Yoast SEO free vs Premium: why upgrading is worth it

Do you want to take your site’s SEO to the next level? Yoast SEO Premium can help you out! But there is also a free version of Yoast SEO. So, what exactly is the difference between the free version of Yoast SEO and Yoast SEO Premium? How do these two compare? And is Yoast SEO Premium worth it? Let’s uncover the ten reasons why you should buy Yoast SEO Premium today!

Yoast SEO free vs premium: what is the difference?

Do you want to compare the main differences between Yoast SEO Free and Premium? This table will give you quick insights:

Yoast SEO Free
Find other ways to optimize your website for SEO
No comprehensive SEO solution. You’d need to find other ways to optimize your website, especially if you have a local business, a news website, or if you have a lot of videos.

No AI
You have to manually optimize all your content yourself.

No AI
You have to manually write and optimize all your SEO titles and meta descriptions yourself.

Only 1 keyword per page
Optimize for one keyword per post or page.

No redirect manager
Forgetting to set up a redirect results in visitors hitting a 404 page, which displeases both them and Google.

You need to guess which links would work best
Identify which pages to link to for improved rankings, for both new and existing pages on your site.

No preview of your page on social media
Without a preview of social snippets, you’re left guessing and hoping for the best.

No support
No support
You can help yourself with our extensive knowledge database.

Manually edit robots.txt file
Manually edit your robots.txt file to block AI bots, at the risk of making mistakes.

No free access to the Yoast SEO Google Docs add-on
Transferring draft content from Google Docs to your website for SEO optimization slows your workflow and makes collaboration with internal and external teams more time-consuming.

Yoast SEO Premium vs Yoast SEO Free
Includes Local SEO, Video SEO, and News SEO plugins
Yoast SEO Premium provides everything you need to improve your website’s visibility, whether you’re a business owner, publisher, agency, or content creator.

Find other ways to optimize your website for SEO
No comprehensive SEO solution. You’d need to find other ways to optimize your website, especially if you have a local business, a news website, or if you have a lot of videos.

(Beta) Get AI-powered suggestions to optimize your content
Get optimization suggestions and apply changes instantly with Yoast’s AI features, saving you time and ensuring your content is search engine-friendly. This feature is currently in beta.

No AI
You have to manually optimize all your content yourself.

(Beta) Get high-quality titles and meta descriptions with Yoast AI
Yoast’s AI helps you craft optimized SEO titles and meta descriptions for search and social, boosting your CTR while saving you time.

No AI
You have to manually write and optimize all your SEO titles and meta descriptions yourself.

Optimize for up to five keyword synonyms by adding variants
Include up to four keyword synonyms for a broader reach, and receive a complete SEO analysis for each one.

Only 1 keyword per page
Optimize for one keyword per post or page.

Automatic redirects: so no more dead links or 404 errors
Effortlessly redirect old or renamed pages to maintain satisfaction for both your visitors and Google.

No redirect manager
Forgetting to set up a redirect results in visitors hitting a 404 page, which displeases both them and Google.

Get real-time suggestions for internal links
As you write, you’ll receive suggestions for internal links to other pages, which Google favors and can boost your ranking.

You need to guess which links would work best
Identify which pages to link to for improved rankings, for both new and existing pages on your site.

Preview your page on Facebook and Twitter/X
You have complete control over your page’s social media appearance, ensuring it entices users to click.

No preview of your page on social media
Without a preview of social snippets, you’re left guessing and hoping for the best.

24/7 support
Our helpful and expert support team is ready to assist you with any questions via email or live chat.

No support
No support
You can help yourself with our extensive knowledge database.

Safeguard your content from being used to train AI bots
Easily protect your intellectual property and data privacy by blocking AI bots from scraping your content with a simple toggle.

Manually edit robots.txt file
Manually edit your robots.txt file to block AI bots, at the risk of making mistakes.

Includes 1 free seat to the Yoast SEO Google Docs add-on
Create and optimize your SEO content in Google Docs with Yoast’s guidance, ideal for teamwork with internal and external partners. Enjoy 1 free seat, valued at $5/month.

No free access to the Yoast SEO Google Docs add-on
Transferring draft content from Google Docs to your website for SEO optimization slows your workflow and makes collaboration with internal and external teams more time-consuming.

What are the benefits of Yoast SEO Premium?

For over fifteen years, Yoast SEO has provided small businesses, bloggers, marketers, and online and offline stores with almost everything they need to compete in the search results. Over the years, we made the plugin better and better — following feedback from users, through thorough research and insights from insiders at the search engines. Today, Yoast SEO is run by a team of passionate SEO experts and built by very talented developers.

