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.

Read more at Read More

Web Design and Development San Diego

Introducing the Branded queries filter in Search Console

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We’re happy to announce we’re providing an additional tool to analyze the performance
of your website by query type in the Search Console Performance Report:
the branded queries filter. This new feature is designed to help analyze the queries driving traffic
to your site by automatically differentiating between branded and non-branded queries.

Read more at Read More

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.

Read more at Read More

Google releases Gemini 3 – it already powers AI Mode

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Google announced the release of its latest AI model update, Gemini 3. “And now we’re introducing Gemini 3, our most intelligent model, that combines all of Gemini’s capabilities together so you can bring any idea to life,” Google’s CEO, Sundar Pichai wrote.

Gemini 3 is now being used in AI Mode in Search with more complex reasoning and new dynamic experiences. “This is the first time we are shipping Gemini in Search on day one,” Sundar Pichai said.

AI Mode with Gemini 3. Google shared how AI Mode in Search is now using Gemini 3 to enable new generative UI experiences like immersive visual layouts and interactive tools and simulations, all generated completely on the fly based on your query.

Here is a video of showing how RNA polymerase works with generative UI in AI Mode in Search.

Robby Stein, VP of Product at Google Search said:

“In Search, Gemini 3 with generative layouts will make it easy to get a rich understanding of anything on your mind. It has state-of-the-art reasoning, deep multimodal understanding and advanced agentic capabilities. That allows the model to shine when you ask it to explain advanced concepts or ideas – it reasons and can code interactive visuals in real-time. It can tackle your toughest questions like advanced science.”

More Gemini 3. Google added that Gemini 3 has:

  • State-of-the-art reasoning
  • Deep multimodal understanding
  • Powerful vibe coding so you can go from prompt to app in one shot
  • Improved agentic capabilities, so it can get things done on your behalf, at your direction

Availability. Gemini 3 is now rolling out, yes, in AI Mode but here also:

  • For everyone in the Gemini app and for Google AI Pro and Ultra subscribers in AI Mode in Search
  • For developers in the Gemini API in AI Studio, our new agentic development platform, Google Antigravity; and Gemini CLI
  • For enterprises in Vertex AI and Gemini Enterprise

Why we care. Gemini 3 is currently powering AI Mode, the future of Google Search. It will continue to power more and more search features within Google, as well as other areas within Google’s platforms.

Being on top of these changes and how they impact search and your site and maybe Google Ads is important.

Read more at Read More

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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The three AI research modes redefining search – and why brand wins

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The three AI research modes redefining search — and why brand wins

The AI resume has become a C-suite-level asset that reflects your entire digital strategy. 

To use it effectively, we first need to understand where AI is deploying it across the user journey.

How AI has rewritten the user journey

For years, our strategies were shaped by the inbound methodology.

We built content around a user-driven path through awareness, consideration, and decision, with traditional SEO acting as the engine behind those moments.

That journey has now been fundamentally reshaped. 

AI assistive engines – conversational systems like Gemini, ChatGPT, and Perplexity – are collapsing the funnel. 

They move users from discovery to decision within walled-garden environments. 

It’s what I call the BigTech walled garden AI conversational acquisition funnel.

For marketers, that shift can feel like a loss of control. 

We no longer own the click, the landing page, or the carefully engineered funnel. 

But from the consumer perspective, the change is positive. 

People want one thing: a direct, trusted answer.

This isn’t a contradiction. It’s the new reality. 

Our job is to align with this best-service model by proving to the AI that our brand is the most credible answer.

That requires updating the ultimate goal. 

For commercial queries, the win is no longer visibility. 

It’s earning the perfect click – the moment when an AI system acts as a trusted advisor and chooses your brand as the best solution.

To get there, we have to broaden our focus from explicit branded searches to the three modes of research AI uses today: 

  • Explicit.
  • Implicit.
  • Ambient. 

Together, they define the new strategic landscape and lead to one truth.

In an AI-driven ecosystem, brand is what matters most.

3 types of research redefining what search is

These three behaviors reveal how users now discover, assess, and choose brands through AI.

