficient. They may load too many large files, haven’t optimized their media, or fail to utilize modern technologies to serve their page. That means that Google has to consume more bandwidth, allocate more resources, and spend more money.

Across the whole web, every millisecond they can save, and every byte they don’t have to process, adds up quickly. And quite often, simple changes to configuration, processes, or code can make websites much faster with no drawbacks. That may be why Google is so vocal about its education on performance.

A faster web is better for users and significantly reduces Google’s operating costs. Either way, that means that they’re going to continue rewarding fast(er) sites.

Improving page speed helps to improve crawling for search engines

Modern sites are incredibly wieldy, and untangling that mess can make a big difference. The larger your site is, the greater the impact page speed optimizations will have. That not only impacts user experience and conversion rates but also affects crawl budget and crawl rate.

When a Googlebot comes around and crawls your webpage, it crawls the HTML file. Any resources referenced in the file, like images, CSS, and JavaScript, will be fetched separately. The more files you have and the heavier they are, the longer it will take for the Googlebot to go through them.

On the flip side, the more time Google spends on crawling a page and its files, the less time and resources Google has to dedicate to other pages. That means Google may miss out on other important pages and content on your site.

Optimizing your website and content for speed will provide a good user experience for your visitors and help Googlebots better crawl your site. They can come around more often and accomplish more.

Page speed is a ranking factor

Google has repeatedly said that a fast site helps you rank better. It’s no surprise, then, that Google has been measuring the speed of your site and using that information in its ranking algorithms since 2010.

In 2018, Google launched the so-called ‘Speed Update,’ making page speed a ranking factor for mobile searches. Google emphasized that it would only affect the slowest sites and that fast sites would not receive a boost; however, they are evaluating website performance across the board.

In 2021, Google announced the page experience algorithm update, demonstrating that page speed and user experience are intertwined. Core Web Vitals clearly state that speed is an essential ranking factor. The update also gave site owners metrics and standards to work with.

Of course, Google still wants to serve searchers the most relevant information, even if the page experience is somewhat lacking. Creating high-quality content remains the most effective way to achieve a high ranking. However, Google also states that page experience signals become more important when many pages with relevant content compete for visibility in the search results.

Google mobile-first index

Another significant factor in page speed for ranking is Google’s mobile-first approach to indexing content. That means Google uses the mobile version of your pages for indexing and ranking. This approach makes sense as we increasingly rely on mobile devices to access the internet. In recent research, Semrush found out that 66% of all website visits come from mobile devices.

To compete for a spot in the search results, your mobile page needs to meet Core Web Vitals standards and other page experience signals. And this is not easy at all. Pages on mobile take longer to load compared to their desktop counterparts, while attention span stays the same. People might be more patient on mobile devices, but not significantly so.

Take a look at some statistics:

  • The average website loading time is 2.5 seconds on desktop and 8.6 seconds on mobile, based on an analysis of the top 100 web pages worldwide (tooltester)
  • The average mobile web page takes 15.3 seconds to load (thinkwithgoogle)
  • On average, webpages on mobile take 70.9% longer to load than on desktop (tooltester)
  • A loading speed of 10 seconds increases the probability of a mobile site visitor bouncing by 123% compared to a one-second loading speed (thinkwithgoogle)

All the more reasons to optimize your website and content if your goal is to win a spot in the SERP.

Understanding the web page loading process

When you click a link or type a URL and press Enter, your browser initiates a series of steps to load the web page. It might seem like magic, but behind the scenes, there’s a lot happening in just a few seconds. Understanding this process can help you see what affects your page loading speed and what you can do to boost website performance.

The “one second timeline” from Google’s site speed documentation

The process of loading a page can be divided into three key stages:

Network stage

This is where the connection begins. When someone visits your site, their browser looks up your domain name and connects to your server. This process, known as DNS lookup and TCP connection, enables data to travel between your website and the visitor’s device.

You don’t have much direct control over this stage, but technologies like content delivery networks (CDNs) and smart routing can make a big difference, especially if you serve visitors from around the world. For local websites, optimizing your hosting setup can still help improve overall page loading speed.

Server response stage

Once the connection is established, the visitor’s browser sends a request to your server asking for the web page and its content. This is when your server processes that request and sends back the necessary files.

The quality of your hosting, server configuration, and even your website’s theme or plugins all influence how quickly your server responds. A slow response is one of the most common issues with slow websites, so investing in a solid hosting environment is crucial if you want to boost your website’s performance.

One popular choice is Bluehost, which offers reliable infrastructure, SSD storage, and built-in CDN support, making it a go-to hosting solution for many website owners.

Browser rendering stage

Now it’s time for the browser to put everything together. It retrieves data from your server and begins displaying it by loading images, processing CSS and JavaScript, and rendering all visible elements.

Browsers typically load content in order, starting with what’s visible at the top (above the fold) and then proceeding down the page. That’s why optimizing the content at the top helps users interact with your site sooner. Even if the entire page isn’t fully loaded yet, a quick initial render can make it feel fast and keep users engaged.

Key causes that are causing your website to slow down

While you can’t control the quality of your visitors’ internet connection, most slow website issues come from within your own setup. Let’s examine the key areas that may be hindering your site’s performance and explore how to address them to enhance your website’s performance.

Your hosting service

Your hosting plays a big role in your website’s performance because it’s where your site lives. The speed and stability of your host determine how quickly your site responds to visitors. Factors such as server configuration, uptime, and infrastructure all impact this performance.