While the free version of Yoast SEO gives you a lot of tools to help you do well in the search results, Yoast SEO Premium makes many tasks much easier. It saves precious time that you can invest in other ways. Yoast SEO Premium also gives you additional tools, like, for instance, Local SEO, AI features, internal linking suggestions, and the redirect manager. You can use all of these tools to build an impressive site structure. All of this helps make your site a great fit for users and search engines alike. As such, Yoast SEO Premium is a wise investment.

Buy Yoast SEO Premium now!

Unlock powerful features and much more for your WordPress site with the Yoast SEO Premium plugin!

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

1: Yoast SEO Premium comes with amazing AI features

Yoast SEO Premium now offers AI-powered features that streamline your SEO tasks. With Yoast AI Generate, you can create engaging titles and meta descriptions effortlessly. Choose from multiple options or generate more until you find the perfect fit. Meanwhile, Yoast AI Optimize provides smart suggestions to enhance your existing content, ensuring SEO best practices are met with just a click. These tools integrate smoothly into your workflow, saving you time and effort while keeping your content search-engine friendly. Available for WordPress and Shopify, these features help you maintain control over your content’s final look and feel.

2: Yoast SEO Premium comes with all add-ons

Yoast SEO Premium now includes various separate add-ons, such as News, Video, and Local SEO, in one convenient package. This comprehensive suite enhances your optimization capabilities without needing additional purchases. However, the WooCommerce SEO add-on is not included and is available separately. Enjoy a streamlined experience to boost your site’s performance across different content types and media.

3: Yoast SEO Premium is a time-saver

One of the most important things you need to remember about SEO is that it is never done. There’s always more to do, better content to write, or fixes to make. Luckily, there’s a WordPress SEO plugin that’s glad to be of assistance. As you might know, Yoast SEO is not a set-it-and-forget-it kind of tool. You need to work with it, whether it’s improving your content or building your site structure. In the free version, you still need to do much of the work yourself. Yoast SEO Premium comes with a number of AI tools that can save you lots of time.

4: Use Yoast SEO in Google Docs

The Yoast SEO Google Docs add-on allows you to draft and optimize your SEO content directly within Google Docs. This tool is ideal for seamless collaboration with both internal teams and external partners. You can work on content, refine it, and ensure it aligns with SEO best practices, all without leaving your document. This efficiency streamlines your workflow and enhances team cooperation. Plus, Yoast SEO Premium includes one user seat for this add-on, typically valued at $5 per seat.

Readability Analysis in Google Docs Yoast SEO add-on
You can enjoy the same Yoast SEO analyses in Google Docs

5: Makes doing site maintenance easier

If working on your site is turning into a day job, you might need some help! Premium makes site maintenance easier. For one, Premium comes with a stale cornerstone content finder that reminds you to update your most important content.

Another tool that helps you work on your pages is the redirect manager. Whenever you make changes to pages or URLs, this tool makes sure to add a redirect for you. All you have to do is say where the new URL needs to lead. With the redirect manager, you can also fix your 404 errors in no time. No developer necessary. It’s so helpful that 58% of Premium users praise the redirect manager as the best feature in Yoast SEO Premium!

6: Helpful tools to build a great site structure

Building a solid site structure is one of the quickest routes to success. Making your content easily accessible to users and search engines helps them both make sense of your site. Yoast SEO Premium comes with a number of tools that help you build relevant links that can build a solid foundation for your site structure. Our plugin comes with internal linking blocks, an orphaned content finder and a targeted internal linking suggestion tool.

With the internal linking suggestions, relevant content will automatically be suggested while you’re writing your new content. There’s no need to remember that all those posts are pages!

But don’t just take our word for it, here’s what Andrew Evans from Intellifluence says about the internal linking tool:

While the free Yoast SEO plugin offers many great features, the Premium version takes things to the next level. The internal linking suggestions feature ensures our blog is organized in a cohesive manner. It also ensures that link equity passes to other posts. This feature alone saves a tremendous amount of time as the plugin suggests links as we write. As the site grows, this feature only becomes more valuable! If you’ve ever tried to develop an interlinking strategy for an established blog, you’ll know exactly what I mean…

Andrew Evans

7: An advanced language analysis that makes writing more natural

Yoast SEO is famous for its SEO and readability analyses — a.k.a. the colored traffic lights. The feedback these analyses give you helps you produce a great piece of content that adheres to a range of SEO best practices. This works splendidly, but Premium makes this process a lot more natural and flexible.

