ChatGPT Shopping: “Buy Now” in AI Chat Is Here

ChatGPT recommends products — complete with photos, pricing, and purchase links — to its 700 million weekly users.

And now customers can complete purchases without leaving the chat.

BIG deal.

But will ChatGPT recommend your products?

That’s not automatic. And you can’t pay for placement.

What you can do is optimize your site so ChatGPT understands what you sell, trusts your brand, and surfaces your products when buyers search. This guide shows you how.

You’ll learn the eight-step framework for getting featured in ChatGPT Shopping.

I also spoke with Leigh McKenzie, Backlinko’s Head of Growth and founder of the ecommerce brand UnderFit, to get his insights on what’s actually working.

First, let’s look at how ChatGPT decides which products make the cut.

How ChatGPT Shopping Works

ChatGPT Shopping kicks in automatically for some shopping intent prompts.

While it doesn’t fire every time, I found it appears more often than not after testing 100+ prompts.

The key? Typing a prompt with clear buying intent.

Like “e-bikes that can handle potholes.”

ChatGPT – Prompt with clear buying intent

Instead of just explaining things or offering advice, ChatGPT Shopping recommends specific products.

This includes product images, pricing, and links to online stores and websites where users can make a purchase.

Side note: The ChatGPT Shopping experience isn’t consistent. Even with the same prompt, the carousel may (or may not) show. It can also appear at the top, middle, or bottom of the chat. This variability suggests the feature is still evolving.


If your store gets recommended, countless high-intent shoppers will see your products.

For example, when I tested the e-bike query, ChatGPT gave me a brief explanation of what features to prioritize.

But it also provided a visual product carousel with eight products, each in its own card with key details.

(It looks similar to Google Shopping ads, except you don’t have to pay for them.)

ChatGPT – Brief explanation of features & visual carousel

Clicking on any card opens a side panel with:

  • Additional product photos
  • A list of stores, prices, and direct links
  • A short “why you might like this” summary
  • Sentiment pulled from reviews and forums

From there, users simply click “Visit” to reach the merchant’s product page.

ChatGPT – Visit to reach merchant product page

But this experience is changing.

As of September 2025, OpenAI is rolling out Instant Checkout — a feature that lets shoppers buy directly inside ChatGPT.

This is a huge shift.

ChatGPT is no longer just a product discovery tool. It’s a full shopping destination.

ChatGPT – Full shoping destination

Right now, Instant Checkout is only available to Etsy sellers in the United States.

But OpenAI plans to expand this feature to Shopify merchants and other countries soon.

Not on either platform?

They’re also accepting applications for merchants to build their own integrations. (More on this in Step #7.)

How ChatGPT Selects Products to Recommend

A shopper describes what they’re looking for (“running shoes with arch support under $150”), and ChatGPT’s AI goes to work.

ChatGPT – AI process the description

It scans the web for the most relevant products based on that request.

And weighs details like product names, descriptions, features, reviews, brand authority, and other signals to find the best matches.

If your product checks the right boxes — and the information on your site is clear and crawlable — it has a chance to be recommended.

ChatGPT may also consider the user’s location and preferences when making recommendations.

ChatGPT – Consider the user's location

Ultimately, all product recommendations must also pass through OpenAI’s safety systems.

This filters out low-quality, misleading, or unsafe products.

So, what does all of this mean for you?

ChatGPT Shopping is evolving fast — and the brands that keep up will win the most visibility.

Here’s how to ensure ChatGPT can understand, trust, and recommend your products.

1. Add Structured Schema Markup to Your Site

ChatGPT needs structured data to understand what you sell.

Schema markup is code that labels key details on your product pages (and website as a whole): name, price, description, availability, reviews, and more.

Schema Markup Code

It turns raw HTML into data AI tools can parse instantly.

Without it, ChatGPT (and other AI systems) have to guess what’s on your page.

With it, they see clean, structured information they can confidently include in product recommendations.

At a minimum, your product schema should include:

  • Product: Name, description, brand, image, and identifiers (GTIN, SKU, MPN)
  • Offer: Price, currency, availability, and URL
  • Review: Individual reviews with reviewer names and ratings

Detailed SEO Extension – Able Carry – Schema

It may look intimidating, but many content management systems — like WordPress, Shopify, and Wix — offer plugins or built-in tools that generate the markup for you automatically.

RankMath – Schema Generator

Once your markup is in place, test that it’s working correctly using Google’s Rich Results Test or Schema.org’s validator.

These tools make it easy to check that your structured data is valid, visible, and error-free.

Validator – Schema – Backlinko

Pro tip: Go beyond the schema basics. Add AggregateRating for average review scores or FAQPage markup to answer common buyer questions. The more context you provide, the easier it is for AI to surface your product in response to specific prompts.


2. Create and Maintain a High-Quality Product Feed

A product feed is a structured file that packages up your product details and sends them to platforms like Google Merchant Center, Shopify, and Etsy.

It includes details like titles, prices, availability, images, links, and more.

CSV – Product Feed Example

ChatGPT may use data from major platforms like Google to decide which products to recommend.

Pro tip: Want to add your product feed directly to ChatGPT? OpenAI will notify interested merchants when this feature is available. Fill out the Merchant Application form for consideration.


For example, if your Google Shopping feed is outdated, incomplete, or inaccurate, ChatGPT may return bad information about your products.

Or skip recommending them entirely.

That’s why a high-quality, up-to-date product feed is critical.

Side note: If you’re on an ecommerce platform like WooCommerce or Shopify, feeds are usually created automatically.


But keeping feeds accurate is easier said than done.

There are a lot of moving parts, like site updates, refresh schedules, and third-party tools.

And it only takes one slip for mismatches to creep in.

Here are a few common product feed issues — and how to fix them:

Product Feed Problem Why It Happens Fix
Price Mismatch Feed not refreshed, sync delay Enable daily/real-time feed updates. Use one consistent pricing source.
Inaccurate availability Inventory updates on site, but feed refresh lags Sync stock levels in real-time whenever possible. Double-check before campaigns.
Wrong or Truncated Title Feed title auto-truncated or different from H1/meta Align feed titles with on-page H1/meta. Keep product names consistent.
Incorrect image Feed defaults to first gallery image Set hero/product image as primary in CMS and feed
Missing reviews Reviews hidden in JS or not in schema Add Review and AggregateRating schema in HTML
Conflicting schema Multiple apps/plugins overwrite each other Use one schema source. Validate with Schema.org or Google’s Rich Results test

Automation keeps most updates in sync. And manual checks before major launches or sales help catch anything that may slip through.

Here’s how Leigh maintains a balance of the two for his ecommerce store:

“I keep all my product data in a spreadsheet. Whenever I change a product detail, I update it there first. WooCommerce uses that data to update my site’s pages and schema automatically. Then, Channable takes the same spreadsheet and syncs those updates into my product feeds. That way, my site and my feeds are always pulling from the same source, so everything stays consistent.”


3. Make Sure AI Bots Can Read Your Site

If ChatGPT can’t read your site, it can’t recommend your products.

Two simple technical issues block many ecommerce sites from showing up: hidden content and restricted crawlers.

Check for JavaScript

Many AI bots — including ChatGPT — still struggle with content that only loads via JavaScript.

If key details aren’t in the page’s raw HTML, the bot might never see them.

This includes your product descriptions, prices, and images.

Eek.

Here’s how to check if that’s happening:

  1. Pull up a product page on your website or online store
  2. In Google Chrome, go to “Settings” > “Privacy and security” > Site Settings
  3. Under “Content,” click “JavaScript” and toggle “Don’t allow sites to use JavaScript”
  4. Reload the product page you’re testing

Chrome – Settings – Content – JavaScript behavior

If your product details disappear, it means they’re only loading through JavaScript.

To fix this, work with a developer to ensure all essential information is in your site’s raw HTML.

Assess Your Robots.txt File

Your robots.txt file can also block AI crawlers.

This small file tells bots which parts of your site they can (and can’t) crawl.

New York Times – Robots text file

By default, most sites already allow all bots, including ChatGPT’s crawler, OAI-SearchBot.

But it’s still worth double-checking.

Here’s how:

First, go to yourdomain.com/robots.txt. Then, look for a rule like this:

code icon
User-agent: GPTBot
Disallow: /

And this:

code icon
User-agent: OAI-SearchBot
Disallow: /

If it says “Disallow,” then ChatGPT is unable to crawl your site.

GPTBot – Disallow

You (or your dev team) can fix this issue by changing it to “allow.”

4. Write Product Copy That Matches Real Buyer Prompts

ChatGPT matches products to prompts by language, not keywords.

So, if your product copy doesn’t sound like the way people talk, it may not surface in shopping results.

The goal: write the way buyers phrase their prompts.

Find the Language Your Buyers Use

You don’t have to guess how your customers talk.

Use research tools like:

  • Google’s People Also Ask
  • AnswerThePublic
  • Keyword tools like Semrush, Ahrefs, and Moz

Look for modifiers that mimic real queries — terms like “best,” “for beginners,” “eco-friendly,” or “kid-friendly.”

People also ask – Laptop for kids learning

Tools like Semrush’s AI SEO Toolkit show you the actual prompts people type into AI engines.

Semrush – AI SEO Prompt Research – Lingerie

So, instead of manually guessing or testing one by one, you get a ready-made list of conversational queries buyers already use.

Once you understand how your audience speaks, weave the terms naturally into your product titles and descriptions.

This will increase the odds of your products showing up in ChatGPT when shoppers search.

Write Product Titles That Match Buyer Intent

When you’re writing copy, pay special attention to your product titles.

They often feed directly into the shopping carousel.

And they’re the first thing shoppers see before deciding to click.

ChatGPT – Product titles

The golden rule: Lead with what matters most to your audience.

If trust drives decisions — like in categories such as laptops or smartphones — put your brand front and center.

If features, benefits, or use cases are more important, focus on those instead.

Use this simple formula:

[Main Benefit or Feature] + [Product Type] (+ [Brand] if it builds trust)


On Leigh’s site, for example, his titles highlight what buyers care about most: product benefits.

That’s why they’re structured as Benefit (Invisible) + Product Type (Undershirt).

Underfit – Invisible undershirt

But when brand recognition is vital to trust, it makes sense to include the brand name.

Like this product title for a Sony home theater:

Crutchfield – Title include brand name

Don’t worry about cramming every detail into the title.

Most ecommerce platforms give you multiple fields for product info. Use those strategically to sprinkle in conversational keywords.

Make Product Descriptions Feel Like Real Answers

Titles get people to click. Descriptions get them to buy.

This is where you expand on features, benefits, and use cases — all in plain, natural language.

For example, UnderFit’s product copy mirrors the words buyers use when searching for an undershirt.

  • “Stay tucked”
  • “All-day comfort”
  • “Soft, breathable feel”

Underfit – Meta product description as answer

These words aren’t filler — they’re search terms.

Which means they’re likely the same language people use when prompting ChatGPT.

Keyword Magic Tool – Undershirts – Keywords

5. Feature Your Value Proposition Prominently

Your product’s value proposition needs to be clear and visible at the top of your product page.

This ensures ChatGPT immediately understands:

  • What the product is
  • Why it’s better than the alternatives

Huel – Complete Nutrition Bar

But that’s not enough.

The rest of your page should support and reinforce that promise.

This gives ChatGPT a complete picture of your product.

And helps it see your product as the best fit for the query.

This means every section — features, benefits, reviews, specs — should back up your value proposition with proof and detail.

Huel’s Black Edition product page is a great example of this in action.

The value proposition is right under the product title:

“High Protein Complete Meal.”

Huel – High-protein complete meal

This instantly explains:

  • What it is (a complete meal)
  • Why it matters (high protein)

The image reinforces this by highlighting complementary copy:

“This is a meal. Not a protein shake” and “40g protein per meal.”

The product description repeats the promise yet again: “40 grams of protein.”

But it also adds details like “27 essential vitamins and minerals.”

Huel – Black Edition

This repetition is exactly what you want.

While you can (and should) use word variety, your page should tell one clear story from top to bottom.

Explain what the product is, why it’s valuable, and how it delivers on that promise.

So, audit your site.

If copy and images don’t reinforce your core message, rework them until it does.

The more consistent and focused your messaging is, the easier it is for ChatGPT to understand (and recommend) your products.

6. Build Strong Authority Beyond Your Site

ChatGPT doesn’t just look at your product page when deciding what to recommend.

It cross-checks authority signals from across the web to figure out whether your brand (and your product) are trustworthy enough to recommend.

These signals include:

  • Reviews and ratings: Platforms like Amazon, Trustpilot, Google, Yelp, and niche retailers
  • Community sentiment: Real-world feedback from Reddit, Quora, Facebook groups, and niche forums
  • Editorial coverage: Authoritative sites like Wirecutter, TechRadar, gift guides, and industry blogs
  • Awards and certifications: Respected organizations that serve as independent trust markers

How ChatGPT Decides Your Product's Credibility

One way to see which sources matter most for your brand is to run a manual check in ChatGPT.

Type a shopping prompt into the tool, scroll to the answer, and click “Sources.”

ChatGPT – Shopping prompt sources

The links you see there are the sites that ChatGPT used to pull its recommendations.