Choosing a reliable host eliminates one major factor that affects speed optimization. Bluehost, for example, offers robust servers, reliable uptime, and built-in performance tools, making it a go-to hosting choice for anyone serious about speed and stability.

Your website theme

Themes define how your website looks and feels, but they also impact its loading speed. Some themes are designed with clean, lightweight code that’s optimized for performance, while others are heavy with animations and complex design elements. To boost website performance, opt for a theme that prioritizes simplicity, efficiency, and clean coding.

Large file size

From your HTML and CSS files to heavy JavaScript, large file sizes can slow down your website. Modern websites often rely heavily on JavaScript for dynamic effects, but overusing it can cause your pages to load slowly, especially on mobile devices. Reducing file sizes, compressing assets, and minimizing unnecessary scripts can significantly improve the perceived speed of your pages.

Badly written code

Poorly optimized code can cause a range of issues, from JavaScript errors to broken layouts. Messy or redundant code makes it harder for browsers to load your site efficiently. Cleaning up your code and ensuring it’s well-structured helps improve both performance and maintainability.

Images and videos

Unoptimized images and large video files are among the biggest causes of slow websites. Heavy media files increase your page weight, which directly impacts loading times. If your header image or hero banner is too large, it can delay the appearance of the main content. Optimizing your media files through compression, resizing, and Image SEO can dramatically improve your website’s speed.

Too many plugins and widgets

Plugins are what make WordPress so flexible, but adding too many can slow down your site. Each plugin adds extra code that your browser needs to process. Unused or outdated plugins can also conflict with your theme or other extensions, further reducing performance. Audit your plugins regularly and only keep the ones that truly add value.

Absence of a CDN

A content delivery network (CDN) helps your website load faster for users worldwide. It stores copies of your site’s static content, such as images and CSS files, across multiple servers located in different regions. This means that users access your site from the nearest available server, reducing loading time. If your audience is global, using a CDN is one of the easiest ways to boost website performance.

Redirects

Redirects are useful for managing URLs and maintaining SEO, but too many can slow down your site. Each redirect adds an extra step before reaching the final page. While a few redirects won’t hurt, long redirect chains can significantly affect performance. Whenever possible, try to link directly to the final URL to maintain consistent page loading speed.

For WordPress users, the redirect manager feature in Yoast SEO Premium makes handling URL changes effortless and performance-friendly. You can pick from redirect types such as 301, 302, 307, 410, and 451 right from the dashboard. Since server-side redirects tend to load faster than PHP-based ones, Yoast lets you choose the type your stack supports, allowing you to avoid slow website causes and boost website performance.

A smarter analysis in Yoast SEO Premium

Yoast SEO Premium has a smart content analysis that helps you take your content to the next level!

Get Yoast SEO Premium Only $118.80 / year (ex VAT)

How to measure page speed and diagnose performance issues

Before you can improve your website performance, you need to know how well (or poorly) your pages are performing. Measuring your page speed helps you identify what’s slowing down your website and provides a direction for optimization.

What is page speed, really?

Page speed refers to how quickly your website’s content loads and becomes usable. But it’s not as simple as saying, ‘My website loads in 4 seconds.’ Think of it as how fast a visitor can start interacting with your site.

A page might appear to load quickly, but still feel slow if buttons, videos, or images take time to respond. That’s why website performance isn’t defined by one single metric — it’s about the overall user experience.

Did you know?

There is a difference between page speed and site speed. Page speed measures how fast a single page loads, while site speed reflects your website’s overall performance. Since every page behaves differently, measuring site speed is a more challenging task. Simply put, if most pages on your website perform well in terms of Core Web Vitals, it is considered fast.

Core metrics that define website performance

Core Web Vitals are Google’s standard for evaluating how real users experience your website. These metrics focus on the three most important aspects of page experience: loading performance, interactivity, and visual stability. Improving them helps both your search visibility and your user satisfaction.

  • Largest Contentful Paint (LCP): Measures how long it takes for the main content on your page to load. Aim for LCP within 2.5 seconds for a smooth loading experience
  • Interaction to Next Paint (INP): Replaces the older First Input Delay metric and measures how quickly your site responds to user interactions like taps, clicks, or key presses. An INP score under 200 milliseconds ensures your site feels responsive and intuitive
  • Cumulative Layout Shift (CLS): Tracks how stable your content remains while loading. Elements shifting on screen can frustrate users, so keep CLS below 0.1 for a stable visual experience

How to interpret and improve your scores

Perfection is not the target. Progress and user comfort are what count. If you notice issues in your Core Web Vitals report, here are some practical steps:

  • If your LCP is slow: Compress images, serve modern formats like WebP, use lazy loading, or upgrade hosting to reduce load times
  • If your INP score is high: Reduce heavy JavaScript execution, minimize unused scripts, and avoid main thread blocking
  • If your CLS score is poor: Set defined width and height for images, videos, and ad containers so the layout does not jump around while loading
  • If your TTFB is high: Time to First Byte is not a Core Web Vital, but it still impacts loading speed. Improve server performance, use caching, and consider a CDN

Remember that even small improvements create a noticeable difference. Faster load times, stable layouts, and quicker interactions directly contribute to a smoother experience that users appreciate and search engines reward.