Premium has a very smart feature called word forms support. This innovative language analysis looks not only at the exact match of the focus keyphrase you enter but also at all the grammatical forms of that word. If you use, for instance, “decoration”, we will find word forms like “decorated” and “decorates” in your text as well, just like Google does. The words don’t even have to be in the same order when your focus keyphrase consists of more than one word.

8: Use synonyms and related keyphrases in your text to make it richer

Search engines get smarter every day, and context is key in SEO. They use the context in which a keyword appears to determine what a text is about. Synonyms and related terms, therefore, are more important than ever. In the free version of Yoast SEO, you can only add a single focus keyphrase. The plugin uses this to help you optimize your post. Yoast SEO Premium has more tricks up its sleeve, making it a much smarter solution. What is that?

Well, you can add a number of synonyms and related keyphrases to your post. By using these, you can make your content come alive. The Premium analysis makes sure that you use these synonyms and related keyphrases correctly in your post. Awesome, right? You can even use the Semrush integration to gather data and trends about your related keyphrases. Premium users can add the related keyphrases Semrush uncovers for you to their post with a single mouse click.

9: Boost AI visibility while maintaining control

Yoast SEO introduces AI-focused features such as llms.txt and AI bot blockers to protect your site’s content and maintain data privacy. The llms.txt file helps AI tools understand your site’s structure and important content. Meanwhile, the AI bot blocker feature lets you safeguard your intellectual property with a simple toggle, preventing AI bots from scraping your content for training purposes. This ensures that your valuable information remains secure and under your control.

10: 24/7 access to our world-class support team

What if you run into issues with the plugin? It would be good if you could contact a real person to help you figure out what the problem is. Luckily, if you sign up for Yoast SEO Premium, you get just that: Premium support. Our helpful support staff is available around the clock to get you up and running in no time.

An incredible bonus: free access to Yoast SEO Academy

Every Yoast SEO Premium subscription comes with complimentary access to Yoast SEO Academy. This is a big deal. We don’t just provide you with the number one WordPress SEO plugin to help you do well in search engines — we also supply many hours of instructional material. We offer several of our courses free of charge to get you started with the basics. But when you sign up for Yoast SEO Premium, you get access to all our SEO courses! Learn about Yoast SEO, SEO copywriting, keyword research, structured data, ecommerce SEO, and many other topics related to SEO!

Invest in Yoast SEO Premium: it pays off!

You see, there are many good reasons to get a Yoast SEO Premium subscription today. A Premium subscription can save you lots of time and gives you access to incredible tools that make working on your site easier and more fun. Plus, you’ll get unrestricted access to Yoast SEO Academy for hundreds of hours of SEO training. And, of course, you get to contact our support team if you should ever run into a problem.

How much does Yoast SEO Premium cost?

You can buy Yoast SEO Premium for $118.80 excluding VAT per year, or €118.80/£118.80 per year, depending on where you are in the world. For this, you not only get Yoast SEO Premium, all the additional plugins like Local SEO and Video SEO, and its awesome tools, but you also get a year of support, updates, and access to all our Yoast SEO Academy courses. Check out all of our products here.

Get Yoast SEO Premium now!

Convinced? Make sure to grab your copy!

Buy Yoast SEO Premium now!

Unlock powerful features and much more for your WordPress site with the Yoast SEO Premium plugin!

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

The post Yoast SEO free vs Premium: why upgrading is worth it appeared first on Yoast.

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How AI is shaping brand perception, and what you can do about it

What does ChatGPT say about your brand? Or Perplexity, Gemini, or Claude? As AI agents emerge alongside traditional search engines as the starting point of discovery, the way they perceive and present your brand can directly shape customer trust and buying decisions. These models don’t know your brand the way people do. They learn it from the web, from structured data, citations, reviews, and the context you’ve built across digital touchpoints. The result: AI isn’t just reflecting your brand; it’s actively influencing how audiences experience it!

This article explores how AI is reshaping brand perception and, more importantly, what you can do about it.

How AI perceives your brand

AI doesn’t just read your brand; it interprets it. Instead of scanning isolated keywords, AI systems build a contextual map of who you are, what you offer, and how the world perceives you. This understanding comes from a combination of techniques like knowledge graphs, entity linking, relationship mapping, and sentiment analysis.