(And, by extension, the sites it trusts.)

For example, when I asked for a “yoga mat with serious grip for hot yoga,” ChatGPT cited:

  • Niche authority sites like EverydayYoga.com and BrettLarkin.com — smaller but highly trusted in the yoga gear space
  • Mainstream review outlets like New York Magazine and People.com
  • Community threads on Reddit, providing authentic, anecdotal reviews

ChatGPT – Sources as roadmap

Use the sources as your roadmap.

Target them with outreach strategies like expert quotes, partnerships, and co-branded content.

Can’t land mentions on the exact sites ChatGPT cited? Go after similar ones with comparable authority.

And build your presence on community platforms, too.

A strong showing on Reddit, Quora, and niche Facebook groups can boost your brand’s credibility.

7. Sign Up for ChatGPT Instant Checkout

Instant Checkout lets shoppers go from product recommendation to purchase without ever leaving ChatGPT.

Once they find something they like, they can confirm details, pay, and place an order — all within the same chat window.

(Hashtag mind blown)

Instant Checkout currently supports single-item purchases in the U.S. on Etsy.

(But Shopify integration is coming soon.)

If you’re on either platform, you’re in luck. Eligibility is automatic.

For everyone else?

You’ll need to apply and integrate with OpenAI’s Agentic Commerce Protocol (ACP).

Translation: Roll up your sleeves. There’s work to do.

Here’s what you can do now.

Start by filling out OpenAI’s merchant application form.

ChatGPT – Merchants

This lets OpenAI know you want in.

They’re onboarding merchants on a rolling basis and will reach out when you’re accepted.

Once you’re in the pipeline, you’ll need to:

  • Provide a structured product feed that meets OpenAI’s product feed specs. Leigh recommends starting with your existing Google feed and updating it as needed to meet OpenAI’s requirements.
  • Enable ACP checkout. ACP lets ChatGPT place and complete orders in your system. If you’re on Stripe, setup can be as simple as one line of code. If not, you can still integrate using Stripe’s Shared Payment Token API or the Delegated Payments Spec — no provider switch required.
  • Connect your payment provider. You’ll still process transactions and remain the merchant of record.
  • Pass certification requirements. OpenAI requires sandbox testing and end-to-end checks before you go live.

Pro tip: Even if ChatGPT Instant Checkout isn’t available for your store yet, preparing your product data, feeds, and backend now will help you move faster when it is. This should give you a head start as this feature gains popularity.


8. Track Your ChatGPT Visibility

It’s not enough to show up in ChatGPT Shopping.

You also need to measure how well you’re performing.

Start with tracking traffic.

The easiest way is through OpenAI’s built-in UTM tag.

code icon
utm_source=chatgpt.com

This is code that OpenAI automatically adds to all outbound links. And looks like this:

Open AI – Outbound links

Set up a custom segment in Google Analytics to track and analyze ChatGPT traffic to your site.

Once that’s done, look for patterns:

  • Is ChatGPT traffic increasing month over month — or slowing down?
  • How does the conversion rate compare to other channels?
  • Do visitors stick around or bounce right away?

Side note: Not every ChatGPT mention will be traceable. Some users see your product in a chat and search your brand directly on Google instead of clicking. Look for spikes in branded search traffic or direct visits to gauge the broader impact of LLMs.


But traffic only tells you what happens after people click.

You also need to measure what happens before — specifically, which prompts surface your products.

To do this, it helps to understand the kinds of prompts shoppers type.

Most fall into four buckets.

  • Price-based: “Best dog food bowl under $20,” “luxury ceramic dog bowl”
  • Use-case: “Dog bowl for messy eaters,” “raised bowls for large breeds”
  • Feature-based: “Non-slip stainless steel dog bowl,” “slow feeder BPA-free”
  • Problem-solution: “Dog bowl that keeps ants out,” “dog bowl that doesn’t slide on tile”

Shopping Prompt Patterns

Think of these buckets as templates.

Test prompts in each category and ask yourself:

  • Does your product show up? If so, are the details accurate?
  • If not, who does — and why? (Are their reviews fresher, their authority stronger, or their copy closer to buyer language?)

Repeatedly run these checks to gather more data.

You’ll learn which prompts lead to product mentions, how your LLM visibility changes, and how buyers talk about your brand.

Rather automate this process?

Tools like Semrush’s AI SEO Toolkit let you:

  • Track which prompts surface your products
  • Monitor brand sentiment
  • Compare visibility in different platforms

Semrush – AI SEO Overview – Babyletto

Beyond ChatGPT Shopping: Your AI Visibility Playbook

There isn’t a magic formula for getting ChatGPT to recommend your products.

But the brands that consistently get recommended all have three things in common:

  • A rock-solid technical foundation
  • Clear, buyer-focused product copy
  • Strong trust signals across the web

Get these right, and you’re not just optimizing for ChatGPT Shopping.

You’re setting yourself up to be discovered across EVERY AI platform out there.

Want to make sure your foundation is bulletproof?

Read SEO vs. GEO, AEO, LLMO: What Marketers Need to Know for an overview of the most important visibility strategies shaping AI search.

The post ChatGPT Shopping: “Buy Now” in AI Chat Is Here appeared first on Backlinko.

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Audience Research: Stop Guessing What Your Buyers Care About

If I had a dollar for every time someone said “know your audience,” I could retire from marketing altogether.

And yet, most teams are completely winging it.

Too often, marketers equate audience research with half-baked customer relationship management (CRM) data, some social media metrics, and a few buyer interviews.

But that’s just organizing information you already have.

Real audience research means discovering what you don’t know yet.

It’s the exact words people use when they’re frustrated. The solutions they’ve already tried and dismissed. The moment they decide to trust one source over another.

When you get this right, you move from guessing what might work to creating content from what your audience is already telling you.

In this guide, I’ll show you how to find those insights across five key channels, with practical tactics you can use right away.

Download our free Audience Research Tracker

As you go through these methods, I’ll show you how to capture insights in our Audience Research Tracker and turn them into actionable content ideas.


Why You Can’t Skip Audience Research

If you’ve ever lost hours scrolling TikTok or binge-watched “just one more episode” on Netflix until midnight, you’ve experienced the power of audience research.

Platforms like Netflix, YouTube, and TikTok own our attention because they know us better than we know ourselves.

They’ve built this advantage by making audience research a core function.

Netflix, for example, treats “Consumer Insights” as one of its nine core research areas, which shows just how pivotal understanding users is to their success.

Netflix – Consumer Insights

For these winning brands, audience research isn’t an afterthought.

It shapes everything: what gets built, how products are positioned, and which messages resonate

And the payoff is massive — delivering experiences tailored to your customers that keep them coming back for more.

In stark contrast, many marketing teams run on fragments.

SEOs chase keywords, social focuses on engagement, and product marketing fine-tunes messaging. Everyone has a piece of the puzzle, but no one can put it together.

As a result, campaigns are designed for specific channels instead of real people.

Done well, audience research can close this gap to:

  • Sharpen your messaging that customers find relatable
  • Prevent wasted spend by showing you where people actually are
  • Speed up creative cycles by giving teams validated insights to work with

Marketing after audience research

In short: This research legwork aligns marketing with real customer needs, winning customer trust in the process.


And the good news is you don’t need Big Tech’s expensive resources to pull this off.

I’ll show you how to conduct audience research and out-empathize the competition with your existing team and budget.

5 Channels to Conduct Audience Research for Content Marketing

Your buyers are already telling you what they want. You just need to listen carefully.

Let’s learn how.

Make sure to download our tracker and jot down all the information from your audience research techniques.

Tap Into Intel Within Your Company

Some of the most valuable audience insights are already within your reach, sitting with your sales and customer success (CS) teams.

These groups are on the front lines.

They regularly interact with prospects and customers about their frustrations, aspirations, objections, and goals.

For marketers figuring out how to conduct audience research, collecting these insights is a great starting point.

Here’s how:

Source of Insight How It Works What You’ll Learn
Listen to conversations
  • Sit in on sales demos, onboarding calls, or quarterly check-ins
  • Use a simple template to document key takeaways
  • How buyers describe challenges
  • Words and phrases they repeat
  • Factors they prioritize
Sync with frontline teams
  • Run regular sessions with sales, CS, product, and marketing to share notes
  • Common challenges
  • Objections that block deals
  • Features customers love or struggle with
Interview & survey customers
  • Conduct 1:1 interviews with prospects and customers
  • Use surveys to validate patterns
  • Why buyers looked for a solution
  • Their decision-making process
  • Alternatives considered

Listen and Capture First-Hand Conversations

The fastest way to understand your audience is to literally listen.

Sit in on a sales demo, a customer onboarding call, or a quarterly check-in meeting.

This will bring you raw insights you can’t get from surveys, like:

  • The way buyers frame their challenges
  • The decision factors they prioritize
  • The words they repeat

But listening alone isn’t enough.

You need a simple system to document the key takeaways from every conversation and share them across teams.

Here’s an example of what that might look like for a fictional coffee brand:

Audience Research – Conversations

Our Audience Research Tracker will help you distill these conversations into meaningful content opportunities.

You can jot down recurring problem statements in your buyers’ language and identify their biggest pain points.

Then, prioritize ideas based on our four key parameters like urgency, business value, and more.

Audience Research Tracker by Backlinko

Sync with Frontline Teams

Another way to capture these insights is by regularly connecting with your customer-facing teams.

When teams work in silos, each one only sees a part of the puzzle.

This creates a disconnect in your customer experience because no one has the whole picture of what buyers want.

That’s why it’s worth setting up regular cross-team sessions for marketing, sales, customer success, and product teams to compare notes.

These sessions can surface insights that no single team could uncover on its own.

Interview and Survey Customers

Besides internal data, hearing directly from buyers can give you a deeper, more reliable understanding of what drives their decisions.

Customer interviews provide essential context about the why behind their behavior.

You can find out:

  • How they first discovered your product or category
  • What pain points pushed them to look for a solution
  • The decision-making process they followed
  • What alternatives did they consider

With surveys, you can validate these insights and see which ones apply broadly versus one-off anecdotes.

The bottom line: Before spending anything on new research, look inward to collect and process information you already have.


Use Reddit for Unfiltered Conversations

Unlike other social media platforms, Reddit gives you access to candid and often brutally honest conversations.

Take this post on frustrating skincare routines.

It voices raw and real emotions that people face when dealing with skincare challenges.

Reddit – Unfiltered conversations

And in the comments, there are even more stories and nuanced perspectives.

They offer crucial insights about the audience, like “skincare feels like a tough road of trial and error” and the “emotional toll of poor skin health.”

So, how do you use Reddit to know your buyers better?

Start with the Right Filters

Reddit’s filters make it easy to sift through posts and find what matters most.

You can sort results by:

  • Relevance: Best for finding posts that match your keyword directly
  • Top: Surfaces the most upvoted posts over a time period
  • Hot: Shows recently trending posts with the most upvotes
  • Comment count: Sorts posts with the most comments
  • New: Shows you the freshest discussions

Reddit – Posts – Filters

Plus, you can filter results by timeframe to see what’s trending now versus what’s been a consistent pain point over time.

In my search for “moisturizer for oily skin,” filtering by “Relevance” shows the closest matches, while “Hot” surfaces the most recently upvoted posts.

Reddit – Filter – Relevance vs. Hot

Pro tip: Use Google with the search operator site:reddit.comkeyword.” This often works better than Reddit’s native search, especially if you’re looking for niche phrases.


Find the Right Subreddits

While it’s easy to find bigger and popular subreddits, it’s equally important to look for smaller, niche spaces where your audience might hang out.

Remember, the same buyers may express themselves differently depending on the space they’re in.

For instance, a skincare brand could find valuable insights across:

  • r/SkincareAddiction: Broad, general skincare conversations
  • r/AsianBeauty: Discussions centered on Asian markets
  • r/30PlusSkincare: Catering to an older demographic

Each subreddit reflects a different slice of the audience.

Read Posts and Comments Like a Researcher

A good Reddit post will give you context into people’s problems, goals, and lived experiences.

But the comments add more nuance to the original post. This is where people expand on the issue, discuss solutions, and share personal stories.

Here’s a post where the original poster (OP) shares their concerns about using Retinol, an ingredient known for its anti-aging properties.

Reddit – Good post will give you context

Other Redditors share their take and advice on this issue, highlighting some alternatives to consider.

Reddit – Comments & Advices

For a skincare brand, this post is helpful to understand:

  • Buyers’ concerns regarding Retinol
  • Commonly used and recommended solutions

Based on these insights, the brand can create content focusing on the best practices for Retinol use. Another great idea is to make a beginners’ guide for using Retinol and taking care of your skin.

Besides, Reddit also offers something other platforms can’t: clear signals of what not to do.

Upvotes highlight ideas and opinions people love. Downvotes show the perspectives or advice they reject.

Find AMAs (Ask Me Anything)

Ask Me Anything (AMAs) can be a gateway to your audience’s biggest questions or issues they’re curious about.

Any industry expert or influencer with trusted credentials can host an AMA.

Here’s an example from a certified dermatologist.

Reddit – AMAs

Questions asked in this thread reveal issues where people need an expert’s guidance.