Tools to measure and analyze your website’s performance

Here are some powerful tools that help you measure, analyze, and improve your page loading speed:

Google PageSpeed Insights

Google PageSpeed Insights is a free tool from Google that provides both lab data (simulated results) and field data (real-world user experiences). It evaluates your page’s Core Web Vitals, highlights problem areas, and even offers suggestions under ‘Opportunities’ to improve load times.

Google Search Console (Page Experience Report)

The ‘Page Experience’ section gives you an overview of how your URLs perform for both mobile and desktop users. It groups URLs that fail Core Web Vitals, helping you identify whether you need to improve LCP, FID, or CLS scores.

Lighthouse (in Chrome DevTools)

Lighthouse is a built-in auditing tool in Chrome that measures page speed, accessibility, SEO, and best practices. It’s great for developers who want deeper insights into what’s affecting site performance.

WebPageTest

WebPage Test lets you test how your website performs across various networks, locations, and devices. Its ‘waterfall’ view shows exactly when each asset on your site loads, perfect for spotting slow resources or scripts that delay rendering.

Chrome Developer Tools (Network tab)

If you’re hands-on, Chrome DevTools is your real-time lab. Open your site, press F12, and monitor how each resource loads. It’s perfect for debugging and understanding what’s happening behind the scenes.

A quick checklist for diagnosing performance issues

Use this checklist whenever you’re analyzing your website performance:

  • Run your URL through PageSpeed Insights for Core Web Vitals data
  • Check your Page Experience report in Google Search Console
  • Use Lighthouse for a detailed technical audit
  • Review your WebPageTest waterfall to spot bottlenecks
  • Monitor your server performance (ask your host or use plugins like Query Monitor)
  • Re-test after every major update or plugin installation

Speed up, but with purpose

As Mahatma Gandhi once said, ‘There is more to life than increasing its speed.’ The same goes for your website. While optimizing speed is vital for better engagement, search rankings, and conversions, it is equally important to focus on creating an experience that feels effortless and meaningful to your visitors. A truly high-performing website strikes a balance between speed, usability, accessibility, and user intent.

When your pages load quickly, your content reads clearly, and your navigation feels intuitive, you create more than just a fast site; you create a space where visitors want to stay, explore, and connect.

The post From slow to super fast: how to boost site speed the right way appeared first on Yoast.

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6 Best Ad Intelligence Software to Outsmart the Competition

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Ad intelligence software promises to show you everything your competitors are doing: their keywords, budgets, creatives, and landing pages.

But many surface insights you could get for free.

Meta’s Ad Library shows what advertisers are currently running. Google’s Transparency Center does the same for search and YouTube. TikTok’s Creative Center reveals top performers by industry.

So, when does paid software earn its cost?

  • You’re tracking multiple competitors across platforms and losing hours to manual checks
  • You need historical data on which ads they tested and killed
  • You rely on spend benchmarks and real-time alerts to catch shifts before your clients do

That’s the gap paid tools fill. If they’re good.

Many aren’t. They bury useful insights under dashboards that create more work than they save. The data looks complete until you actually try to use it.

This guide covers six platforms that deliver real intelligence (if you know what you’re looking at).

We’re not promising magic improvements. We’re showing what each tool reveals, who it’s built for, and what you give up at each price point.

What Is the Best Ad Intelligence Software?

Ad Intelligence Tools Best For Price
Similarweb Best for stalking competitors’ ads at scale — plus, their SEO, traffic, and market moves $649+/month. (Only higher-tier plans come with ad intelligence.)
Semrush Advertising Toolkit Best for multi-platform ad intelligence, from Meta and TikTok to Google Shopping $99-$220/month
SpyFu Best for affordable Google Ads intelligence with deep historical data $39-$249/month
PowerAdSpy Best for analyzing ad engagement across social media platforms $69-$399/month
Adbeat Best for tracking competitor display ads and landing pages $249+/month
Pathmatics Best for enterprise-level ad spend intelligence across mobile, social, and video Pricing is not publicly available

1. Similarweb

Best for stalking competitors’ ads at scale — plus, their SEO, traffic, and market moves

Similarweb – Homepage

Similarweb reveals your competitors’ complete paid strategies, from their winning ad creatives to their most successful publishers.

It also includes SEO and competitive intelligence tools in every subscription, so you get the full picture of how your rivals attract and convert traffic across every channel.

This cross-channel context is especially helpful if you already use native ad libraries but want scalable intel that ties everything together.

Learn Your Competitors’ Highest-Performing Publishers and Ad Networks

If your competitors are running ads, Similarweb shows you where (and how to beat them).

You’ll see:

  • Which ad networks and placements work best for your top competitors
  • Where their ad budgets go, broken down by channel
  • Industry-wide trends that reveal missed opportunities

Similarweb – The Spruce – Website Intelligence

Say Similarweb shows that multiple competitors spend over 50% of their display budgets on a single publisher.

That’s a data-backed signal you can’t ignore.

Use that data to target the same publisher to test similar placements. Or find underused publishers in the same category for more affordable traffic.

Similarweb – Huffpost – Publisher Performance

Get Inspired by Proven Ad Creatives

Similarweb’s database makes it easy to browse display ads by publisher, network, and format.

  • See the messaging and offers competitors use to get conversions
  • Learn how many days each ad was active, so you know which ones excelled (and which ones failed)
  • Find out which formats your competitors are using, including product, display, and video ads

Similarweb – Creatives

Of course, copying your competitors’ ads word-for-word isn’t the goal.