Here is a brief overview of different technologies that AI agents use for understanding brands:

Knowledge graphs

Image source: TechTarget

Knowledge graphs are structured databases that represent entities (like brands, products, or people) and the relationships between them. For AI, they serve as a kind of brand blueprint, linking Apple not only to ‘smartphones’ and ‘laptops’ but also to competitors like Samsung, product lines like iPhone, and audiences like ‘tech-savvy young adults.’ By connecting these dots, AI understands a brand’s position within a larger ecosystem.

Entity linking

Image source: Ontotext

Entity linking ensures that when AI encounters a brand reference – whether in a news article, review, or social post – it knows exactly which brand is being discussed. A mention of ‘Apple’s new iPhone’ doesn’t just get read as text; AI links ‘Apple’ and ‘iPhone’ to their knowledge graph entries, capturing the context that this is about Apple’s smartphone launch, not fruit.

Relationship mapping

Beyond direct links, AI maps relationships between entities to uncover patterns. This could mean identifying which product features resonate with certain customer segments or surfacing how a brand is associated with trends like sustainability or innovation. Relationship mapping highlights not only who is connected to a brand, but how.

Sentiment and perception analysis

AI also analyzes tone and sentiment across reviews, forums, social platforms, and media. These signals reveal whether people talk about a brand positively, negatively, or neutrally, and in what context. Over time, these insights shape how AI interprets a brand’s reputation and credibility.

Personalization and content alignment

Finally, AI uses this brand understanding to personalize consumer interactions and even generate content aligned with a brand’s tone and values. The more consistent the data and signals a brand sends out, the clearer its identity becomes in AI systems.

Taken together, these technologies mean AI doesn’t just see a brand as a logo or a tagline. It sees a web of relationships, perceptions, and behaviors, continuously updated in real time. AI understands brands through both what they say about themselves and how the world engages with them, but it often weighs the latter more heavily.

Overall, if we set aside the technical layers, the bigger picture is this: AI doesn’t see a brand as just a logo, tagline, or marketing claim. Instead, it constructs meaning from the countless interactions, mentions, and connections that exist around the brand. Every review, conversation, and association adds another layer to how AI perceives brand equity.

Your brand’s story was never yours alone; customers, communities, and competitors have always shaped it. What’s changing is that AI amplifies those influences in real time.

The new gatekeepers: LLMs & generative search

For decades, search has been the front door of the internet, the place where customers first discovered, compared, and connected with brands. Ranking high on Google meant visibility, trust, and traffic, and much of the brand strategy was built around that dynamic. But that front door is changing.

Today, large language models (LLMs) and generative AI are reshaping discovery itself. Search is no longer just a list of blue links you can optimize against. Instead, AI compresses, summarizes, and reinterprets content on behalf of the user. It’s faster, more convenient, and increasingly becoming the default way people search.

In fact, by 2028, organic search traffic could decline by 50% or more as consumers rely more heavily on generative AI-powered search.

This shift marks a turning point: discovery is moving from traditional search engines toward AI-driven experiences. And nowhere is this transformation clearer than in the evolution of search engines themselves.

Read more: LLM SEO optimization techniques (including llms.txt)

Let’s understand this shift and its different aspects in detail.

From traditional search to AI-driven discovery

In the pre-AI era, search meant competing for blue links. Your content carries not just keywords but also your voice, tone, and brand identity. That visibility gave businesses some control over how they were discovered.

Now, discovery is expanding beyond links into AI-generated answers, instant summaries, and conversational results. These systems don’t just point to your site; they synthesize information from multiple sources and deliver it directly to the user.

This shift means people are no longer ‘clicking through’ in the same way; they’re expecting instant, conversational results. It’s faster, more convenient, and quickly becoming the default search experience.

Search engines’ evolution into generative platforms

Search engines themselves are fuelling this transition. Google is the clearest example. It remains the dominant force in search, with usage rising more than 20% in 2024 and still delivering ~373X more searches than ChatGPT. But the nature of that search is changing.

Image source: SparkToro
  • AI Overviews, launched in May 2024, now appear in more than half of searches. Instead of users scrolling down to organic results, they see synthesized AI summaries right at the top.
  • AI Mode, rolling out widely in 2025, makes the entire experience conversational, with generative responses as the default surface, not the list of links below.
  • Behind all of this is Gemini, the model family that deepens Google’s ability to parse context, language, and intent, reshaping what it means for content to be ‘visible.’
An example of a search in Google AI Mode

For brands, this creates a paradox. Your content may be seen more often through impressions, but clicks decline because users often don’t need to leave the search results page. Instead of optimizing just for rankings, success depends on whether your content can deliver highly specific, immediately useful insights that AI wants to pull into its answers.