For example, one Redditor asked for basic skincare regimens while another shared a question about stretch marks.

Reddit – Comments – Experts guidance

Pay attention to questions with high upvotes. Those are the ones that most people want advice on.

Check Out YouTube Comments and Videos

YouTube is the second-largest search engine where people go to solve problems, compare options, and learn new skills.

Naturally, it can reveal a lot about your buyers.

An audience intelligence tool like Sparktoro is a good starting point for YouTube research.

When you enter any keyword, it lists the most relevant YouTube channels for this audience.

Visit these channels and extract rich insights based on the steps I explain below.

SparkToro – YouTube – Research – Running shoes

Analyze Comments Using LLM Tools

A YouTube video gives you one perspective.

The comments give you hundreds.

For example, this video comparing stainless steel pans with cast iron skillets tells you the creator’s subjective take on the topic.

YouTube – Video perspective

But when you scroll through the comments, you’ll find which option people prefer — and why.

YouTube – Comment's perspectives

Here’s a quick and easy process to document insights from as many YouTube videos as you want.

Copy comments from every video in one go. Then, paste them into ChatGPT or any LLM tool of your choice.

Share this prompt to extract common pain points and themes:

I have added a collection of YouTube comments below. Please analyze them as if you’re conducting target audience research.

Identify:

→ The most common themes and topics people talk about

→ Motivations, desires, or positive outcomes they want

→ Patterns in language (words/phrases that repeat often)

Present your findings in a structured summary. Create a table highlighting frequent pain points, frustrations, or complaints, and add users’ quotes for each pain point.

Here are the comments:

[Paste comments]


This way, you can turn hundreds of scattered thoughts into a structured list of what your audience actually struggles with in their exact words.

I tried this myself and here’s how it went:

ChatGPT – Results for prompt with YouTube video comments

I found a clear breakdown of my audience’s pain points spelled out in their exact words.

Add these to our research tracker — and just like that, I have topics for my next few Instagram reels, like “Health concerns around non-stick pans” and “Why stainless steel pans are better than non-stick.”

ChatGPT – Table of pain points & user quotes

Learn From User-Generated Content

Beyond comments, user-generated content (UGC) can also offer a direct line into what your buyers care about.

Think product reviews, unboxing videos, comparisons, or even vlogs where people share how they use a product.

Notice the kind of pros and cons that people highlight in these videos.

For example, this YouTube creator made a video about his decision to stop using Hexclad pans.

He explains:

  • Why he bought these pans
  • What went wrong with these products
  • What alternatives he considered and switched to

YouTube – Decision to stop using product

Use these insights to understand key buying factors and some pain points worth exploring.

Explore Social Media Platforms Your Buyers Use

Social media works best as an audience research method when you know where your buyers actually spend their time.

Tools like Similarweb make this easier by showing you which channels your audience prefers.

Add your website and a few key competitors to get started, like this example with TechCrunch, Wired, and other competitors.

Here’s how the tool breaks down each brand’s audience share on different social media platforms:

Similarweb – Social networks

The takeaway: Identify the platforms that matter most to your buyers and dig deep into those spaces.


LinkedIn

On LinkedIn, start by identifying people who fit your Ideal Customer Profile (ICP).

Pay close attention to the posts they share — their wins, failures, roadblocks, and processes.

These real-world updates reveal where your product or service can make a meaningful impact.

For example, if your ICP includes customer success teams, this LinkedIn post shows how leaders are experimenting with AI tools.

It highlights both opportunities and gaps you could address — like growing interest in a trend (opportunity) or frequent complaints (gap).

LinkedIn – How leaders experiment with AI tools

To scale your research, use LinkedIn Sales Navigator to apply filters and zero in on the right people within your ICP.

For example, you can filter results by industry, keywords, location, seniority, language, and more of these filters.

LinkedIn – Filters

Instagram

Instagram hashtags are a great way to discover audience interests.

Start with broad themes like #mealprepideas to see what’s trending.

Each hashtag (like a keyword) surfaces a collection of posts tagged with this term.

Instagram – Hashtags search

Look for posts with high engagement because they signal what truly resonates.

For instance, this post earned over 393k likes because it offered clear, visual recipe ideas that people found useful.

Instagram – Clear visual recipe idea

Like LinkedIn, you can also follow influencers or niche creators in your space to get closer to your audience.

Their posts (and especially the comments) often pinpoint the questions, frustrations, and goals your buyers are struggling with.

TikTok

To use TikTok as an audience research method, create a fresh account dedicated to your niche.

Interact only with videos specific to your space, and TikTok’s algorithm will start curating a feed of trending content.

Once you see relevant videos, dive into the comments to spot recurring themes and pain points.

For example, the comments on this meal prep video include many questions about the containers and the recipe.

TikTok – Recipe comments – Questions

You can also search for your keywords and toggle between “Top,” “Users,” “Videos,” and “LIVE” content to explore different kinds of content on the app.

TikTok – Top – Users – Videos – Live

X

X has powerful tools for audience research if you know where to look.

Use the advanced search function to filter posts by keyword, engagement, account, or time frame.

X – Advanced search options

Another underrated feature for target audience research: “Lists.”

It lets you build a curated feed of accounts you want to hear more from, like potential customers, influencers, or industry voices.

You can either follow existing lists or create a new one.

For instance, searching for “vibe coding” lists shows ready-made feeds you can tap into for insights.

X – Search – Vibe coding – Results

Compare Platforms with Semrush Social Tracker

Semrush’s Social Tracker helps you zoom out and learn more about your audience from multiple channels at once.

It pulls data from Instagram, Facebook, LinkedIn, X, YouTube, Pinterest, and TikTok, so you can see how your audience interacts with different channels.

With this report, you can identify which platforms generate the strongest engagement from your target audience.

Semrush – Social Tracker – Facebook

And it’s easier to spot popular post formats (Reels, carousels, videos, etc.) and hashtags that drive interaction.

Semrush – Social Tracker – Hashtags

To get started, connect your social accounts and add competitor profiles in Social Tracker.

Use the “Overview” tab to compare follower growth, posting activity, and engagement side by side.

Semrush – Social Tracker – Overview

Then, jump to platform-specific tabs to get in-depth reports for each platform.

Semrush – Social Tracker – Different tabs

Mine Customer Reviews

A single customer review may just be one person’s opinion.

But when you analyze these reviews at scale, clear patterns start to emerge.

For starters, look for factors that led people to buy a product. Or, notice the cons people mention in low-rated reviews.

Both indicate pain points you can target.

For example, this customer calls out weak product durability and a disappointing warranty process.

Amazon – Customer Review – Bad quality

You also want to find what success looks like for your potential customers. Is it saving time, cutting costs, improving quality, or something else?

Walnut – Comments

Document the features they call out as good or bad.

This insight can shape your messaging and even suggest improvements for your offering.

Tripadvisor – Comment & Improvements

See if reviews pinpoint any competitors that people considered. Note why they chose or didn’t choose a specific brand over others.

Amazon – Customer Review – Anna

Similar to the exercise I suggested for YouTube, collect product reviews from different platforms.

Ask any LLM tool to analyze these reviews and prepare a list of pain points.

Here are the review platforms you should check out based on your business type:

Platform Type of Business
Amazon Consumer products
G2 B2B software & services
Trustpilot Services (consumer & B2B)
Capterra / Software Advice B2B tools & software
Google My Business Local & service businesses
Yelp Local services & hospitality
TrustRadius / PeerSpot Enterprise B2B
Industry-specific sites (Healthgrades, Avvo, etc.) Niche industries (healthcare, legal, etc.)

Make Audience Research Your Competitive Edge

Audience research isn’t simply a box to check.

The more you know about your buyers, the stronger results your marketing efforts can produce.

What’s even better, your audience is already leaving signals about what they want.

When you listen closely and capture these insights, you can create content and launch campaigns that hit closer to home.

Download our Audience Research Tracker to easily document this data and turn these insights into content opportunities.

Next up: Wondering how to tie all your audience-centric content ideas together? Check out our guide on building a customer-focused content strategy to put this research to work.


The post Audience Research: Stop Guessing What Your Buyers Care About appeared first on Backlinko.

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What Is Paid Media?

Turning paid ads into profit is a proven path to scalable, predictable growth.

When you nail it, paid media gives you a steady stream of customers, without depending on Google’s latest update or social media’s shifting algorithms. In fact, digital ad spend hit $259B in 2024 and is expected to keep growing.

But which channels are right for you? How can you weave them together into an effective strategy? And what’s the best way to measure your performance?

Here’s what you need to know.

Key Takeaways

  • Paid media is any form of advertising you pay to place on platforms you don’t own, like Google ads, Facebook posts, banner placements, or influencer partnerships.
  • The big three categories are display ads (banners and videos that stand out), native ads (sponsored posts that blend in), and traditional media (billboards, TV, radio).
  • Search ads and influencer partnerships are the most trusted paid channels because they catch people with intent or leverage existing relationships.
  • A winning campaign has seven steps: get your team aligned, set specific goals, budget for real costs (not just ad spend), know your audience, pick the right channels, create compelling ads, and optimize relentlessly.
  • Track five key metrics: return on ad spend (ROAS), overall return on investment (ROI), cost per click (CPC), impressions, and click-through rate (CTR). These tell you whether you’re making money or just spending it.

Paid Media Basics

Paid media is any kind of promotion that meets two criteria: it happens on a platform you don’t own, and you pay for it.

Banner ads are everywhere, like the ones shown in the Wired article below. 

An example of a banner ad.

Paid media drives real revenue, whether you’re running a startup or managing a global brand.

In research from my team at NP Digital, we found that paid ads make up a meaningful chunk of revenue across businesses of all sizes.

A chart showing percentage of revenue from paid ads by company size.

Paid Media vs. Earned Media vs. Owned Media

Think of marketing like a three-legged stool. The three legs here are paid, earned, and owned media.

Understanding how they work and how they work together can help you build a strategy that covers your blind spots and scales over time.

As mentioned earlier, paid media is any promotional placement you pay for. Think search ads, social ads, banner placements, influencer partnerships, and more.

Earned media is unpaid publicity that your business receives from other people and websites. It’s what others say about your brand mentions in news articles, influencer shoutouts, customer reviews, backlinks, or viral social shares.

Owned media is the stuff you fully control. Your website, blogs, social media accounts, newsletters, and email list, fall into this category. You manage the content, the experience, and the message.

Here’s how they fit together:

  • Paid media helps you get visibility fast, especially when you’re just starting out or entering new markets
  • Owned media builds trust, it’s where your brand message lives
  • Earned media amplifies both. It kicks in when people start talking about what you’re already doing well

The best campaigns use all three. Paid gets attention. Owned keeps it. Earned multiplies it.

Categories and Examples: Paid Media in the Wild

Paid media is evolving fast. Search, social, video, and display are table stakes, but newer formats are gaining traction too, including ads inside large language models (LLMs) like ChatGPT and Gemini.

Even with all this growth, most formats fall into three core categories: display, native, and traditional. There’s often overlap between them, but these labels help keep things simple.

  • Display ads: These are visually distinct image, video, and text ads that appear alongside content on the web. Website banners, YouTube ads, and interstitial pop-ups are all examples. 
  • Native ads: These are ads that fit within the flow of content and are often indistinguishable from it at first glance. Influencer recommendations, advertorials, and sponsorships are well-known forms of native advertising. 
  • Traditional media: Commercials, billboards, and direct mail are examples of traditional media. You don’t get the same tracking or targeting you’d see with digital, but these channels still play a role in large-scale brand awareness.

Now that we’ve covered the broad categories, let’s break down some of the most common paid media channels, and where each one fits.

Search Engine Advertising (Search Engine Marketing)

 Google, Bing, Yahoo, and even Amazon.

While Google Ads dominates the space, Bing Ads (now part of Microsoft Advertising) can offer lower CPCs (cost per click) and a different audience, especially for B2B brands. Amazon Ads also work well for product-heavy businesses.

We found that search ads across platforms drive some of the highest conversion rates in paid media, second only to channels like LinkedIn and influencer marketing.

A graphic showing average conversion rate by channel for ads.

Here’s what the advertising process looks like:

  • Open an account with the ad network (like Google or Bing)
  • Choose the keywords you want to appear for, such as “gardener in Arizona”
  • Set your maximum bid for those keywords (top bidders appear first)
  • Create your advertisement, which will be text-based
  • Launch your campaign and let Google serve your ad on relevant SERPs

The benefit of SEM is intent. You’re targeting users who are already searching for what you offer, which puts them closer to a buying decision.

And if you’re willing to bid competitively, your ad can appear above the organic result, even above your competitors.

Here’s an example of search engine ads for the keyword “paid media consultant.” Note the “Sponsored” label, which helps users distinguish paid ads from organic results.

Search engine ads for the keyword "paid media consultant."

Third-Party Banner Ads

Banner display ads are shown on a third-party online property, usually a website or app. 

Most people think banner ads only appear at the top of pages. Not true. Inline banner ads also show in the flow of content. A banner ad is simply a square or rectangular display ad (an ad that is distinct from surrounding content).

NP Digital research shows that banner ads are the least trusted of all paid media formats, underperforming search and influencer ads significantly. 

An NP Digital graphi showing trust in advertising by channel.