The real value is in spotting patterns: the hooks they repeat, the formats they invest in, and the offers they continually test.

These insights let you design campaigns that build on what already works in your market.

When you’re juggling multiple accounts, this saves hours of creative testing, and points you directly toward proven formats.

Reverse-Engineer Competitors’ Search and Shopping Campaigns

Similarweb shows you which keywords your competitors bid on and how much they’re spending.

This helps you identify high-value keywords that drive conversions and avoid wasting budget on terms that don’t perform.

Similarweb – Paid Keywords

From there, you can build stronger landing pages that target your competitors’ most successful keywords and match intent.

Pros and Cons

Pros Cons
Tracks 500M+ ads across publishers, networks, and formats for deep competitive insights Ad intelligence tools only available with the most expensive plan
Uncovers competitors’ top-performing publishers and ad placements Can feel overwhelming for smaller teams due to the platform’s depth
Includes SEO, traffic, and market data for a full competitive picture If you only want ad intelligence, you’ll be paying for much more than you need

Pricing

Similarweb – Pricing

Similarweb offers multiple plans, but only the most expensive one includes dedicated tools for ad intelligence.

This plan costs $649/month ($540 billed annually). Similarweb also offers business and enterprise plans, but pricing and tools are not publicly available online.

Further reading: How to Use Similarweb for SEO and Content Marketing

2. Semrush Advertising Toolkit

Best for multi-platform ad intelligence, from Meta and TikTok to Google Shopping

Semrush – Advertising Research – Ebay – Positions

When you’re managing multiple clients or campaigns, switching between Meta, TikTok, and Google dashboards gets messy fast.

Semrush’s Advertising Toolkit consolidates that chaos into one workspace — letting you analyze competitor campaigns and build your own in the same place.

You’ll get deep intel on keywords, budgets, ad copy, and creative trends.

Plus, actionable advice on how to turn that data into high-performing campaigns.

Track Competitor Keywords and Budgets

The Advertising Research tool reveals everything, and we mean everything, about your competitors’ Google Ads strategies.

Enter any domain and you’ll see:

  • Estimated ad traffic
  • Cost per click (CPC)
  • Highest- and lowest-performing keywords
  • Organic search position
  • Keyword difficulty
  • URL

No more wasting ad budget on terms that don’t perform. You’ll know exactly which ones to target in your next campaign.

Semrush – Advertising Research – Ebay – Position Changes

The tool also tracks keyword trends over time.

See which keywords competitors continuously invest in month after month.

When a keyword consistently appears in their paid strategy with stable or growing volume, that’s a clear sign it’s profitable.

Semrush – Advertising Research – Ebay – Paid Search Trends – Keywords

With this data, you might test variations of the keyword in multiple ads to capitalize on its success.

Or use them to inform your broader content strategy beyond paid campaigns.

Spy on Google Shopping Ads

Have an ecommerce brand?

The PLA Research tool shows you which products your competitors promote most heavily in Google Shopping.

You’ll see position, volume, price, product titles, URLs, and trend data for each listing.

When a product shows up month after month, it’s likely a top seller.

Semrush – PLA Research – Ebay – PLA Positions

If you don’t carry that product yet, you might consider adding it to your catalog.

Already sell it? Increase your Shopping ads to compete directly.

You can also view all of your competitors’ Google Shopping ads in one place.

Semrush – PLA Research – Ebay – PLA Copies

Analyze their copy, images, and offers.

Then, apply these insights to your own listings:

  • Adjust your product titles to match high-performing formats
  • Test pricing strategies that undercut or match theirs
  • Prioritize ads for products where you have a competitive advantage. Think better reviews, faster shipping, or exclusive features they don’t offer.

Here’s another cool feature:

Instead of bouncing between tools, Semrush’s AI-powered Ad Launch Assistant lets you create and optimize Google and Meta ads directly inside the platform.

Semrush's AI powered Ad launch assistant

The tool generates copy and visuals tailored to your brand, from attention-grabbing headlines to conversion-focused descriptions.

Instead of writing everything from scratch, all you have to do is review each element:

  • Headlines
  • Descriptions
  • Site links
  • Callouts
  • Images
  • Videos

Simply refine the voice and messaging as needed. You’ll be able to test multiple variations in minutes instead of hours.

Unlock Deeper Insights with AdClarity

AdClarity is Semrush’s advanced cross-channel ad intelligence tool.

Need complete visibility into competitor display, social, and video campaigns?

This is where you’ll find it.

Semrush – AdClarity

You’ll get a lot of data with this tool.

Including how much rivals spend, which publishers drive the most impact, and the exact creatives they’re using across platforms:

  • Facebook
  • Instagram
  • X
  • Google Display
  • Pinterest
  • YouTube
  • TikTok
  • LinkedIn

Say a competitor suddenly doubles their TikTok spend. You’ll spot the shift immediately and can adjust your strategy in real time.

Semrush – AdClarity – Advertising Intelligence

AdClarity also automatically identifies your competitors’ top publishers and campaigns.

So there’s no guessing or testing which ones work well for your target audience.