Recognizing this shift early opens up space to differentiate, while many competitors are still optimizing for the old playbook.

Read more: How to optimize content for AI LLM comprehension using Yoast’s tools

The branding challenges of AI mediation

While generative search improves user experience, it strips away brand nuance. AI blends multiple sources, compresses messaging, and removes design and visual branding, leading to tone flattening. A playful coffee brand known for witty puns and bold design may simply appear as ‘a coffee retailer offering various blends’. Stripped of its energy and personality.

There’s also the problem of sentiment drift. Because models rely on historical data, they may surface outdated or dominant narratives that don’t reflect your current positioning. A hotel that has rebranded into a luxury wellness retreat may still show up as ‘a budget accommodation option,’ simply because older reviews carry more weight in training data.

The risk here is bigger than being misrepresented; it’s being misunderstood at scale. In the AI-driven discovery era, your brand isn’t just competing for attention; it’s competing for interpretation.

Read more: What AI gets wrong about your site, and why it’s not your fault

What shapes your brand’s AI profile

AI agents build brand profiles not just from your owned content but from the network of signals surrounding it, some of which you can influence directly, others that linger long after you’ve moved on.

Everything mentioned till now clearly shows that AI agents’ answers for your brand depend on several factors, like:

  • Structured data and schema usage provide machines with a clear blueprint of who you are, what you offer, and why it matters. Without this scaffolding, your content risks being flattened into something indistinguishable.
  • Citations in authoritative sources act like trust anchors. When established publications, industry bodies, or credible researchers reference your brand, AI models absorb those signals and treat them as validation.
  • Consistency of context, making sure your brand name, description, and expertise align across platforms, ensures that fragmented or contradictory mentions don’t dilute your identity in AI summaries.
  • Depth and authority of content matter more than sheer volume. AI is tuned to favor content that demonstrates expertise and perspective, not just keyword density.
  • Geographical and personalization cues influence how your brand is profiled in specific markets or for specific user types. For instance, a brand may appear as a local leader in one geography and an emerging player in another.
  • Reputation signals like reviews, press coverage, and forum discussions shape how AI remembers your brand. Unlike a campaign you can sunset, these signals persist in training data.A software tool that fixed its early bugs, for example, might still be labelled unreliable in AI-generated summaries because forum complaints from years ago remain part of the record.

Together, these factors reveal an uncomfortable truth: your brand’s AI profile is not solely in your control. It is co-authored by every structured markup, citation, review, and discussion thread tied to your name.

And that’s exactly why the next step isn’t just about visibility, it’s about equity. If machines are going to carry your reputation forward, then the real question becomes: how do you actively shape and protect that equity in the AI era?

What you can do about it: building brand equity in the AI era

If AI is going to summarize your brand for users, the challenge is no longer just getting to page one; it’s making sure those summaries capture the right story. That means shifting your strategy from chasing rankings to actively shaping the signals AI pulls from.

Here’s how to start:

Audit how AI describes your brand

Don’t assume your website is the only source AI is pulling from. Ask ChatGPT, Perplexity, or Gemini to ‘Describe [Your Brand]’ every quarter. Track how those descriptions change, whether they reflect your current positioning, and if old baggage is still showing up. This gives you a baseline for what’s working and what needs fixing.

For deeper insights, tools like Yoast AI Brand Insights go a step further, tracking mentions, sentiment, and visibility across AI assistants so you can see exactly how your brand is represented and take control of the narrative.

Keep ‘anchor’ content fresh

Pages like your About, product introductions, and service overviews are disproportionately influential. Refresh them regularly with clear, keyword-rich descriptors that reinforce your current narrative. These are often the first things AI models latch onto, so make sure they reflect today’s positioning, not yesterday’s.

Infuse brand storytelling into content

Generic descriptions fade in summaries; unique stories stick. Instead of ‘We sell camping gear,’ write ‘We help families turn weekends into campfire stories.’ Language that’s memorable, metaphorical, or emotionally charged has a better chance of surviving AI compression and carrying your brand identity with it.

Experiment beyond traditional blog posts

AI models ingest more than just written blogs. Case studies, explainer videos, podcasts, interviews, or even forum contributions can influence how your expertise gets profiled. A varied content mix increases the likelihood that your brand is represented in different contexts and query types.

Work on visibility across multiple touchpoints

Don’t let your footprint be limited to your own site. Citations in industry publications, guest appearances, reviews, and even thoughtful participation in online discussions expand the sources AI relies on. The broader your presence, the harder it is for AI to miss you.