That said, banner ads are good at raising brand awareness. As customers see the same ad repeated across different websites, “brand memory” strengthens. The average person needs to see a brand at least seven times before they make a purchase.

Here’s an example of a fairly conspicuous banner ad on UK news site the Daily Mail

Daily Mail website example of an ad.

The Google Display Network, the world’s biggest display network, consists of over two million websites and mobile apps that businesses can display their ads on—reaching 90 percent of web users worldwide. When someone clicks on an ad, Google Ads and whoever hosted it share the spoils.

Paid Social Media Advertising

Social media advertising is big business. The global market was worth an impressive $252.95 billion at the end of 2024, and this is set to grow in the future.

According to NP Digital research, Facebook generated over $100 billion in ad revenue last year, making it the top-performing social ad platform. Instagram followed at $70.9 billion.

NP Digital graph showing ad revenue by social network.

Here’s an example of paid media advertising on Facebook. This sponsored post is by McDonald’s and appears in relevant customers’ newsfeeds, enticing them to try their $8 Chicken McNugget Meal. These ads blend into the feed but still offer clear calls to action.

McDonald's ad for chicken nuggets and fries.

And it’s not just for B2C. In the LinkedIn ad below, Microsoft targets professionals in banking with an ebook download offer.

Microsoft Cloud ad for AI for bankers.

Social ads work because they meet people where they’re already scrolling. Nearly 60 percent of the world’s population has at least one social media account.

Even better, social platforms give you advanced targeting tools. Most platforms let you target people by age, gender, and location, as well as their hobbies and other social media accounts they follow.

Video Advertising

Video content gets more engagement than static text or images. In fact, one NP Digital study found that short-form and long-form videos accounted for 31.38% and 15.51% of all engagement, respectively.

NP Digital graph showing the type of content that generates the most engagement.

That kind of engagement makes video a powerful paid media tool, especially on platforms like YouTube, Facebook, TikTok, and Instagram.

Video ads show up before or during content users are already watching.

What makes video ads effective is how they combine storytelling with visual cues. Create a stylish, funny, or cool video, and people will naturally want to discover your brand. Like display ads, videos are great for capturing people’s attention on mobile as well.

In-App Ads

In-app ads are paid placements that show up inside mobile apps while someone is using them. These can be banner ads, video ads, interstitials (full-screen takeovers), or rewarded ads where users watch a video in exchange for in-app perks.

You’ve probably seen these in gaming apps, news apps, or streaming services. They appear between levels, in feed scrolls, or before content loads.

An example of an in-app ad.

Source

These ads work well if your audience spends a lot of time on mobile, and even better if you’re targeting users by behavior, interest, or location. App data gives you targeting options you won’t always get on the open web.

Performance varies by industry, but in-app ads tend to perform best for consumer apps, entertainment, retail, and local services.

Digital Out of Home (DOOH) Ads

DOOH ads are digital billboards, transit screens, and signage in public spaces. You’ve seen them in malls, airports, gas stations, elevators, and even gym treadmills.

An example of Digital out of home ads.

Source: BMedia Group

Unlike traditional out-of-home ads, these use screens and software, which means you can update them in real time and target by location, time of day, or audience segment.

They’re a great fit for local campaigns, brand awareness pushes, or national advertisers who want visibility in high-traffic areas. You won’t get click data, but they can be effective for driving searches, visits, and offline conversions.

DOOH is especially useful when paired with mobile or geotargeted campaigns. Seeing a screen ad in a gym, then getting a related offer on your phone, is the kind of multi-touch experience that performs well.

Connected TV (CTV) and Over-the-Top (OTT) Advertising

Connected TV (CTV) and Over-the-Top (OTT) ads show up inside streaming content, on platforms like Hulu, Roku, YouTube TV, and Peacock. These are the ads you see while watching shows or movies on smart TVs, streaming boxes, or even mobile apps.

The big difference? CTV runs on television screens. OTT can run on any device.

An example of CTV and OTT platforms.

Source: Madhive

These ad formats are great for reaching cord-cutters who’ve moved away from traditional cable. They’re also more trackable than old-school TV ads, with options for targeting by location, device, behavior, and even interests.

CTV and OTT ads are especially useful for brand awareness, product launches, and retargeting. You can run short video ads in high-attention environments—and often get better completion rates than on social.

Large Language Model (LLM) Ads

LLM ads are an emerging format of paid placements that appear in large language model tools like ChatGPT, Google Gemini, and Perplexity. These ad types are still in the early stages, but they’re gaining momentum as AI assistants become part of everyday search behavior.

Right now, some platforms are testing sponsored response blocks or product carousels within AI-generated answers. These typically appear when users ask for recommendations, product ideas, or service comparisons.

For marketers, LLM ads offer a new way to show up during early-stage research, especially in verticals like travel, consumer products, software, and education.

Unlike traditional search ads, these placements are more dependent on content quality and relevance than keyword bidding. That gives brands with helpful, trustworthy content an advantage.

This space is still evolving, but it’s one marketers should keep a close eye on. Testing early gives you a head start as AI search platforms build out their ad offerings.

Sponsorships and Advertorials

Sponsorships, advertorials (paid articles), and influencer marketing are the most prominent examples of paid native advertising. 

These ads blend in with regular content.

Here’s an example: an article written by a company executive who’s part of Forbes Council, a paid program that entitles members to publish a set number of articles every year. It looks like editorial content, but it’s paid for, and the author gets guaranteed publishing rights.

An article written by a company executive that's  a part of Forbes Council.

Sponsored posts are everywhere, especially on social. The Instagram post below is clearly labeled as a “Paid partnership with Gymshark.” This post feels authentic because it comes from a trusted influencer, not a brand’s ad account.

Along with that, since the influencer has a loyal, engaged following—the post has over 140,000 likes—the ROI will likely be positive for the advertiser. 

An Instagram post labeled as a paid partnership with Gymshark.

What makes these work? Trust. When the message comes from someone users already trust, it tends to land better, and perform better.

Benefits of Paid Media as a Marketing Channel

Here are some key benefits of paid media for marketers:

  • You have more control. As you pay to advertise, you get more say over your ad’s appearance. Conversely, if you submit a press release to a publication, they may edit it to suit their in-house tone of voice.
  • You get immediate visibility. Search engine optimization (SEO) costs less than paid media, but it can take three to 12 months to see optimal results. With paid media, if you’re happy to pay, you can appear in front of prospective customers immediately.
  • You can measure results. Paid ads platforms offer detailed analytics so you can see how your ads are doing. Some even provide a quality score so you know which campaigns you need to optimize.
  • You can tailor your ads. You can target your ads to specific groups of customers and even tailor content toward a location. This increases the chances of people responding positively to your advertisements. Similarly, you can advise who you don’t want your ad to show to.
  • You can implement automation. You can be as hands-on or hands-off with your advertising as you want. For example, Google Ads offers automated bidding where it automatically optimizes your bids to appeal to people more likely to help you achieve your goals.

Top 5 Paid Media Metrics for Paid Media

You could track dozens of metrics, but these five matter most.

List of key metrics for paid media success.

There are lots of metrics you can use to track the success of your paid media campaigns. The risk is that you get lost in a sea of data. 

I recommend a simplified approach. One that lets you hone in on channels with potential, drop those that aren’t working, and demonstrate a clear ROI throughout. 

Here are my top five metrics for paid media:

These give you a clear picture of performance and help you decide where to optimize or pull back.

  • Return on ad spend (ROAS): ROAS tells you how much revenue you’re generating for every dollar spent on ads. It’s important to measure this separately because it’s the first thing you need to remedy if you’re not achieving a positive ROI overall. If your ROAS drops, you may need to adjust your targeting, creative, or offers.
  • Return on investment (ROI): This is the big one. If you’re generating more from your paid media campaigns than it costs to run them, you’re on the right track. Account for everything—creative costs, time managing ad accounts, A/B testing, etc.—and not just the ad platform fees.  Paid media without ROI is just spend. Use this number to decide whether to scale or pause.
  • Cost per click (CPC): This is the average amount you pay whenever someone clicks on your ad. Ideally, this should be as low as possible. It’s a ripe area for optimization.  CPC is most useful when viewed alongside CTR and conversion rate. A low CPC doesn’t help if nobody converts.
  • Impressions: This is the total number of times users see your ads. A high reach shows that you’ve chosen a channel that gives you exposure to a large audience, which is important for brand building. Low impression count? It might be time to evaluate the reach of your chosen channel.  Impressions alone won’t drive results but they show whether your ads are getting visibility in the first place.
  • Click-through rate (CTR): This is the percentage of people who see and click on your ad. A high CTR shows that people find your ad interesting and valuable.

How to Create a High-ROI Paid Media Campaign: 7 Steps

Illustration of the steps to create a high-ROI paid media campaign.

Paid media can generate traffic, leads, and revenue, but only if you approach it with a clear plan. Skipping strategy and jumping into ad spend is one of the fastest ways to burn through your budget.

Because large amounts of money are involved, caution is your ally. Many businesses burn through cash before giving up on paid media, wondering what went wrong. 

Your paid media strategy should clearly cover the following:

  • Which internal stakeholders you need to include
  • Goals you want to achieve
  • Characteristics of your audience
  • Platform-specific budgets
  • Viable paid media channels
  • Products and services you want to promote
  • Metrics for gauging success 

The process doesn’t need to be complicated. These seven steps will help you build a campaign that’s focused, efficient, and ready to scale.

1. Obtain Internal Stakeholder Buy-In

Getting buy-in goes beyond simple approval. Your team needs to fully understand what’s happening, why it matters, and what role they play.

Start by identifying who needs to be involved. At a minimum, that usually includes:

  • Marketing leadership (budget, goals, channel mix)
  • Creative teams (ad copy, assets, landing pages)
  • Analytics (conversion tracking, attribution setup)
  • Sales (if the campaign impacts lead gen or pipeline)

Don’t wait until after launch to bring these teams in. Paid media works best when everyone is aligned from day one.

Set up a short kickoff meeting to walk through the campaign plan. Cover what you’re promoting, who you’re targeting, what platforms you’re using, and how results will be reported.

It doesn’t have to be a big formal process. A shared doc, quick sync, or even a Slack thread can go a long way.

The goal is to eliminate surprises and make it easy for other teams to support the strategy.

2. Set clear goals and KPIs

You need to know exactly what you’re trying to accomplish. Metrics are important (we’ll come to those later), but goals lay the foundation. 

If you don’t know what success looks like, it’s easy to waste money. That’s why clear goals are the first thing to lock in, before budgets, platforms, or creatives.

Start by asking one question: What do you need this campaign to accomplish?

This could include:

  • Lead generation
  • Product sales
  • Free trial signups
  • App installs
  • Event registrations
  • Traffic to a specific landing page
  • Brand awareness in a new market

Be specific, not general. “More leads” isn’t a goal. “Generate 250 demo requests this quarter at a CPL (cost per lead) under $80” is. Pass your goals through the SMART test: are they Specific, Measurable, Attainable, Relevant, and Timely? The more detailed you make the goals, the easier they will be to achieve.

After that, you can pick KPIs and metrics that match your objective, which we will be talking about in a little bit.

3. Determine budget

With paid media campaigns, it’s essential to set a budget and stick to it. Many paid media platforms let you set a definite upper limit for your ad campaigns. If you exceed this budget, the platform stops showing your ads.

Your budget isn’t just ad spend, but it fuels the entire campaign. Along with the baseline budget for your paid media ads, you must also consider additional costs. These include ad copywriting, graphic design, and videography. If you use an agency, you’ll have to cover ongoing account management fees.

Start by figuring out what success looks like. If your goal is to get 100 leads at $50 each, you’ll need to spend at least $5,000 in ad budget alone. That’s your baseline.

Then add in the supporting costs:

  • Ad creative (copy, graphics, video, landing pages)
  • Tracking and analytics setup
  • A/B testing budget to compare variants
  • Management costs if you’re outsourcing or using tools

Different platforms also have different minimums and cost expectations. Running paid social on Facebook or Instagram can be more flexible for smaller budgets. Search ads on Google or Bing often require more competitive bidding to see traction.

Don’t spread your budget too thin. It’s better to run fewer campaigns with enough spend to test and optimize properly, instead of trying to be everywhere with limited reach.

And whatever number you start with, keep a reserve. Paid campaigns almost always need tweaking in the first few weeks.

4. Know Your Audience

The more specific you get with your targeting, the less you waste on clicks that go nowhere. If you’re paying for media on a publication or newsletter, you can compare your ideal customer profile (ICP) to the audience specs.

Research all the following points for your ICP:

  • Industry or niche
  • Company size or household income
  • Job titles or demographics
  • Location
  • Pain points and goals
  • What platforms they use most
  • What influences their buying decisions

Here’s how your audience research translates into paid media results:

  • Ad platforms: Choose based on where your audience actually spends time
  • Creative: Match tone, visuals, and messaging to their mindset
  • Offers: Promote what solves their problem, not what you want to sell
  • Targeting settings: Use demographics, behaviors, and interests to narrow reach
  • Retargeting: Build separate campaigns for cold traffic vs. returning visitors

The goal is to reach the right people at the right stage and give them a reason to click.