Explicit research (brand): The final perfect click

Explicit research is any query that includes your brand name, such as:

  • Searches for your name.
  • “Brand name reviews.”
  • “Brand vs. competitor.”

They represent deliberate, high-stakes moments when a potential client, partner, or investor is actively researching your brand. 

It’s the decision stage of the funnel, where they look for specific information about you or your services, or conduct a final AI-driven due diligence check before committing.

What they see here is your digital business card. 

A strong AI assistive engine optimization (AIEO) strategy secures these bottom-of-funnel moments first. 

You must engineer an AI resume – the AI equivalent of a brand SERP – that is positive, accurate, and convincing so the prospect who is actively looking for you converts.

Branded terms are the lowest-hanging fruit, the most critical conversion point in the new conversational funnel, and the foundation of AIEO.

Implicit research (industry/topic/comparison): Being top of algorithmic mind

Implicit research includes any topical query that does not contain a brand name. 

These are the “best of” comparisons and problem-focused questions that happen at the top and middle of the funnel.

To win this part of the journey, your brand must be top of algorithmic mind, the state where an AI instinctively selects you as the most credible, relevant, and authoritative answer to a user’s query.

  • Consideration: When a user asks, “Who are the best personal injury law firms in Los Angeles?”, the AI builds a shortlist, and you cannot afford to be missing.
  • Awareness: When a user asks, “Give me advice about personal injury legal options after a car accident,” your chance to be included depends on whether the AI already understands and trusts your brand.

Implicit research is not about keywords. It is about being understood by the algorithms, demonstrating credibility, and building topical authority.

Here’s how it works:

  • The algorithms understand who you are.
  • They can effectively apply credibility signals. (An expanded version of Google’s E-E-A-T framework, N-E-E-A-T-T, incorporates notability and transparency.)
  • You have provided the content that demonstrates topical authority.

If you meet these three prerequisites, you can become top of algorithmic mind for user-AI interactions at the top and middle of the funnel, where implicit research happens.

Get the newsletter search marketers rely on.

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Ambient research (push by software): Where the algorithms advocate for you

Ambient research is the ultimate form of push discovery, where an AI proactively suggests your brand to a user who isn’t even in research mode. 

It represents the most profound shift yet. Ambient research sits beyond the funnel – it is pre-awareness.

Simple examples include:

  • Gemini suggesting your name in Google Sheets while a prospect models ROI.
  • Your profile surfacing as a suggested consultant in Gmail or Outlook.
  • A meeting summary in Google Meet or Teams recommending your brand as the expert who can solve a key challenge.

In these day-to-day situations, the user is no longer pulling information. 

The AI is pushing a solution it trusts so completely that the engine becomes your advocate.

This is the ultimate goal, signaling that a brand has reached true dominant status as top of algorithmic mind within a niche. 

This level of trust comes from building a deep and consistent digital presence that teaches the AI your brand is a helpful default in a given context. 

It’s the same dynamic Seth Godin describes as “permission marketing,” except here the permission is granted by the algorithms.

It may feel like an edge case in 2025, but ambient research will become a major opportunity for those who prepare now. 

The walls are rising in the AI walled garden 2.0 – the new, more restrictive AI ecosystems. 

The next evolution will be AI assistive agents. 

These agents will not just recommend a solution. They will execute it. 

When an agent books a flight, orders a product, or hires a consultant on a user’s behalf, there is no second place. 

This creates a true zero-sum moment in AI. 

If you are not the trusted default choice, you are not an option at all.

Rethink your funnel: Brand is the unifying strategy

The awareness, consideration, and decision funnel still exists, but the journey has been hijacked by AI.

A strategy focused only on explicit research is a losing game. 

It secures the bottom of the funnel but leaves the entire middle and top wide open for competitors to be discovered and recommended.

Expanding into implicit research is better, yet it remains a reactive posture. You are waiting to be chosen from a list. 

That approach will fail as ambient research grows, because ambient moments are where the AI makes the first introduction.

This landscape demands a brand-first strategy.

Brand is the one constant across all three research modes. AI:

  • Recommends you in explicit research because it understands your brand’s facts. 
  • Recommends you in implicit research because it trusts your credibility on a topic. 
  • Advocates for you in ambient research because it has learned your brand is the most helpful default solution.