Always think about intent and context

AI-powered discovery isn’t keyword stuffing; instead, it’s intent recognition. Structure your content around the problems your audience is trying to solve, not just the queries you want to rank for. When your answers consistently match user intent, AI is more likely to position you as relevant and authoritative.

Invest in tools that guide AI to your brand

Unlike search engines, AI tools don’t crawl your full site; they only scan small pieces of content in real time. This means important details can be missed or outdated. That’s where Yoast SEO’s llms.txt feature helps.

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)

This feature automatically creates a file that acts as a map for AI assistants, pointing them to your most important, cleanly structured content. No setup required. By doing this, you give LLMs a better chance of representing your business accurately in their answers.

The future of brand perception

We’ve entered a new era of discovery. Customers aren’t just scanning pages; they’re trusting AI-generated answers to shape their perception of your brand. That shift comes with both risk and opportunity.

On one hand, AI assistants can strip away the nuance, tone, and ownership brands that brands once held over how they’re presented. On the other hand, they offer a chance to reach audiences in more natural, context-rich ways than ever before, if you prepare for it.

The path forward isn’t about chasing rankings alone. It’s about ensuring your brand is understood, accurately represented, and consistently visible across this new AI-powered landscape. That means building content that survives summarization, experimenting beyond traditional formats, and guiding AI to the information that matters most about you.

But awareness is only the first step; you also need visibility into how AI tools are currently describing and interpreting your brand.

That’s where Yoast AI Brand Insights comes in. With AI visibility scores, sentiment tracking, and real-time monitoring of mentions across tools like ChatGPT, Gemini, and Perplexity, you’ll finally have a clear picture of how your brand lives inside AI answers, and how to shape it.

The future of brand perception isn’t written by you alone. It’s written by the AI that your customers trust. The question is: will you leave that story to chance, or take control of it?

👉 [Join the waitlist for Yoast AI Brand Insights] and be among the first to shape how AI sees your brand.

The post How AI is shaping brand perception, and what you can do about it appeared first on Yoast.

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Product page SEO: 5 things to improve

Having great product pages is important for your sales. After all, it’s where people decide to click that buy button. Besides optimizing your product pages for user experience, you also want to make sure these pages work for your SEO. You might think this is obvious. That’s why we’ll show you a few less obvious elements of product page SEO in this post. And we’ll explain why it’s so important to take these things into account. Let’s go!

1. The basics of product page SEO

First things first: a product page on an online store is a page too. This means that all the SEO things that matter for your content pages matter for your product pages as well. Of course, there’s a lot more to product page SEO. But for now, this will be your basic optimization. Tip: If you offer not-so-exciting products on your site, you may want to read our post on SEO for boring products.

Let’s start with the basics.

A great title

Try to focus on the product name and include the manufacturer’s name, if applicable. In addition, if your product is a small part of a larger machine (screw, tube), for example, you should include the SKU as well. People might search for that specifically.

A proper and unique product description

While it might be tempting to use the same description as the product’s manufacturer, you really shouldn’t. That description might be found on hundreds of websites, which means it’s duplicate content and a sign of low quality for your website (to Google). Remember, you want to prevent duplicate content at all times!

Now, you might think: “But all my other content (content pages, category pages, blog) is unique!” However, if the content on hundreds of product pages isn’t unique, then the majority of your website’s content still won’t be up to par. So make time to create unique content! And if you need help, the Yoast WooCommerce SEO plugin comes with product-specific content and SEO analysis that helps you produce great product descriptions.

An inviting meta description

A product page usually contains a lot of general information, like the product’s dimensions or your company’s terms of service. To avoid Google using that unrelated text in a meta description, you want to add a meta description to your product pages. It’s arguably even more important than adding one to your content pages!

Next, try to come up with unique meta descriptions. This can be difficult sometimes. You might come up with a sort of template, where you only change the product name per product. That’s okay to start with. But ideally, all your meta descriptions should be unique. Yoast SEO has various AI features that will help you with this.

Pick a great and easy-to-remember URL

We recommend using the product name in the URL. However, keep it short and simple so that it is still readable for site visitors.

Add high-quality and well-optimized images with proper ALT text

Include the product name in at least the main product image. This will help you do better in visual search. Also, don’t forget video — if applicable.

Focus on your product page UX

Last but not least: UX, or user experience. This is an important step because it’s all about making your product pages as user-friendly as possible. Plus, it’s an important part of holistic SEO. There are many parts to UX, which is why we wrote a post with product page UX examples. Give it a read!