Semrush – AdClarity – Top Publishers

Pros and Cons

Pros Cons
Combines robust multi-site ad intelligence with Meta and Google campaign execution in one platform The base plan includes only Google and Meta ad intelligence
Google Shopping insights are especially strong for ecommerce brands AdClarity is only included the higher-tier plan
AdClarity offers advanced ad intelligence across display, social, and video Doesn’t include SEO tools; you’ll need a separate toolkit for that

Pricing

Semrush – Advertising Toolkit – Pricing

The Semrush Advertising Toolkit is $99 per month.

It includes Advertising Research, PLA Research, Ads Launch Assistant, and more.

The higher-tier plan ($220/month) includes AdClarity, along with all of the above.

3. SpyFu

Best for affordable Google Ads intelligence with deep historical data

SpyFu – Homepage

SpyFu is built for one thing: uncovering Google Ads strategies.

If your strategy leans heavily on Google, it’s one of the most detailed and budget-friendly advertising intelligence software options available.

Download Competitor Keywords Without Limits

SpyFu shows you everything your competitors do on Google Ads — and lets you export it all with no limits.

Many ad intelligence platforms cap your keyword downloads, so this is a plus.

Type in any competitor’s domain and you’ll see:

  • Every keyword they’ve ever bought on Google Ads
  • Estimated monthly clicks and CPC
  • Total spend on paid search

SpyFu – Monthly PPC Overview

For example, say you’re in SaaS project management and Asana is your top competitor.

Search their domain, and SpyFu shows you their current and historical ad keywords. We’re talking thousands of terms, not just the top 50 or 100.

Download the complete dataset and…

  • Feed it into your analytics tools or Google Sheets
  • Share it with your team for campaign planning
  • Build custom reports for leadership
  • Cross-reference it with your CRM to see which keywords actually convert

SpyFu – Asana – Most Successful Paid Keywords

Spot Overlaps and Waste in PPC Strategies

SpyFu’s Kombat tool compares your PPC strategy against up to two competitors at once.

But instead of having to sift through 10,000 keywords, the ad intelligence tool automatically groups them into helpful buckets:

  • Core Keywords: Terms all competitors are bidding on
  • Consider Buying: Valuable keywords they use, but you don’t
  • Potential Ad Waste: Terms that neither competitor uses but you do

SpyFu – Asana – Kombat tool

So, you know exactly which terms to focus on (and which to remove from your campaigns).

This is especially helpful if you’re newer to paid campaigns.

Or have limited time (or tolerance) for turning data into actionable insights.

SpyFu also tags certain terms as “Great Buys” and estimates how many impressions you’ll get for each one.

Plus, it shows which competitors already bid on them, so you can piggyback on proven opportunities.

SpyFu – Asana – PPC Overview

For example, the report below reveals that Asana’s competitor, Monday.com, uses “top task management apps” and “work time tracker app” in its ad strategy.

Asana could (and probably should) target both terms since SpyFu’s data shows they’re worth the investment.

SpyFu – Asana – Top Google Ads Buy Recommendations

Learn From Ads That Worked (or Failed)

SpyFu’s Ad History tool shows every ad variation competitors have tested for a given keyword.

If an ad copy ran for 14 consecutive months, you know it was effective.

If it vanished after a week? Probably a dud.

This kind of insight lets you write ads with fewer flops and faster wins.

This is especially valuable if you handle multiple accounts. You can skip obvious mistakes and start from proven winners.

SpyFu – Asana – Ad History

Pros and Cons

Pros Cons
Unlimited keyword exports with no download caps Focused exclusively on Google Ads; no social or display coverage
10+ years of historical ad data for deep competitive analysis Historical data (10+ years) requires paying for higher-tier plans
Kombat tool automatically identifies keyword overlaps and wasted spend The base plan doesn’t come with unlimited downloads

Pricing

SpyFu – Pricing

SpyFu offers three main plans, all of which come with ad intelligence and SEO reports.

The most affordable plan is $39 per month.

However, you’ll need to upgrade to a higher tier to get 10+ years of historical insights ($59-$249/month).

Further reading: SpyFu Guide: How to Get the Most Out of This SEO Tool

4. PowerAdSpy

Best for analyzing ad engagement across social media platforms

PowerAdSpy – Homepage

PowerAdSpy specializes in social advertising intelligence with one key differentiator: engagement data that shows what’s actually resonating.

You’ll see which competitor social ads are getting likes, shares, and comments across 11 platforms:

  • Facebook
  • Instagram
  • YouTube
  • Google
  • Google Display Network
  • Native
  • Quora
  • Reddit
  • Pinterest
  • LinkedIn
  • TikTok

If you need to understand which creatives are worth replicating at scale, PowerAdSpy is a strong option.

Search Ads by Keyword, Competitor, or Domain

Want to know which competitor ads crush it on Instagram Reels?

Or which offers rivals push hardest on YouTube or TikTok?

Plug in a keyword, competitor’s name, or domain, and you’ll instantly see all of their active and historical campaigns.

That single search can replace hours of platform hopping between ad libraries.

PowerAdSpy – Domain, Advertiser, Keyword – Filter

Reveal What’s Actually Driving Engagement

Every ad includes engagement data specific to the platform you’re analyzing.

Assessing competitors’ or clients’ Facebook ads? Sort by likes, comments, impressions, and popularity.

PowerAdSpy – Likes, Shares – Filter

You can also filter by ad type and call to action, depending on the platform.

This is especially useful for spotting:

  • Whether video or static images dominate your niche
  • Which CTAs (“Learn More” vs. “Sign Up”) consistently get clicks
  • What ad hooks (“Free trial” vs. “Save 50%”) keep resurfacing across competitors

PowerAdSpy – Call to action – Filter

See How Competitors Win Attention on Reddit and Quora

PowerAdSpy tracks sponsored posts on Reddit and Quora.