5. Choose Channels

Not every platform fits every goal. The right channel depends on who you’re targeting, what you’re promoting, and how fast you need results.

Take the following into consideration when choosing where to advertise:

  • Use search ads (like Google or Bing) if you’re targeting high-intent keywords. People searching are already looking for solutions.
  • Use social ads (Facebook, Instagram, TikTok, LinkedIn) to create demand or raise awareness. These platforms are great for targeting by interest, behavior, or job title—even if people aren’t actively searching yet.
  • Use display or retargeting to stay in front of people after they’ve engaged. These can bring users back to your site to finish what they started.

You can also learn a lot by seeing where your competitors are advertising. Tools like Meta Ad Library, Google Ads Transparency Center, and manual Google searches will show you what channels they’re using and how often they show up. Look at their messaging, creative, and landing pages. If it’s working for them, it might work for you.

Budget matters, too. Some platforms are better suited to lower ad spend. Facebook, Instagram, and TikTok can give you meaningful reach on a modest budget. Search or YouTube may require more competitive bidding to see real traction.

For smaller budgets, focus on one or two channels where your audience is most active. Don’t try to be everywhere if you can’t afford to run meaningful tests.

And don’t lock yourself into one format. The best campaigns evolve. Start with the highest-potential channel, then expand once you’re confident in performance.

6. Create Compelling Creative

Here are some of my top tips for designing paid media ads that drive clicks:

  • Don’t be afraid of being “loud”—you want an ad that customers stop and look at.
  • Keep your ad copy clear and concise. 
  • User-generated content and testimonials show prospects why existing customers love your brand.
  • If you’re using search advertising like Google Ads, take advantage of assets that tell customers more about your business for no additional cost. 
  • Run multiple variants of your ads from the get-go for some quick A/B test wins. 

But good creative is more than just how your ad looks, it also covers what you say and how fast you get to the point. Lead with the benefit, keep the message tight, and match your CTA to the user’s intent.

Make sure your offer matches the awareness stage also. A discount works well for bottom-of-funnel buyers. But for top-of-funnel, try a quiz, guide, or video to build interest first.

Finally, try to avoid launching with just one ad. Rotate in multiple headlines, formats, and visuals early so you can learn what actually converts before you scale spend.

In addition, some paid media platforms have ad libraries where you can see examples of paid media ads from your competitors. Meta (Facebook and Instagram), TikTok, LinkedIn, and Google Ads all have libraries. They’re fantastic sources of inspiration. 

7. Optimize Your Campaigns

Like all digital marketing campaigns, paid media is not something you can set and forget. When it comes to optimization, little and often wins the race. 

I recommend checking your paid media accounts at least once a week, even once a day if you’re running a short-term campaign.

Paid media is excellent for running multivariate and A/B testing. You can create multiple ad versions with small differences—such as CTA texts or color schemes—and test them against statistically significant sample sizes. 

But don’t stop at testing creative. Optimization includes your audiences, bidding strategy, landing pages, placements, and even campaign structure.

Here’s what to review regularly:

  • Which ads are getting clicks but not conversions? Pause or adjust those.
  • Which campaigns are spending without results? Reallocate that budget.
  • Are certain audiences or geos outperforming others? Double down where it counts.
  • Is your cost per result trending up or down? That’s your early warning system.

Document what you’re testing and why. Optimization doesn’t mean quickly reacting without thinking. Your team needs to learn over time and building a smarter strategy with every round.

Paid Media and AI: Trends You Need to Know

AI is already shaping how campaigns are built, optimized, and scaled. My team and I ran research looking at AI vs. human-generated ads, for example, and found that AI ads converted at 1.28%, less than half a percentage point below human ads, which converted at 1.54%. Yes, human ads performed better. But not by a huge margin. 

NP Digital graph showing the difference between AI-generated ads vs Human-generated ads and which converts better.

I would urge digital marketers to keep the following four points in mind when it comes There are already a growing amount of applications for AI in the world of paid media:

Marketers are using AI to:

  • Write ad copy faster (especially for high-volume campaigns)
  • Build and test ad creative using AI image and video tools
  • Generate audiences automatically based on existing customer data
  • Optimize budgets in real time across channels
  • Predict what offers or creatives will perform best, before spending anything

These aren’t experimental use cases anymore. They’re being built directly into the tools marketers already use.But things are changing fast. Here’s some key points to keep in mind:

  • Paid media isn’t going anywhere: Most paid media channels will remain viable. People will continue to read their favorite publications, open newsletters, follow influencers on social media, listen to podcasts, and so on. Even if traditional SEO and search ads vanish, LLMs like ChatGPT will need to monetize at some point. 
  • Revenue from ads provides stability: As AI changes the way people consume content online, revenue from ads can actually provide more stability. Unlike organic traffic, they’re not dependent on algorithms over which you have no control. 
  • Paid media helps you build brand citations: Branding will be more important than ever in the age of AI. Citations around the web are one of the ways LLMs identify and measure the relevance of your business to a particular query. For example, if “NP Digital” appears often in AI training materials next to “advertising agency,” my brand is more likely to be referenced in response to related questions. 
  • Now is the time to start experimenting with AI: As was shown in the research by me and my team, AI can perform nearly as well as humans. For a head start when AI is truly ready to assist with paid media campaigns, you should start experimenting and learning now. 
  • That said, AI is a tool, not a strategy. You still need strong positioning, good creative, and clear goals. But if you’re not testing AI workflows now, you’re going to fall behind the brands that are.

Should You Focus on One or All Channels?

Most marketers think they need to be everywhere. That’s usually wrong.

To be clear, I’m a big proponent of omnichannel digital marketing. 

When you’re everywhere, you reach more of your prospects. Yet you would be amazed at how many businesses fail to grasp this simple fact.

With that said, for paid, omnichannel may sound great, but isn’t always the right move.

With large amounts of money at risk, you need to do two things: research and test.  

If you’re just getting started with paid media, stick to one or two platforms where your audience is most active. That gives you enough budget and data to learn what works without spreading yourself too thin.

Once you’ve found a winning message and offer, then it makes sense to expand. You can start repurposing creative, retargeting across platforms, and building a true full-funnel system.

Here’s the truth: omnichannel paid marketing only works when you have the team, budget, and systems to support it. Otherwise, it turns into a mess of disconnected campaigns.

Ask yourself:

  • Do you have the creative capacity to build for multiple formats?
  • Do you have enough budget to collect meaningful data across platforms?
  • Can you track performance in a way that ties everything together?

If the answer is yes, go for it. If not, focus and scale intentionally. The best paid media campaigns start small, then scale up.

FAQs

What is paid media?

Paid media refers to any marketing or advertising content a brand pays to place on a third-party platform. Common examples include search engine ads, social media ads, display banners, video ads, influencer sponsorships, and traditional placements like radio, print, or TV.

The key benefit of paid media is the ability to generate visibility and traffic quickly, often with precise targeting and measurable results. Brands typically use paid media to reach new audiences, promote offers, or support other marketing efforts. It works best when paired with earned and owned media in a broader strategy.

How often should you evaluate your paid media budget?

Most brands should evaluate their paid media budget weekly. This allows time to monitor spend, performance, and early signals on what’s working.

For short-term or high-investment campaigns, daily budget checks are recommended to catch issues before they impact results.

Monthly or quarterly reviews are useful for larger budget adjustments, channel planning, or reallocation based on return.

Consistent monitoring ensures your budget is supporting your goals and allows for real-time optimizations, rather than reactive fixes after performance dips.

How do you build a paid media strategy?

A strong paid media strategy starts with setting a clear objective, such as lead generation, product sales, or brand awareness.

From there, define your target audience and select platforms that align with where they spend time. Creative should match the platform and campaign goal, while KPIs like ROAS, CPC, or conversion rate help track progress.

Budget should be allocated based on priorities and expected return, with room for testing.

Successful strategies are built on iteration—launching, analyzing, and optimizing based on what the data shows.

What’s the difference between earned media and paid media?

Paid media includes advertising you pay for, such as social ads, search ads, sponsored content, and display banners. It gives you control over placement, timing, and messaging.

Earned media refers to organic exposure you don’t pay for—such as press coverage, backlinks, user reviews, or social shares.

While paid media drives immediate visibility, earned media builds trust and long-term authority. Most marketing strategies benefit from a mix of both, with paid media often used to accelerate early reach.

Conclusion

Most marketers treat paid media like throwing money at a wall and hoping something sticks. That’s expensive and frustrating.

The brands winning with paid media treat it like a system. They start with one platform, nail their message and targeting, then scale what works. They track the right metrics, test relentlessly, and aren’t afraid to kill campaigns that aren’t delivering.

If you’re just getting started, pick Google Ads or Facebook—whichever platform your audience uses most. Set a budget you can afford to lose while you learn. Create multiple ad variants from day one so you can see what resonates.

Want to see what’s coming next? Check out the latest paid media trends shaping the industry.

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Introducing a new AI-powered package: Track your brand in AI search 

We’re excited to announce the beta release of Yoast AI Brand Insights, available as part of the Yoast SEO AI+ package. This new tool helps you understand how your brand appears in AI-powered answers, and where you can improve your visibility. Ideal for bloggers, marketers, and brand managers, Yoast AI Brand Insights gives you an overview of your brand presence across tools like ChatGPT, Perplexity, and Gemini.

For years, Yoast has helped you get found in search engines. Recently though, search is changing. People aren’t just using Google anymore, they’re turning to AI tools like ChatGPT for answers. Those answers often mention brand names as recommendations. So here’s the big question: when AI tools answer questions in your niche, does your brand show up? Our new tool, Yoast AI Brand Insights (beta), helps you find out. 

Yoast AI Brand Insights lets you see when and how your brand appears in AI-generated answers and helps you understand where you need to focus your effort to improve your visibility. 

Why Yoast AI Brand Insights matters, now 

AI-powered answers are shaping customer decisions faster than ever. Visitors from AI search are often more likely to convert than those from regular search. It’s no surprise, because asking an AI-powered chatbot can feel like getting a personal recommendation. Afterall, word of mouth remains one of the most powerful ways to build trust and spark interest. 

Most analytics tools can’t tell you how your brand appears in AI answers, or if it’s mentioned at all. With more people turning to tools like ChatGPT, Perplexity, and Gemini for advice, that’s a big blind spot if you are trying to get your name out there. 

Yoast AI Brand Insights aims to close that gap. You’ll see when and how your brand appears, what’s being said, and where the information comes from, so you can take action to ensure your brand is part of the conversation. 

See how you stack up against other brands mentioned in your prompts

With just a few clicks, you can: 

  • Check if your brand is mentioned in AI-generated answers for relevant search queries 
  • Benchmark against competitors: see how often your brand comes up 
  • Understand the sentiment connected to your brand: positive, neutral, or negative 
  • Find the sources AI tools use when they mention you 
  • Track your progress over time so you can respond to changes quickly 

Pricing & getting started 

Yoast SEO AI+ is priced at $29.90/month, billed annually ($358.80 plus VAT). The plan includes one automated brand analysis per week per brand, so you can track and compare how your brand is showing up in AI-powered search over time. With each purchase of Yoast SEO AI+ you recieve one extra brand.

With this package you also get the full value of Yoast WooCommerce SEO, which includes everything from Yoast SEO Premium, News SEO, Local SEO, and Video SEO, in addition to one free seat of the Yoast SEO Google Docs add-on.  

For marketers, this means you no longer need to patch together separate solutions for on-page SEO, ecommerce optimization, content creation, or LLM visibility. Everything you need to analyze, optimize, and grow your brand presence is included in one complete package. 

How to get started

  1. Login with MyYoast: secure, single sign-on for all your Yoast tools and products. 
  2. Open Yoast AI Brand Insights: You can find it near the Yoast SEO Academy
  3. Set up your brand: add your brand’s name and a short introduction to your business 
  4. Run your scan: we’ll find relevant AI search queries for you, you can use them or tweak them to your liking. 
  5. Review your results: see relevant mentions and their sources, your brand sentiment, and the AI Visibility Index in an easy-to-read dashboard

Want more details? Check out the full guide to getting started. 

Launching in beta

Yoast AI Brand Insights is now available in beta as part of Yoast SEO AI+. This is your chance to be among the first to explore how your brand shows up in AI-powered search. We’d love your thoughts as we refine the tool, your thoughts here.

See how your brand appears in AI search today 

Get Yoast SEO AI+ today to start your first brand scan. See if and how AI tools are talking about you. 

The post Introducing a new AI-powered package: Track your brand in AI search  appeared first on Yoast.

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Why is summarizing essential for modern content?

Content summarization isn’t a new idea. It goes back to the 1950s when Hans Peter Luhn at IBM introduced one of the first algorithms to summarize text. Back then, the goal was straightforward: identify the most important words in a piece of writing and create a shorter version. What began as a technical experiment has now evolved into a fundamental aspect of how we read, learn, and share information. Summarization allows us to cut through overwhelming amounts of text and focus on what really matters, shaping everything from research and education to marketing and SEO.

In this article, we’ll explore why summarizing is essential for modern content and how both humans and AI-driven tools are making information more accessible, trustworthy, and impactful.

What is content summarization?