By building understandability, credibility, and deliverability, you are not optimizing for one type of search. 

You are systematically teaching the AI to trust your brand at every possible interaction.

The brands that become the best teachers will be the ones an AI recommends across all three research modes. 

It’s time to update your strategy or risk being left out of the conversation entirely.

Your final step: The strategic roadmap 

You now understand the what – the AI resume – and the where – the three research modes. 

Finally, we’ll cover the how: the complete strategic roadmap for mastering the algorithmic trinity with a multi-speed approach that systematically builds your brand’s authority.

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Google AI Overviews: How to remove or suppress negative content

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How to remove or suppress negative content from AI Overviews

By now, we’re all familiar with Google AI Overviews. Many queries you search on Google now surface responses through this quick and prominent search feature.

But AI Overview results aren’t always reliable or accurate. 

Google’s algorithms can promote negative or misleading content, making online reputation management (ORM) difficult. 

Here’s how to stay on top of AI Overviews and your ORM – by removing, mitigating, or addressing negative content.

How AI Overviews source information

AI Overviews relies on a mix of data sources across Google and the open web, including:

  • Google’s Knowledge Graph: The Knowledge Graph is Google’s structured database of facts about people, places, and things. It’s built from a range of licensed data sources and publicly available information.
  • Google’s tools and databases: Google also draws on structured data from its own systems. This includes information from:
    • Business Profiles.
    • The Merchant Center.
    • Other Google-managed datasets that commonly appear in search results.
  • Websites: AI Overviews frequently cites content from websites across the open web. The links that appear beside answers point to a wide variety of sources, ranging from authoritative publishers to lower-quality sites.
  • User-generated content (UGC): UGC can also surface in AI Overviews. This may include posts, reviews, photos, or publicly available content from community-driven platforms like Reddit.

Several other factors influence how this data is organized into answers, including topical relevance, freshness, and the authority of the source.

However, even with relevance and authority taken into consideration, harmful or false content can still appear in results.

This can happen for a variety of reasons, including:

  • Where the information is sourced.
  • How Google’s AI fills in gaps.
  • Instances where it may misunderstand the context of a user’s query.

Removing or suppressing harmful content

There are several options for removing or suppressing negative information on the web, including those related to AI Overviews. Let’s look at two.

Legal and platform-based removal

From time to time, you are left with no other option but to take legal action.

In certain instances, a Digital Millennium Copyright Act (DMCA) claim or defamation lawsuit might be applicable. 

A DMCA claim can be initiated at the request of the content owner. A defamation lawsuit, meanwhile, aims to establish libel by showing four things:

  • A false statement purporting to be fact. 
  • Publication or communication of that statement to a third person.
  • Fault amounting to at least negligence.
  • Damages, or some harm caused to the reputation of the person or entity who is the subject of the statement.

Defamation standards vary by jurisdiction, and public figures may face a higher legal standard. 

Because of this, proper documentation and professionalism are essential when filing a lawsuit, and working with a legal professional is likely in your best interest.

Dig deeper: Generative AI and defamation: What the new reputation threats look like

Working with an ORM specialist

The other (and perhaps easier) route to take is working with an online reputation management specialist. 

These teams are extremely well-versed at handling the multi-layered process of removals.

In an online crisis, they have the tools to respond and mitigate damage. They’re also trained to balance ethical considerations you might not always account for.

Get the newsletter search marketers rely on.

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How to deliver positive signals to AI systems

Clearer signals make it easier for AI Overview to present your brand correctly. Focus on the following areas.

Strengthening signals through publishing 

One effective method is strategic publishing.

This means building a strong, positive presence around your company, business, or personal brand so AI Overviews have authoritative information to draw from.

A few approaches support this:

  • Publishing on credible domains: ORM firms often publish content on platforms like Medium, LinkedIn, and reputable industry sites. This strengthens your presence in trusted environments.
  • Employing consistent branding and factual accuracy: Content must also be factual and consistently branded. This reinforces authority and signals reliability.
  • Leveraging press releases and thought leadership: Press releases, thought leadership pieces, and expert commentary help create credible backlinks and citations across the web.
  • Supporting pages that build the narrative: ORM specialists also create supporting pages that reinforce key narratives. With the right linking and content clusters, AI Overviews is more likely to surface this material.