These platforms matter because buying decisions often start there.

Conversations on these sites can also influence how LLMs (such as ChatGPT and Perplexity) surface your brand in answers.

PowerAdSpy – Ad Spy Tool – Quora

By analyzing these ads, you’ll see:

  • Which threads your competitors target (like “best project management software” on r/productivity)
  • How they position offers in Q&A format
  • Which ads earn upvotes, shares, and comments

PowerAdSpy – Filter with Likes

See what competitors are saying and which conversations are shaping buyer intent.

Spot content angles that consistently earn engagement. Identify threads or audiences they’re overlooking.

Another helpful feature?

Search by topic, like “games,” to find the competitors dominating that ad niche.

PowerAdSpy – Likes sort by filter

Include a custom “like” range so you narrow results to the level of popularity you prefer.

Then, zero in on the highest-performing ads and gather details such as ad copy and social engagement to improve your campaigns.

PowerAdSpy – Reddit ad spy tool

Pros and Cons

Pros Cons
Large, frequently updated database of social ads across 10+ major platforms Mainly focused on social media; lacks advanced search or display ad data
Engagement metrics (likes, shares, comments) reveal which creatives actually resonate Advanced filtering options are locked behind higher plans
Powerful filters for ad type, placement, geography, and CTA performance Only the highest-tier plan includes insights from all 11 platforms

Pricing

PowerAdSpy – Pricing

PowerAdSpy has six different plans.

The one you choose depends on the social platforms you want to analyze, and the features you need.

Only need Facebook, Instagram, Google, and YouTube?

(And don’t mind missing out on features like ad budget, ad type filter, and advanced analytics?)

The most affordable plan ($69/month) might work for you.

Need all the features and platforms? You’ll pay $399 per month.

5. Adbeat

Best for tracking competitor display ads and landing pages

Adbeat – Homepage

Adbeat specializes in display, native, and programmatic advertising.

But it goes beyond ad creatives.

You’ll also see landing page insights, so you get intel on the complete customer journey.

See Which Landing Pages Are Actually Converting

Adbeat shows you which landing pages drive the most ad traffic. And how long each page has been live.

For example, Squarespace’s longest-running landing page has been active for 794 days.

That’s over two years.

Adbeat – Squarespace – Advertiser profile

When a page stays live that long, you know it’s consistently converting.

This intel helps you see which page layouts, offers, and messaging are worth replicating.

If you work for an agency and have multiple clients, this is particularly valuable. It’s a fast way to benchmark what “good” looks like in each vertical.

Reveal Media Buying Strategies and Publisher Insights

The Advertiser Dashboard breaks down where competitors allocate their budgets across channels, networks, and publishers.

You’ll also see share-of-voice data to understand their market presence.

For example, Adbeat found that Squarespace ran 524 ads in one month.

Adbeat – Squarespace – Monthly Ads

And 78% of their spend went to programmatic ads.

Details like this highlight which channels matter most in your niche. And where you can reallocate budget to get better performance for your own campaigns.

Adbeat – Squarespace – Ad Channels breakdown

Benchmark Campaign Performance and Spot Trends

Adbeat’s ad intelligence software lets you monitor how your competitors’ budgets shift over time.

But what’s especially helpful is that they break it down by ad type: standard, native, and video.

For example, Squarespace’s longest-running video ad has been live for 413 days.

Adbeat – Squarespace – Video Ads

If they’ve kept it running that long, it’s a moneymaker.

In other words, it’s worth considering if you’re investing enough in video ads. And studying individual high performers for hooks, visuals, and offers.

Pros and Cons

Pros Cons
Lets you analyze ads and landing pages together for complete funnel insights Limited coverage of search and social campaigns
Reveals media spend, publisher performance, and traffic sources Pricing is higher than ad-creative-only tools
Great for agencies, affiliate marketers, and display-heavy advertisers Enterprise pricing is not publicly available

Pricing

Adbeat – Pricing

Adbeat’s pricing starts at $249 per month for display, programmatic, and native ad intelligence.

For advanced filters, alerts, and historical data, you’ll need the higher plan ($399 per month).

There’s also an enterprise plan, but pricing isn’t listed publicly.

6. Pathmatics by Sensor Tower

Best for enterprise-level ad spend intelligence across mobile, social, and video

SensorTower – Pathmatics

Pathmatics is built for large teams and big brands.

Household names like P&G and Unilever use this platform, so expect enterprise-level pricing and complexity.

But if you’re managing high-volume spend or reporting to leadership, it offers the transparency and benchmarking you can’t get from native tools.

Uncover Competitors’ Ad Spend Across Every Channel

Pathmatics shows you where every ad dollar goes in a pretty granular way.

It breaks down spend by platform, campaign, or creative — and tracks impressions, reach, and frequency over time.

Pathmatics – Gain Visibility

Say you notice a competitor’s Instagram spend suddenly increased by a significant amount in a single week during Q4.

That signals a major campaign launch — possibly holiday shopping or Black Friday prep.

With this data, you can adjust your strategy immediately. And compete head-to-head with your main competitors.

Pathmatics also lets you benchmark your ad spend against multiple competitors at once.