Content summarization is the process of condensing a large piece of high-quality content into a shorter version while keeping the essential points intact. The aim is straightforward: to produce a clear and concise summary that accurately represents the meaning of the original text without overwhelming the reader.

Summarization makes information easier to process. Imagine reading a lengthy report or book but only needing the key takeaways for a meeting. It also helps individuals and businesses grasp the core message quickly, saving time and effort.

There are two main approaches to summarize moder content:

Manual or human-driven content summarization

Think back to the last time you turned a long article into a short brief for a colleague; that’s a perfect example and explanation of manual content summarization. In this approach, a human reads, weighs what matters, and rewrites the core points for easy digestion of information.

Manual content summarization requires critical thinking to spot what matters and language skills to explain important information clearly and concisely.

Clear advantages of human-driven content summarization are:

  • The ability to notice nuance and implied meaning
  • Flexibility to shape tone and level of detail for a specific audience
  • The creativity to link ideas or highlight unexpected relevance
  • Judgment to keep or discard details based on purpose

This human-led method complements content summarization AI, giving summaries a thoughtful, audience-aware edge.

AI-driven content summarization

The other approach is powered by technology. AI-driven content summarization utilizes natural language processing and machine learning to rapidly scan through text and generate summaries in seconds. It typically works in two ways:

  • Extractive summarization, where the AI selects the most important sentences directly from the content
  • Abstractive summarization, where the AI generates new sentences that capture the main ideas in a more natural way

The benefits are clear: speed, consistency, and scalability. AI can summarize website content, reports, or articles far faster than a human team. However, it has limits. Context can be missed, and nuances like sarcasm or cultural references may be overlooked. The quality also depends on the AI model and the original text.

Both manual and AI-driven summarization play a crucial role today. Humans bring nuance and creativity, while AI delivers efficiency and scale. Together, they make summarization an essential tool for modern communication.

What are some of the core benefits of content summarization?

Turning lengthy information into clear takeaways is more than convenient. It makes content meaningful, easier to use, and far more effective in learning and communication. Whether done manually or supported by AI tools, summarization offers key benefits:

Enhances learning and study preparation

Summarizing strengthens comprehension and critical thinking by distilling main ideas and separating them from supporting details. Students and professionals can also rely on concise notes that save time when revising or preparing presentations.

Improves focus and communication

Condensing text sharpens concentration on what matters most. It also trains you to express ideas in a precise and structured way, which enhances both writing and verbal skills.

Saves time and scales with AI tools

Summaries allow readers to absorb essential points without having to read hours of content. With AI tools, this process scales further, reducing large volumes of text into clear insights within minutes.

Boosts accessibility and approachability

Summarization makes complex or lengthy content approachable and accessible for diverse audiences. Multilingual AI tools extend this further, breaking down language barriers and ensuring knowledge reaches a global audience.

Why summarization matters in the modern content landscape?

We live in an age of too much information and too little time. Every day, there is more content than anyone can read, which means people make split-second choices about what to open, skim, or ignore. This makes it more important that your content presents clear takeaways upfront before readers move on. Content summarization is how you win that first, critical moment of attention.

Information overload

Digital work and life produce an enormous flood of text, messages, reports, and notifications. This makes it challenging for readers to find the right signal in the noise. Therefore, text summaries act as a filter, surfacing the most relevant facts so readers and teams can act faster and with less cognitive friction.

People scan and skim, so clarity wins

Web reading behavior has been stable for years: most users scan pages rather than read every word. Good summaries present the core idea in a scannable form, increasing the chance your content is understood and used. That scannability also improves the odds of search engines and AI LLM comprehension surfacing your content as a quick response to user queries.

Trust and clarity for readers and systems

A clear and crisp text summary signals that the author understands their topic and values the reader’s time. That builds trust. On the search side, concise and well-structured summaries are what engines and AI systems prefer when generating featured snippets or AI overviews. Being chosen for a snippet or overview can boost visibility and credibility in search results.

Faster decision-making

When stakeholders, readers, or customers need to act quickly, summaries provide the necessary context to make informed decisions. Whether it is an executive skimming a report or a user checking if an article answers their question, summaries reduce the time to relevance and accelerate outcomes. This is also why structured summaries can increase the chance of being surfaced by search features that prioritize immediate answers.

Prominent use cases of content summarization

Content summarization is not a nice-to-have. It is one of the main reasons modern content continues to work for busy humans and businesses. Below are the most practical and high-impact ways in which the summarization of modern content is currently being used.

Business reports

Executives and teams rely on concise summaries to make informed decisions quickly and effectively. Executive summaries and one-page briefs transform dense reports into actionable insights, enabling stakeholders to determine what requires attention and what can be deferred. Effective summaries reduce meeting time, expedite approvals, and enhance alignment across teams.

Educational content

Students and educators use summaries to focus on core concepts and to prepare study notes. AI-driven summarization tools can generate revision guides, extract exam-relevant points, and turn long lectures or papers into study-friendly formats. These tools can support personalized learning and speed up content creation for instructors.

Marketing strategies and reporting

Marketers rely on summaries to present campaign performance, highlight key KPIs, and share learnings without overwhelming stakeholders. Condensed campaign briefs and executive summaries enable teams to iterate faster, align on priorities, and uncover insights for strategic changes. Summaries also make it easier to compare campaigns and track trends over time.

Everyday consumption: news digests, newsletters, podcast notes

Readers and listeners increasingly prefer bite-sized overviews. Newsrooms use short summaries and AI-powered digests to connect busy audiences with high-quality reporting. Podcasts and newsletters pair episode or article summaries with timestamps and highlights to improve discoverability and retention. Summaries help users decide what to read, listen to, or save for later.

Content Summarization & SEO: Does it Benefit in Boosting Organic Visibility?

Did you know that content summarization can help your SEO strategy? Search engines prioritize clarity, relevance, and user engagement, and concise summaries play a role in meeting those criteria. They not only shape a smoother user experience but also help search engines quickly grasp the core themes of your content.

Boosting click-through rates

Summaries also support higher CTRs in search results. A clear and compelling meta description written as a summary can serve as a strong preview of the page. For example, a blog on “10 Healthy Recipes” with a summary that highlights “quick breakfasts, vegetarian lunches, and easy weeknight dinners” is more likely to attract clicks than a generic description.

Improving indexing and relevance

From a technical standpoint, summarization helps search engines with indexing and relevance. Algorithms rely on context and keywords, and well-written summaries bring focus to the essence of your content. This is especially important for long-form blogs, case studies, or reports where the main ideas may otherwise get buried.

Winning featured snippets

Another growing benefit is visibility in featured snippets and People Also Ask sections. Summaries that clearly answer a query or highlight structured takeaways increase the chances of being pulled into these high-visibility SERP features, directly boosting organic reach.

Extending multi-channel visibility

Content summarization also creates multi-channel opportunities. The same summaries can be repurposed as social media captions, newsletter highlights, or even adapted for voice search, where users want concise and direct answers.

Supporting AI and LLMs

Lastly, in the age of AI, summaries provide context for LLMs (large language models). Clean, structured summaries make it easier for AI to process and reference your content, which extends your reach beyond search engines into how content is surfaced across AI-powered tools.

How to write SEO-friendly content summaries with Yoast?

The basics of an effective summary are simple: keep it clear, concise, and focused on the main points while signalling relevance to both readers and search engines.

This is exactly where Yoast can make your life easier. With AI Summarize, you can generate instant, editable bullet-point takeaways that boost scannability for readers and improve how search engines interpret your content.

Want to take it further? Yoast SEO Premium unlocks extended AI features, smarter keyword optimization, and advanced SEO tools that save you time while improving your visibility in search.

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)

What is AI text summarization?

AI text summarization uses artificial intelligence to condense text, audio, or video content into shorter, more digestible content. Rather than just cutting words, it preserves key ideas and context, making information easier to absorb.

Today, summarization relies on large language models (LLMs), which not only extract sentences but also interpret nuance and generate concise, natural-sounding summaries.

How does AI text summarization work?

AI text summarization relies on a combination of sophisticated systems that help a large-language model deeply understand the content, decipher patterns, and generate content summaries without losing any important facts.

Here’s a brief overview of the process of AI-powered content summarization:

  • Understanding context: AI models analyze entire documents, identifying relationships, sentiment, and flow rather than just looking at keywords, allowing the AI models to understand at a deeper level
  • Generating abstractive summaries: Unlike extractive methods, which simply copy existing sentences, abstractive summarization paraphrases or rephrases content to convey the essence in fresh, coherent language
  • Fine-tuning for accuracy: LLMs can be trained on specific domains such as news, legal, or scientific content, so the summaries reflect the right tone, terminology, and level of detail

Benefits of AI text summarization

The true power of AI summarization lies in the value it creates. By blending scale with accuracy, it turns information overload into actionable knowledge.

  • Scales content summarization: Handles hundreds of pages or documents in minutes, which would otherwise require hours of manual effort
  • Ensures consistency: Produces summaries in a uniform style and structure, making information easier to compare and use
  • Saves time and costs: Frees up teams, researchers, and analysts to focus on insights instead of spending time reading
  • Improves accessibility: Makes complex content digestible for wider audiences, including those unfamiliar with technical details
  • Supports accuracy with human oversight: Editors can refine summaries quickly while still benefiting from automation

Practical use cases of AI summarization

AI summarization is not just theoretical. It has already become part of how businesses, teams, and individuals manage daily information flow. Here are some of the common applications of AI summarization which have become a part of our live:

  • Meetings: Automatically captures key points, decisions, and action items in real time
  • Onboarding: Condenses company or project documentation so new team members can understand essentials quickly
  • Daily recaps: Summarizes Slack, Teams, or email threads into clear, concise updates
  • Surfacing information: Extracts relevant context from long reports, technical documents, or customer feedback, ensuring that critical insights are never overlooked

In fact, AI agents are already being used in professional settings to summarize key provisions in documents, with 38% of professionals relying on these tools to expedite the review process. This demonstrates that AI summarization is not just a future possibility, but an integral part of how modern teams manage complex information.

In summary, don’t skip the summary!

Summarization is no longer a sidekick in your content strategy; it is the main character. It fuels faster human learning, strengthens SEO by making your pages clearer to search engines, and ensures AI systems don’t misrepresent your brand. When your content is easy to scan, you reduce bounce rates, improve trust, and increase visibility across platforms where attention spans are short.

This is exactly where a tool like Yoast SEO Premium becomes invaluable. With features like AI Summarize, you can instantly generate key takeaways that work for readers, search engines, and AI overviews alike. Instead of manually condensing every piece of content, you achieve clarity at scale while maintaining editorial control. Summarization is not just about making content shorter; it is about making it smarter, and Yoast helps you do it with ease.

So, to summarize the summary: invest in doing this right, because the future of content depends on it.

The post Why is summarizing essential for modern content? appeared first on Yoast.

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Why A Mobile Measurement Partner (MMP) Is Crucial In A Privacy-First Mobile Ecosystem 

The app marketing space is hugely competitive, and at the same time, data privacy has become the defining challenge for marketers. From Apple’s App Tracking Transparency (ATT) to Google’s Privacy Sandbox, user-level tracking is harder than ever. To stay competitive, you need partners that give you visibility while keeping you compliant. Among these, one of your most important allies is your Mobile Measurement Partner (MMP). MMPS play a central role in any app’s marketing strategy, both for user acquisition and retention. 
 

Key Takeaways

  • MMPs unify your data: They consolidate insights across paid, owned, and earned channels in one dashboard. 
  • True performance visibility: Go beyond just installs by tracking cost per impression, click, install, and deeper engagement metrics.
  • Better budget allocation: Identify which channels deliver real value and optimise spend accordingly. 
  • Unlock user insights: In-app event tracking shows not just where users come from, but what they do after downloading. 
  • Essential for privacy-first marketing: MMPs help navigate iOS privacy changes and ensure accurate measurement. 
  • Stay scalable: They simplify your tech stack, replacing multiple SDKs with a single, integrated solution. 
     

What is an MMP?

App marketers typically run user acquisition (UA) campaigns across multiple platforms and channels, including: 

  • Paid – Meta, Google, Snapchat, TikTok, Apple Search Ads, etc. 
  • Owned – Website, blog, email 
  • Earned – App reviews in independent magazines and review sites 
Search Ads on Apple.

Source: Apple Search Ads  
 

All this activity should lead to people downloading and installing your app, all of which is great, but also meaningless if you can’t track which activity generated each download. And in today’s privacy-first ecosystem, that visibility is harder to achieve than ever. With Apple and Google limiting user-level tracking, attribution can feel like a black-box.  

An MMP helps you cut through the complexity by attributing, collecting, and organizing app data in a privacy-first way, delivering a unified view of campaign performance across channels, media sources, and ad networks. It gives you this visibility of which channels are performing, and which aren’t.  

For each channel, it will deliver metrics such as: 

  • Cost per impression 
  • Cost per click 
  • Cost per install 
  • Cost per acquisition 

These insights enable you to optimise your marketing spend towards the best-performing channels so that you can scale up your UA activities most efficiently. This is particularly important when you consider that app user acquisition costs have increased by 60% in the last five years, reaching an average of $29 per user in 2024, according to research from SimplicityDX, reported by Business of Apps. Understanding where your budget delivers the best results is essential for staying competitive.  