Leveraging structured data and E-E-A-T

Another effective method to establish credibility on AI Overviews is to focus on technical enhancements and experience, expertise, authoritativeness, and trustworthiness (E-E-A-T). 

ORM specialists typically focus on two areas:

  • Structured data and schema markup: This involves adding more context about your brand online by:
    • Enhancing author bios.
    • Highlighting positive reviews.
    • Reinforcing signals that reflect credibility.
  • Establishing E-E-A-T signals: This includes building a trusted online presence by:
    • Referencing work published in reputable outlets.
    • Highlighting real client examples.
    • Showcasing customer relationships.
    • Outlining accolades and expertise through your bio.

Monitoring AI Overviews and detecting issues early

A final key aspect of staying on top of AI Overviews is to monitor the algorithm and detect issues early. 

Using tools to track AI Overviews is extremely efficient, and these systems can help business owners monitor keywords and detect potential damage.

For instance, you might use these tools to track your brand name, executive names, or even relevant products.

As discussed, it’s also crucial to have a plan in place in case a crisis ever hits.

This means establishing press outreach contact points and a legal department, and knowing how to suppress content via the suppression methods already mentioned.

Ethical considerations

Online reputation management isn’t just generating think pieces. It’s a layered process grounded in ethical integrity and factual accuracy.

To maintain a truthful and durable strategy, keep the following in mind:

  • Facts matter: Don’t aim to manipulate or deceive. Focus on promoting factual, positive content to AI Overview.
  • Avoid aggression: Aggressive tactics rarely work in ORM. There’s a balance between over-optimization and under-optimization, and an ORM firm can help you find it.
  • Think long-term: You may want negative or false content removed immediately, but lasting suppression requires a long-term plan to promote positive content year after year.

Managing how AI Overviews presents your brand

AI Overviews is already a dominant part of the search experience.

But its design means negative or false content can still rise to the top.

As AI Overviews become more prominent, business owners need to monitor their online reputation and strengthen the positive signals that surface in these results.

Over time, that requires strategic publishing, long-term planning, the right technical signals, and a commitment to factual, honest content.

By following these principles, AI Overviews can become an asset for growth instead of a source of harm.

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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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Google tests “Journey Aware Bidding” to optimize Search campaigns

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Is it time to rethink your current Google Ads strategy?

Google is preparing a new Search bidding model called Journey Aware Bidding, designed to factor in the entire customer journey — not just the final biddable conversion — to improve prediction accuracy and campaign performance.

How it works:

  • Journey Aware Bidding learns from your primary conversion goal plus additional, non-biddable journey stages.
  • Advertisers who fully track and properly categorize each step of their purchase funnel stand to benefit the most.
  • Google recommends mapping the entire journey — from lead submission to final purchase — and labeling all touchpoints as conversions within standard goals.

Why we care. Performance advertisers have long struggled with fragmented signals across the funnel. Journey Aware Bidding brings more of their conversion funnel into Google’s prediction models, potentially improving efficiency for long, multi-step journeys like lead gen.

Instead of optimizing on a single end-stage signal, Google can learn from every meaningful touchpoint, leading to smarter bids and better alignment with real business outcomes. This update rewards advertisers with strong tracking and could deliver a meaningful performance lift once fully launched.

What advertisers need to do:

  • Choose a single KPI-aligned stage (e.g., purchase, qualified lead) as the optimization target.
  • Mark other journey stages as primary conversions, but exclude them from campaign-level or account-default bidding optimization.
  • Ensure clean tracking and clear categorization of every step.

Pilot status. A closed pilot is due to launch this year for a small group of advertisers, with broader availability expected afterward as Google refines the model.

The bottom line. Journey Aware Bidding could represent a major shift in Search optimization: Google wants its bidding systems to understand not just what converts — but how users get there.

First seen. The details of this new bidding model was shared by Senior Consultant Georgi Zayakov on LinkedIn, amongst other products that were featured at Think Week 2025.

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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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