If you’re investing $500K on display while your top three competitors each spend $2M+, you’ll see that gap.

Pathmatics – Identify seasonal advertising trend

Use this data to justify budget increases to leadership.

Or to identify where smaller reallocations could close the gap faster.

Benchmark Market Share and Share of Voice

Pathmatics tracks your share of voice against competitors in your industry and region.

If three brands dominate 80% of impressions in your category, you’ll see who owns what percentage.

This data helps you understand your position in the market.

Are you a distant fourth? Or neck-and-neck with the leader?

Pathmatics – Benchmark Market Share

You can also identify which competitors dominate specific channels and spot opportunities where they’re underinvesting.

If the market leader owns Facebook but ignores TikTok, that’s your opening.

Evaluate Creatives That Resonate

Every ad includes details like format, placement, messaging, CTAs, and audience profiles.

See which creatives competitors keep running and which ones they kill after a few days.

Track the exact messaging and offers that stick around for months or years.

Pathmatics – Analyze Top Creatives

Use these insights to refine your own creative strategy.

Double down on formats that consistently deliver, and try localized messaging in new markets where your competitors are seeing success.

Pros and Cons

Pros Cons
Provides cross-channel visibility across social, display, mobile, video, and OTT Pricing is custom and can be expensive for smaller teams and startups
Combines creative data with detailed spend, reach, and audience insights Steeper learning curve due to platform depth and data complexity
Ideal for enterprise-level teams, app publishers, and multi-channel marketers Some users report data accuracy issues

Pricing

Pathmatics – Pricing

Pathmatics’ pricing is custom.

Request a quote if you’re interested.

Turn Competitive Intel into Campaign Wins

The right ad intelligence software isn’t the one with the most features.

It’s the one you can trust.

This means reliable data, less manual work, and the ability to scale campaigns across platforms with ease.

On a budget and focused mainly on Google Ads? Start with SpyFu.

Need deep, multi-site advertising intelligence across search and social with campaign execution built in?

Go for Semrush’s Advertising Toolkit.

Once you’ve picked your platform and gathered competitive intel, the next step is making sure your paid and organic strategies work together.

Learn how to align SEO and PPC to maximize visibility, reduce wasted spend, and improve your ROI.

The post 6 Best Ad Intelligence Software to Outsmart the Competition appeared first on Backlinko.

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October 2025 Digital Marketing Roundup: What Changed and What You Should Do About It

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October showed just how fast AI is reshaping how brands connect, convert, and stay visible. OpenAI turned chats into checkout experiences. Google tested AI-written snippets and agent-driven search. The line between platforms, ads, and transactions keeps disappearing.

Creators gained new credibility. Rebrands proved riskier than ever. Data-driven PR entered a new era.

Here’s what mattered most and how to stay ahead.

Key Takeaways

  • • AI is officially a channel, not a tool. Search, shopping, and PR are all happening inside AI environments now.
  • • Authenticity outperforms aspiration. Whether you’re selling luxury goods or refreshing your brand, identity, and connection drive growth.
  • • Visibility depends on AI citations and structure. The brands getting mentioned in AI results are building more trust and traffic everywhere.
  • • Automation is powerful, but it still needs control. As Google’s AI Max expands, you need to balance efficiency with oversight to protect budgets and brand safety.
  • • Every brand action is a public statement. From rebrands to creator partnerships, perception moves fast. Plan your narratives or risk losing control of them.

Search & AI Evolution 

Search has moved beyond discovery. October’s updates from OpenAI and Google show how AI is collapsing the gap between queries and actions. Visibility means something different now.

OpenAI launches in-chat purchases

OpenAI rolled out Instant Checkout in ChatGPT. U.S. users can now buy products directly inside the chat. Powered by Stripe, the feature starts with Etsy listings and will expand to more merchants soon. Sellers on Shopify are auto-enrolled. Others can join by connecting product feeds and enabling Stripe checkout.

An ad in ChatGPT.

Our POV: ChatGPT shopping changes product discovery completely. If your product data isn’t complete, detailed, and conversational, you won’t show up. The most visible listings will have rich attributes and language that reflects how users naturally describe what they want.

What to do next: Audit your product feeds. Fill every field. Use detailed, long-form descriptions that anticipate real-world queries. Give the e-commerce agent what it needs to surface your products.

<h3> Google tests AI-written meta descriptions <h3>

Google began testing AI-generated snippets powered by Gemini. Instead of pulling your written meta description, the model writes or summarizes one based on on-page content.

Our POV: Google’s been rewriting descriptions for years. AI just made it smarter and less predictable. Treat your page intros as the new meta description because that’s what AI will pull from.

What to do next: Front-load the first 150 words of each key page with a clear summary of what the page delivers and why it matters. Tighten headings and intros, monitor CTR shifts, and adjust language when AI summaries drift from your brand’s tone.

<h3> Google Search Labs adds Agentic AI <h3>

Google’s AI Mode now lets users book restaurants and other services directly from results. Search is moving from recommending to acting.

Our POV: This isn’t a traffic killer. But signals are shifting. AI will handle the click path. The brands that win will have structured, verified, action-ready data.

What to do next: Audit structured data, integrate local feeds, and make sure your listings are up to date across booking platforms. When the search agent starts acting on your behalf, data hygiene becomes your conversion strategy.

Paid Media & Automation

AI is taking over ad delivery. Control is the new currency. You have to balance efficiency with visibility to keep performance from becoming unpredictable.