But it doesn’t stop at downloads. The data MMPs generate enables you to dig deeper into the value of each install by looking at what happens “down-funnel” by setting up in-app events. 
 

Use In-App Events to Generate Valuable Insights from your MMP 

In-app events allow you to track what users do in the app after installing it. Each event is a key conversion point in the user’s journey through the app. They will differ depending on the type of app, but will typically include things like: 

  • User registration 
  • Newsletter sign up
  • Clicks on a push notification 
  • Makes a purchase  
  • Join your loyalty program 

You can set up the in-app events that are most relevant to your app and most useful in understanding the value of each user. Your MMP then enables you to track these back to where the install came from. This might reveal, for example, that Meta generates twice as many installs as Apple Search Ads, but that the users who install after clicking on an Apple Search Ads spend three times more in the app than those who came in via Meta.  
 

A graphic showing the value of different channels.

Simplified Reporting in one Dashboard

An MMP delivers all these insights in one unified dashboard, across all the platforms you use to find new users. It’s a far easier way to get a consolidated, real-time view of what’s happening. Even if you’re only active in one or two channels, the insights an MMP delivers into things like Customer Lifetime Value, churn, and conversion against the in-app events you set up far exceed what each platform will typically offer in terms of reporting. 

An MMP dashboard.

The Benefits of Using an MMP

In summary, the key benefits of using an MMP are: 

  • Unified reporting across all platforms in one dashboard 
  • Granular insights into cost per impression/click/install, customer lifetime value, churn, conversion in in-app events 
  • Insights that enable you to optimise your marketing spend and better allocate your budget. 
     

Why Skipping an MMP is a Risky Move

Falling Behind in Privacy Compliance 
With iOS privacy updates transforming the landscape, MMPs are critical for adapting to new tracking systems and ensuring accurate data collection. They provide the agility needed to stay ahead in a rapidly changing privacy environment. 

Misleading Performance Data 
Without an MMP, you’re forced to rely on self-attribution from platforms like Google, which often overinflate their numbers. We’ve seen examples of platforms over-reporting key metrics like installs, leading to inaccurate performance insights. This kind of misreporting can lead to budget misallocation and misguided strategy decisions. 

Missing out on Critical Insights 
MMPs allow you to measure and optimise performance beyond just installs, providing a more comprehensive view of user behavior and value. Leveraging MMP data can reveal that a lower CPI doesn’t always translate to higher-quality users. By analyzing the relationship between CPI and downstream metrics like trial start rates, marketers can refine their bidding strategies to drive better results. Without an MMP, such nuanced insights, and the resulting optimizations, wouldn’t have been possible. 
 

Overcomplicating your Tech Stack 
Skipping an MMP requires integrating multiple SDKs, such as Meta, which not only complicates the setup but also raises significant data and privacy concerns. 
 
 

Setting up your MMP for Success: Best Practices 

Most of the main MMP providers will have integrations across your tech stack, but this is a point worth checking with them when you are assessing providers. If the MMP is integrated across your tech stack, it will be easier to set everything up and gain the insights that will feed your app’s success. For example, if you have already set up in-app events in an in-app analytics tool such as Mixpanel, these can be carried across to the MMP platform to avoid duplicating effort. 
 

1. Define the In-App Events to Optimize Towards

The first step to maximizing the investment in your MMP is to define the in-app events you want to track. The chosen events should reflect meaningful interactions that signal user engagement or progression toward higher-value actions. It’s vital to define these events, not only to monitor when and how frequently they occur, but also to optimise your user acquisition campaigns to align with each funnel stage. Once the user completes an event, i.e.., installs or registers, the point of optimization within the campaigns may change to encouraging conversion to purchase, for example. 
 

2. How many In-App Events should I Track?

It’s not possible, or even desirable, to track everything that happens in your app. We normally recommend around 5-10 in-app events. These should be the key points you want users to convert against, and the ones you can optimise your campaigns towards. Events should describe an action a user takes and should be a combination of a verb and noun, for example: 
 

  • Registration Completed 
  • Watched Video 
  • Product Page Viewed 
  • Purchase Completed 
  • Subscription Purchase Completed 
     

Event names should be easy to read and not overly descriptive. Upper/lower casing is supported, and it is recommended that the verb should be in the past tense (see the example below). 

Top Events Charts.

 
Once you have defined the in-app events, create a tracking plan that details the naming convention for each event (e.g. subscription purchase completed); the point where it triggers (once a user selects the ‘confirm payment’ button on the billing page); and any parameters that provide more detail on that event (e.g., ‘monthly’, signaling that it is the monthly subscription they’ve purchased), then pass that onto your developers to in build as part of the SDK setup. Now you’re ready for testing. 
 

3. Test Everything to Ensure Success

Testing is vital to ensure that your app behaves as it should and that the in-app events are triggered correctly. Once the in-app events are set up, set up an app testing account to simulate the potential user journey and ensure the events show within the MMP testing environment. Use this account to complete each in-app event, ensuring that: 

  1. The events are triggered at the appropriate points 
  1. The tracking is functioning properly 
  1. The data returned is accurate and reliable. 
     

How to Choose the Right MMP to Boost your App’s Growth

A graphic showing how to choose the right MMP.

Choosing the right MMP to work with is all about finding one that is best aligned with your needs and expectations. Choosing the best mobile attribution platform is a detailed process, but essentially this breaks down into four key areas: 
 

  1. Cost and scalability – When allocating your budget for an MMP, you need to look at the bigger picture. As you expand your marketing efforts using an MMP, the associated costs are likely to rise, not just from increased spending on channels but also due to the higher volume of reported conversions within the platform. Remember to evaluate these costs and ensure they remain within your budget as your campaigns grow. 
  1. Functionality – Ask yourself, does the MMP do everything you need it to do? For example, does it provide a holistic view across multiple traffic sources and in terms of the granularity of data you require to understand each channel’s performance? Or, can it show you how much it’s costing you to acquire a click and a conversion? 
  1. Support level provided – Are you looking/able to run everything on the MMP platform yourself, or do you need the support of a managed service? Consider the level of support the MMP offers, especially for troubleshooting setup challenges or addressing questions about the data displayed in the platform.   
  1. Tech stack integration – Consider what level of integration the MMP offers with your existing tech stack, including in-app analytics tools, CRM tools, and DMPs (Data Management Platforms), and any other tools that you rely on to market and sustain your app. 
     

Final Word: Making the Smart Choice

Even the best app needs a constant influx of new users to replace those who churn and deeper engagement with loyal users. Your MMP is key to achieving this, offering a unified view of marketing performance across platforms. It reveals how many installs each platform drives, their cost, and long-term value. Without an MMP, you’re marketing blind as ASO’s future rapidly evolves. 

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Google Ads tests new Labs hub for experimental features

Inside Google Ads’ AI-powered Shopping ecosystem: Performance Max, AI Max and more

Google is piloting a Labs section inside the Google Ads platform, giving advertisers a centralized place to access early-stage experiments and tools.

Why we care. Instead of quietly testing features across scattered accounts, Google appears to be consolidating experiments into a single hub, making it easier for advertisers to discover and try new features before full rollout.

Details.

  • The Labs section shows up at the bottom of the left-hand menu in select accounts.
  • Early tests include features like “missed growth opportunities,” which highlight potential campaign improvements through bid or budget adjustments.
  • Not all advertisers will have access to it.

First seen. The update was first spotted by Vojtěch Audy, PPC specialist at Na volné noze.

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Google adds ROI insights to Meridian marketing mix model

Google is enhancing Meridian, its open-source Marketing Mix Model (MMM), to help marketers make smarter, more precise budget decisions.

Why we care. Understanding ROI across channels is increasingly critical. These new Meridian updates allow for a more precise understanding of what drives sales, factoring in both media spend and non-media variables like pricing and promotions.

The big picture. Here’s what’s new:

  • Non-media variables: Marketers can now include pricing, promotions, and other business levers to measure their impact on sales more accurately.
  • Channel-level contribution priors: New features let you guide the MMM with your own business knowledge, improving the relevance of insights.
  • Longer-term effects: Enhanced binomial adstock decay functions track how upper-funnel media influences purchases weeks later.
  • Optimized spending: Marginal ROI (mROI) priors help pinpoint where the next dollar delivers the highest return, using past campaign performance.

Support and community. Meridian now has 30 certified global partners and an active Discord community, offering guidance to deploy the tool effectively and translate insights into business growth.

The bottom lineThese updates aim to transform Meridian from a measurement tool to a strategic partner for budget allocation. This means Meridian can help marketers optimize spend across immediate conversions and longer-term brand impact.

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Thriving in AI search starts with SEO fundamentals

Thriving in AI search starts with SEO fundamentals

The history of search offers clues about where we’re headed in the AI era – but there’s more to learn and more to do to move forward with practical steps.

AI changes the way people search. Instead of short queries that once required digging through blended results, users can now ask complex questions and get direct answers.

Much of the work to optimize for AI, though, overlaps with what SEO professionals have been doing for years. Our community is already adapting and well-positioned to take on this shift.

This article outlines practical steps to navigate the evolving landscape.

SEO, AEO, GEO: Defining the new terms

Before diving in, it’s worth addressing the terminology. It’s still new, and no single label has fully crystallized for this AI layer on top of SEO.

Two terms have gained traction:

  • AEO (answer engine optimization), which focuses on optimizing content so it’s chosen as the answer in AI-driven results like Google’s AI Overviews.
  • GEO (generative engine optimization), which describes a broader approach across generative AI platforms.

Neither feels perfect. AEO is a bit clunky, and GEO risks confusion with geography and local search. 

Still, these are the terms currently in use. For simplicity, I’ll use GEO in this article.

Dig deeper: The origins of SEO and what they mean for GEO and AIO

How GEO extends SEO

While tools like ChatGPT are undoubtedly cool – and early adopters, myself included, are spending a lot of time tinkering – the broader story is different.

For most people, AI will matter less as a standalone tool and more through its integration into phones, web browsers, and search engines.

GEO is a new layer that sits above SEO.

Often, tools like ChatGPT will search and compile information.

These tools provide a layer of abstraction and do much of the grunt work.

They still scan the digital world and then collate that information to simplify things for the user, while search engines like Google continue to provide the best overall digital map of the world.

If traditional SEO was about matching keywords, AEO is about being the best answer – and the easiest to integrate into an AI response.

GEO: Strategic foundations 

There’s no firm consensus on GEO tactics, but most of what’s recommended is simply good SEO.

That said, tactics that lost ground in the zero-click landscape may regain utility in AI Mode, where the AI does the deep dive and collates information for users.

Here are some basic strategic foundations to put in place to set yourself up for visibility in AI tools.

1. Focus on your customers

I’ve long championed bringing traditional marketing thinking into SEO, and GEO is the natural evolution of that approach.

Know your audience. Create personas, gather feedback, and define their goals, pain points, and the jobs they rely on your product or service to support.

Customer insight is key to building a customer-first strategy that helps you stand out in the age of AI.

2. Real expertise wins

The web is full of derivative content that does little to stand out. This creates a problem for AI. 

Model collapse happens when AI keeps training on AI-generated content without new signals, leading to increasingly stale and inaccurate results.

The solution is what humans are still best at – fresh insights from: 

  • Interviews.
  • Original research.
  • Proprietary data

These provide AI with something new – and worth citing.

That’s an opportunity. Have a voice, and bring something original to the table.

Frameworks like the Value Proposition Framework and SCAMPER can also support your SEO content marketing process here. 

3. Branding is key

Homepage traffic is up as a result of mentions in AI tools.

Recent studies show engagement from AI-driven traffic may even surpass organic, long the gold standard for user engagement.

Make sure your branding is strong. 

Create unique names for your products and services so they’re easy to reference in AI tools and simple for users to search.

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4. Your website is important

Your website remains critical in the age of AI.

Anything you publish will likely drive brand searches and send people to your site. 

Structure it so visitors landing on your homepage can quickly explore and find more detail.

Dive into your customers’ wants, needs, and pain points – and answer the questions that matter most to them.

The ALCHEMY website planning framework can help guide this work.

5. Conversational content works

Think beyond static blog posts. Consider:

  • FAQs that are detailed and rooted in customer insight.
  • Step-by-step explainers.
  • Long-form guides that anticipate follow-up questions.

Structure your content to cover all your customers’ questions and concerns. 

Remember, many will turn to AI to learn more about you.

6. Beyond Google

Gen Z already uses TikTok and Instagram as search engines. 

YouTube remains the second-biggest search platform globally. 

AI-powered tools are simply the next step in the ongoing fragmentation of upper-funnel discovery.

Your approach should be to diversify your content so it surfaces wherever people look:

  • Your own website.
  • Third-party sites and industry publications.
  • Social platforms like TikTok and Instagram.
  • Search engines such as Google and Perplexity.
  • Video and professional platforms like YouTube and LinkedIn.

Think of modern AI SEO as search everywhere optimization.

Dig deeper: What’s next for SEO in the generative AI era

What to do next: Practical steps for marketers

AI is helping people research and make purchase decisions. Your role is to be part of the discussion.

Modern SEOs are in good shape – much of what AI requires builds on the strategic SEO work we already do.