Read more: Write great product descriptions with WooCommerce SEO »

WooCommerce SEO simplified

Enhance product visibility and drive more traffic to your online shop.

Get Yoast WooCommerce SEO Only $178.80 / year (ex VAT)

2. Add structured data for your products and get rich results

Structured data is an essential part of a modern SEO strategy. You simply can’t do without structured data for your product pages anymore, because they help your product page stand out. For example, there is a specific Product schema that helps you get highlighted search results, so-called rich results. These are great for your site’s visibility, and they can also increase your click-through rate! And if you mark up customers’ reviews with Review structured data, they will show up in the search results. Seeing those beautiful stars underneath a product page will convince people they should check out your site!

Another reason to add it is to manage customers’ expectations. Your visitors will know your price up front and that the product is still in stock. How’s that for user experience?

Search engines and AI/LLMs will understand your page better

Structured data is also important for your product page SEO because the major search engines came up with this markup, not the W3C consortium. Google, Bing, Yahoo, and Yandex agreed upon this markup, so they could identify product pages and all the product elements and characteristics more easily. Why? So they could a) understand these pages a lot better and b) show you rich snippets like this:

That’s a lot of info in the search results, right?

The Product schema tells the search engine more about the product. It could include characteristics like product description, manufacturer, brand, name, dimensions, and color, but also the SKU we mentioned earlier. The Offer schema includes more information on price and availability, like currency and stock. It can even include something called priceValidUntil to let search engines know that the price offer is for a limited time only.

Add structured data with Yoast SEO

Boost your website’s presence with powerful schema structured data features, included for free with Yoast SEO.

Options to add structured data for product page SEO

Schema.org has a lot of options, but only a limited set of properties are supported by search engines. For instance, look at Google’s page on product page structured data to see what search engines expect in your code and what they can do with it.

This is why you want to add Schema.org data for product page SEO: It’s easier to recognize for Google, and it makes sure to include important extras in Google already. If you have a WooCommerce shop, our WooCommerce SEO plugin takes care of a lot of this stuff behind the scenes.

Keep reading: Rich results, structured data and Schema: a visual guide to help you understand »

A preview of how your product might look in Google thanks to structured data

3. Add real reviews

Reviews are important. In fact, 74% of consumers say that they check reviews on at least two sites before buying anything online or locally. Although not everyone trusts online reviews, many do, so they can be very helpful.

If you are a local company, online reviews are even more important. Most reviews tend to be extremely positive, but it might just be the negative reviews that give a better sense of what is going on with a company or product. In addition, getting awesome testimonials is another way of showing your business means business.

Leading Dutch online store Coolblue gives consumers a lot of options to make relevant and useful reviews of the products they buy

Try to get your customers to leave reviews, then show the reviews on your product page. Do you get a negative review? Contact the writer, find out what’s wrong, and try to mitigate the situation. Maybe they can turn their negative review into a positive one. Plus: You’ve gained new insights into your work.

If you’re not sure how to get those ratings and reviews, check out our blog post: how to get ratings and reviews for your business. And don’t forget to mark up your reviews and ratings with Review and Rating schema so search engines can pick them up and show rich results on the search results pages.

4. Make your product page lightning fast

Nobody enjoys waiting, especially when browsing on a mobile device. Many shoppers are now using their phones to make purchases, so speed on your product pages is crucial. Visitors expect instant access to content, and search engines reward that expectation. Compress images, implement responsive design, and streamline scripts to enhance load times. Regularly test your mobile layout to identify and fix problems before they impact your users. Prioritizing mobile performance not only satisfies your customers but also aligns with search engine preferences, potentially boosting your SEO rankings and increasing traffic.

Remember, a fast, mobile-friendly site is a win-win for everyone involved. To get you started, here’s a post about how to improve your Core Web Vital scores.

5. User test your product page

Looking at numbers in Google Analytics, Search Console, or other analytical tools can give you insight into how people find and interact with your page. These insights can help you improve the performance of a page even more. But there’s another way to ensure that your product page is as awesome as it can be: user testing. There are also many ways to get more value from site visitors with A/B testing.

How user testing can help you

Testers can find loads of issues for you, such as terrible use of images (including non-functioning galleries), bad handling of out-of-stock products, or inaccurate shipping and return information, which can lead to trust issues. Now, you might be thinking: Surely, my website doesn’t have those issues! But you’d be surprised.