Google doubles down on AI Max

Google refreshed its AI Max ad pitch. The system is fully automated: it matches intent, rewrites copy, and routes users to brand assets. Powerful, but still a black box.

Google AI Max.

Our POV: Automation doesn’t replace strategy. Advertisers need visibility, not just results. Without strict guardrails, budgets can leak into low-value placements or off-brand creative.

What to do next: Run low-risk tests first. Add negative keyword lists, set URL exclusions, and manually review creative. Monitor performance closely until you can prove control before scaling.

Apple launches dedicated Games app

Apple introduced a standalone Games app with iOS 26, bridging Game Center and the App Store. Developers can now feature their games, run dual search visibility, and analyze engagement with new metrics later this year.

Apple's Games app.

Our POV: This isn’t a small tweak, Apple’s essentially building a second storefront. Game publishers who adapt early will own discoverability.

What to do next: Refresh creatives, optimize In-App Events, and plan for dual indexing between the Games app and App Store. When analytics arrive, use them to refine ASO and campaign timing.

Social & Content Trends

Creators and consumers are rewriting the rules. Authenticity, identity, and emotional connection drive engagement across platforms that once ran on aspiration and polish.

TikTok reframes luxury branding

TikTok’s new research shows luxury audiences care more about self-expression than status. It’s about showing who you are, not showing off.

TikTok's 4 Ls of Luxury concept.

Our POV: That shift goes way beyond luxury. Audiences in every category now expect brands to reflect their identity. Connection beats aspiration. Authenticity beats polish.

What to do next: Reevaluate your brand’s emotional identity. Work with creators who reinterpret your message through their lens. Build content that feels participatory, not performative.

UK YouTubers contribute £2.2B to the economy

YouTube creators generated £2.2 billion for the UK economy last year, supporting over 45,000 jobs. Parliament even launched a cross-party group to represent them.

Our POV: Creators aren’t influencers anymore. They’re small businesses with real economic weight. Partnering with them means investing in industries, not individuals.

What to do next: Build collaborations that help creators grow beyond campaigns. Shared education, joint products, or community-driven initiatives create deeper, longer-term value.

PR, Reputation & Brand Risk

Reputation management has become real-time and AI-measurable. From LLM citation tracking to brand backlash, every communication choice now echoes faster and louder.

Notified + Profound launch AI-driven PR monitoring

A first-of-its-kind industry partnership between these two companies now offers a tool that tracks how often press releases are cited by LLMs like ChatGPT and Gemini. It finally gives brands visibility into their “AI footprint.”

Our POV: PR just gained a measurable seat in AI discoverability. Knowing when AI cites your releases helps you shape future narratives.

What to do next: Integrate AI citation metrics into your analytics stack. Identify which stories get surfaced and refine future language to match the tone that earns citations.

Rebrands are riskier than ever

Cracker Barrel’s attempted rebrand backfired almost instantly. Modest design updates triggered outrage and political backlash—proof that brand refreshes now carry reputational stakes.

Our POV: Rebrands still matter, but they demand foresight. A design tweak is a message, whether you mean it or not.

What to do next: Before launching a new look, test reactions across audience segments and scenario-plan your communication strategy. Shape the story before the internet does.

Olivia Brown automates PR outreach

A new AI platform called Olivia Brown is automating nearly every part of digital PR, from writing press releases to pitching journalists and sending aggressive follow-ups. It promises to “democratize publicity,” but its bulk-send approach is flooding inboxes and straining relationships between brands and reporters who value relevance and trust.

The Olivia Brown interface.

Our POV: Rebrands still matter, but they demand foresight. A design tweak is a message, whether you mean it or not.

What to do next: Before launching a new look, test reactions across audience segments and scenario-plan your communication strategy. Shape the story before the internet does.

SEO 2.0: The New Search Game

Traditional rankings are giving way to AI visibility. The brands that master structure, credibility, and omnichannel authority are the ones AI systems will learn to trust and users will keep choosing.

Rankings + AI Citations

Traditional SEO metrics can’t capture how visible you are inside AI systems. NP Digital’s SEO 2.0 approach tracks AI citations alongside rankings to see how content performs in generative search.

Our POV: Rankings aren’t the endgame anymore. Visibility inside AI summaries is. The brands that get cited are the ones shaping what users read next.

What to do next: Create original, data-backed content that builds authority across multiple platforms: YouTube, Reddit, TikTok, and forums. These are the signals AI models use to decide who to trust.

<America’s favorite new query: “Is it good or bad?”

SEMrush found that U.S. users are now searching in binary terms. Tens of millions of queries every month ask if something is “good” or “bad.”

A graphic showing the main topics behind "Good/Bad" searches from SEMrush.

Source

Our POV: AI Overviews have trained users to expect clear answers. If your content hedges or buries the lead, you’ll lose clicks and credibility.

What to do next: Structure pages for speed and certainty. Use FAQ blocks, schema markup, and straightforward intros that deliver the verdict early. This is how you earn trust in zero-click environments.

Conclusion

AI is rewriting the rules of visibility, discovery, and trust. Success no longer depends on who publishes most. It depends on who provides the clearest data, most credible voice, and strongest structure. The brands investing in AI-ready content, authentic storytelling, and measurable strategy will own the next wave of search, social, and PR.

Need help applying these insights? Talk to the NP Digital team. We’re already helping brands adapt as things develop.

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