Add in some PR, social media, and content creation (which often sit under the SEO umbrella), and you’re well on your way to a functional GEO strategy.

Getting started is crucial. To stay ahead:

  • Create content worth quoting: Write the piece an AI (or a human journalist) would want to reference. That means clear answers, evidence, original insights, and a point of view – not filler.
  • Anticipate the full conversation: Don’t just answer the first question – answer the follow-ups, too. If someone asks, “How does AI change SEO?” they’ll also want to know, “What should I do about it?” Build that into your content.
  • Structure for machines and humans: Use headings, lists, FAQs, and concise summaries to help AI parse your work. But don’t forget the narrative depth that keeps people reading.
  • Diversify your discovery footprint: Don’t rely on Google alone. Research your audience, understand their hangouts, and publish in the formats and places where they ask questions today: LinkedIn, YouTube, podcasts,and industry forums. AI tools crawl all of it.
  • Focus on authority signals: Show the human behind the content. Add author bios, cite sources, and link to your work elsewhere. AI engines, like search engines before them, lean on trust and authority.
  • Experiment, measure, refine: Try different formats, test and measure how your content shows up in AI summaries, track brand mentions, and adapt. SEO has always been iterative – this new era is no different.

The opportunity in the chaos

As SEO evolves into GEO – or whatever it may end up being called – this really is the best approach.

There’s no doubt a lot of change is happening. 

But much of it is part of the same gradual evolution we’ve seen before, where clicks declined and Google started answering questions directly.

AI now makes it even easier for customers to find the information they’re looking for. 

They may not read it on your site – at least not initially – but the AI will, and that’s the point.

Another strength we have as SEOs is that change is constant. 

If you’ve been in SEO for any length of time, you’ve lived through Panda, Penguin, Mobilegeddon, BERT, helpful content updates – the list is long (and may cause PTSD for many of us).

The key is to treat this as the next evolution. AI is being integrated into search, and it will likely become the way the masses adopt the technology.

Don’t see this as the death of SEO. 

Instead, view SEO and AI (or GEO/AEO, etc.) as close, contributing partners, and evolve your plan to match the changing landscape.

Your job as a marketer is to feed these tools the information they need to point customers to you and your clients.

This shift will likely mean fewer short-term manipulations and tactical opportunities – but better results for businesses that do the basics well. 

At its core, good SEO/GEO is just good marketing: understanding your customers, meeting their needs, and communicating clearly.

Amid the chaos lies opportunity. For those willing to embrace the challenge, experiment with new tools, and keep going.

That’s what we’ve always done as SEOs, which is why we’re best positioned to embrace this new world.

Dig deeper: SEO at a crossroads: 9 experts on how AI is changing everything

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AI Max in action: What early case studies and a new analysis script reveal

AI Max testing

Google’s AI Max for Search campaigns is changing how we run search ads. 

Launched in private beta as Search Max, the feature began rolling out globally in late May, with full availability expected by early Q3 2025. 

But will AI Max actually drive incremental growth or simply take credit for conversions your existing setup would have captured anyway? 

This article:

  • Breaks down the key metrics to track in AI Max.
  • Shares early results from travel, fashion, and B2B accounts.
  • Includes a Google Ads script to make analysis faster and easier.

Understanding AI Max

Think of AI Max as Google combining the best parts of Dynamic Search Ads and Performance Max into regular search campaigns. 

It does not replace your keywords. Instead, it works alongside them to find more people who want what you’re selling.

AI Max does three main things.

  • Finding new search terms your keywords might miss, using search term matching.
  • Writing new ad headlines and descriptions that match what people are actually searching for.
  • Sending people to the best page on your website instead of just the one you picked.

The real game changer came in July 2025, when Google began showing AI Max as its own match type in reports. 

Before this, figuring out what AI Max was doing felt like looking into a black box. 

Now, we can finally see the data and make smarter decisions.

Evaluating AI Max: Metrics that matter

When you’re looking at AI Max performance, start with the basics. 

Open your search term tab and look for the Search terms and landing pages from AI Max option. 

This lets you see AI Max results separately from your exact match, phrase match, and broad match keywords.

Compare conversion share and budget share

The first thing to check is how many conversions come from AI Max versus your regular keywords. 

If AI Max is bringing in 30% of your conversions but eating up 60% of your budget, you know something needs attention. 

Look at the cost per conversion, too. 

AI Max might cost more at first, but that’s normal while Google learns what works for your business.

Look beyond cost – focus on conversion rates

Don’t just focus on the cost. Pay attention to conversion rates. 

AI Max often finds people who are ready to buy but use different words than you expected. These new search terms can be gold mines if you spot the patterns.

One of AI Max’s biggest benefits is finding search terms you never thought to target. 

Look at your search terms report and filter for AI Max queries. You’ll probably see some surprises.

Let’s say you sell running shoes and target “best running shoes.” AI Max might show your ads for “comfortable jogging sneakers” or “shoes for morning runs.” 

These are people who want the same thing but use different words. The smart move is to add these high-performing terms to your regular keyword lists.

Identify irrelevant traffic 

If you’re getting clicks from people searching for “cheap shoes” when you sell premium products, add “cheap” as a negative keyword. 

AI Max respects negative keywords, so use them to guide the system toward higher-quality queries.

Dig deeper: Google’s AI Max for Search: What 30 days of testing reveal

Tracking the learning process

Every AI system needs time to learn, and AI Max is no different. 

Plan for a learning phase

The first few weeks often look expensive because Google is still figuring out what works. Don’t panic if your costs jump initially.

Track your performance daily during the first month

As AI Max learns your patterns, you should see costs stabilize and conversion rates improve. If things keep getting worse after three weeks, then it’s time to make changes.

Keep an eye on the types of search terms AI Max finds over time

Early on, you might see lots of random queries. As the system learns, the terms should become more relevant to your business goals.

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When things go wrong

The biggest mistake people make is changing too much, too fast. 

AI Max needs data to work properly, and constantly adjusting things prevents the system from learning.

That said, some problems need quick fixes. 

  • If AI Max is spending money on completely irrelevant searches, add negative keywords immediately. 
  • If the AI creates ads that violate your brand guidelines, remove those assets right away.

Watch your overall account performance, not just AI Max numbers. 

Sometimes, AI Max might look expensive on its own, but it actually helps your other campaigns perform better by capturing different types of traffic.

Planning for the future

AI Max is still evolving, and Google keeps adding new features. 

To adapt:

  • Build reporting systems that can grow with these changes. 
  • Set up automated reports for the metrics that matter most to your business.
  • Don’t try to control everything. 

The businesses seeing the best results from AI Max are the ones that:

  • Set clear goals.
  • Provide good data.
  • Let the system do its job. 

Your role shifts from managing keywords to managing strategy.

Start testing AI Max on a small scale if you’re nervous about it. For example:

  • Create one campaign with AI Max enabled and compare it to your existing campaigns.
  • Run an AI Max for Search campaign experiment and let Google evaluate if the experiment is statistically valid. 

Once you see how it works for your specific business, you can decide whether to expand.

Case studies: AI Max in action

These are early results from a limited data set and shouldn’t be viewed as statistically significant. 

I’m sharing them to illustrate what I’ve seen so far – but the sample size is small and the timeframe short. Take these numbers with caution.

Case 1: Tourism and travel

This advertiser already had a solid search setup and was seeing good results. 

Growth, however, was difficult because of heavy competition and the fact that strong keywords were already in play within a modern search structure.

Match type Avg. CPC (€) CVR (%)
AI Max €0.11 1.47%
Broad match €0.09 3.79%
Exact match €0.53 9.00%
Exact match (close variant) €0.22 7.11%
Phrase match €0.16 6.25%
Phrase match (close variant) €0.11 3.27%

AI Max generated additional conversions, but relative to the existing setup the impact was limited. 

The conversion rate was much lower than other match types. 

Because the average CPC was low, there was no cost spike, but performance still lagged.

Broad match – also known for surfacing broader, newer queries – had an even lower CPC (€0.09) and a conversion rate more than twice that of AI Max. 

In this account, AI Max’s contribution was minor.

Search term overlap analysis showed AI Max had a 22.5% overlap rate, meaning 77.5% of queries were new to the campaign. 

That’s a fairly good sign in terms of query discovery.

Case 2: Fashion ecommerce

This account focused on women’s clothing and already had a well-optimized campaign. 

The goal was to expand reach during the competitive holiday season, when exact match keywords became increasingly expensive.

Match type Avg. CPC (€) CVR (%)
AI Max €0.08 2.15%
Broad match €0.12 2.89%
Exact match €0.67 8.45%
Exact match (close variant) €0.28 6.78%
Phrase match €0.19 5.92%
Phrase match (close variant) €0.14 4.11%

AI Max performed well here, delivering the lowest CPC at €0.08 and a respectable 2.15% conversion rate. 

Although conversion rates were lower than exact and phrase match, the cheaper clicks kept cost per acquisition competitive. 

AI Max also captured fashion-related long-tail searches and seasonal queries that the existing keyword set had missed.

Notably, AI Max outperformed broad match with both lower costs and better conversion rates. 

This suggests its ability to better understand product context and user intent – especially important in fashion, where search terminology is diverse.

Search term overlap analysis showed only an 18.7% overlap rate, meaning 81.3% of queries were completely new. 

That level of query discovery was valuable for extending reach in a highly competitive market.

Case 3: B2B SaaS

This account promoted project management software and had a mature strategy focused on high-intent keywords. 

Conversion tracking was strong, measuring both MQLs and SQLs. 

The client wanted to test AI Max for additional lead generation opportunities.

Match type Avg. CPC (€) CVR (%)
AI Max €0.89 0.76%
Broad match €0.72 1.23%
Exact match €1.84 4.67%
Exact match (close variant) €1.22 3.91%
Phrase match €1.05 3.44%
Phrase match (close variant) €0.94 2.88%

In this case, AI Max struggled. Despite a reasonable CPC of €0.89, the conversion rate was just 0.76%. 

That pushed CPA well above the client’s target, making AI Max the worst-performing match type in the account. 

It tended to capture too many informational searches from users not yet ready to convert.

Even broad match, typically associated with lower-intent traffic, outperformed AI Max with a 1.23% conversion rate at a lower CPC. 

The complexity of the B2B buying cycle favored exact and phrase match keywords over AI Max’s broader interpretation.

Search term overlap analysis showed a 31.4% overlap rate, leaving 68.6% of queries as new. 

However, these were mostly low-intent informational searches that didn’t align with SQL goals – underscoring the importance of high-quality conversion tracking when evaluating AI Max.

Wider industry sentiment

Advertiser feedback so far mirrors these mixed results. 

In a recent poll by Adriaan Dekker, more than 50% of respondents reported neutral outcomes from AI Max, while 16% saw good results and 28% reported poor performance.

Tips to analyze AI Max search terms

You can analyze AI Max queries in Google Sheets using a few simple formulas. If your search term report has the term in column A and match type in column B:

  • To check whether a search term appears in both AI Max and another match type:

=IF(AND(COUNTIFS($A:$A;A2;$B:$B;"AI Max")>0;COUNTIFS($A:$A;A2;$B:$B;"<>AI Max")>0);"Overlap";"No Overlap")

  • To count how many match types trigger a given term:

=COUNTIFS($A:$A;A2) can be used to count how many match types trigger on that search term.

  • To measure query length with an n-gram analysis:

=(LEN(A1)-LEN(SUBSTITUTE(A1," ","")))+1

These checks show whether AI Max is surfacing unique queries, overlapping with existing match types, or favoring short-tail vs. long-tail terms.

Because AI Max is still in early stages, it’s hard to draw firm conclusions. 

Performance may improve as the system learns from more data, or remain flat if your setup already covers most transactional queries. 

That’s the question advertisers will answer in the coming months as more tests and learnings emerge.

So far, results can be positive, neutral, or negative. 

In my experience, neutral to negative outcomes are more common – especially in accounts with strong existing setups, where AI Max has fewer opportunities to add value.

A Google Ads script to uncover AI Max insights

To make analyzing AI Max performance easier, I created a Google Ads script that automatically pulls data into Google Sheets for deeper analysis. 

It saves hours of manual work and includes the exact formulas mentioned earlier in this article, so you can immediately spot overlap rates and query patterns without manual setup.

The script creates two tabs in your Sheet:

  • AI Max: Performance Max search term data with headlines, landing pages, and performance metrics.
  • Search term analysis: A full comparison of all match types, including AI Max, with automated formulas.

The analysis covers:

  • Overlap detection between AI Max and other match types.
  • Query length analysis (short-tail vs. long-tail).
  • Match type frequency counts to identify competitive terms.
  • Automatic cost conversion from Google’s micro format into readable currency.

How to use it:

  • Create a new Google Sheet and copy the URL.
  • In Google Ads, go to Tools > Scripts.
  • Paste the script code and update the SHEET_URL variable.
  • Run the script to automatically populate your analysis.

With this setup, you can quickly calculate the same metrics I used in the case studies – like the 22.5% overlap rate in the tourism account or the 81.3% new query discovery in fashion. 

The automated workflow makes it easier to see whether AI Max is surfacing genuine new opportunities or simply redistributing existing traffic.

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