In their Product Page UX research project, the Baymard Institute found that:

“The high-level benchmark results show that only 49% of e-commerce sites have an overall ‘decent’ or ‘good’ UX performance for their product pages, while 51% of sites have ‘mediocre’ or worse product page implementations. On the extreme ends of performance, only a couple of sites had a very ‘poor’ Product Page UX performance that failed to align with commonly observed user behavior in our large-scale PDP testing. This is a fortunate shift upward from 2021, which previously had 4% of sites with below ‘poor’ performances. At the other end of the scale, there aren’t any sites with an overall ‘Perfect’ or ‘“’State of the Art’ product page implementation (unchanged since 2021).

You can read this fascinating study on their Product Page UX site.

The Baymard report has loads of insights into the most common errors seen on product pages

While you compare your product pages to external user research, don’t forget to do your own user testing! Doing proper research will give you eye-opening results that you probably wouldn’t have found yourself.

Bonus: Build trust and show people your authenticity

Getting a stranger to buy something on your site involves a lot of trust. Someone needs to know you are authentic before handing you their hard-earned money, right? Google puts a lot of emphasis on the element of trust — It’s all over their famous Search Quality Raters Guidelines. The search engine tries to evaluate trust and expertise by looking at online reviews, the accolades a site or its authors receive, and much more.

Brand perception in AI and LLMs

AI search engines and LLMs also assess these trust factors to shape how your brand is presented. They analyze reviews, schema, and overall credibility to produce an accurate portrayal. A trustworthy online presence can positively influence how these systems perceive and convey your brand to users.

This is why it’s so important that your About Us and Customer Service pages are in order. Make sure people can easily find your contact information, information about returns and shipping, payment, privacy, etc. This will build trust with your customers. So, don’t forget!

Social proof is another way to build trust with your customers. Adding social proof to your product pages can significantly influence buying decisions. Display customer reviews, testimonials, and ratings to build trust and demonstrate real-life experiences. Include trust badges, like security symbols or industry awards, to boost credibility. Encourage happy customers to share photos or videos of your products and showcase this content on your website. These elements help assure visitors that your products are both credible and valued by others.

Conclusion: Be serious about your product page SEO

If you’re serious about optimizing your product page, you shouldn’t focus on regular SEO and user experience alone. You’ll have to dig deeper into other aspects of your product pages. For instance, you could add the Product and Offer Schema, so Google can easily index all the details about your product and show these as rich results in the search results. In addition, you should make your product pages fast, add user reviews, and try to enhance your website’s trustworthiness. And don’t forget to test everything you do!

Need a helping hand? Be sure to check out our ecommerce SEO training course. Learn what ecommerce SEO entails, how to optimize your site, and boost your online presence. Want to get your products ranking in the shopping search results? We’ll tell you how. Start your free trial lesson today! Full access to Yoast SEO Academy is included in Yoast SEO Premium, which also includes all other plugins — including Local SEO for optimizing your performance in local search.

Check out our overview of product page must-haves

To help you stay on top of your product pages, we created a PDF that you can use to optimize your product pages. Most of what’s discussed in this blog post can be found in the PDF, plus more tips! Just click on the image to go to the PDF and download it.

preview product page must haves
Click on the image to download the PDF

Read on: 7 ways to improve product descriptions in your online store »

The post Product page SEO: 5 things to improve appeared first on Yoast.

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Google Ads adds loyalty features to boost shopper retention

Google Shopping Ads - Google Ads

Google is rolling out new loyalty integrations across Google Ads and Merchant Center, giving retailers tools to highlight member-only pricing and shipping benefits to their most valuable customers.

How it works:

  • Personalized annotations display member-only discounts or shipping benefits in both free and paid listings.
  • A new loyalty goal in Google Ads helps retailers optimize budgets toward high-value shoppers, adjusting bids to prioritize lifetime value.
  • Sephora US saw a 20% lift in CTR by surfacing loyalty-tier discounts in personalized ads.

Why we care. With 61% of U.S. adults saying tailored loyalty programs are the most compelling part of a personalized shopping experience (according to Google), retailers face pressure to prove value beyond discounts.

By surfacing member-only perks directly in search and shopping results, retailers can boost engagement from their most valuable customers and optimize spend toward higher lifetime value, not just single conversions. It’s a way to tie loyalty programs directly to ad performance — and win more share of wallet from existing shoppers.

The big picture. Loyalty features are Google’s latest move to keep retail advertisers invested in its ecosystem — positioning search and shopping as not just discovery channels, but retention engines. Expect more details at Google’s Think Retail event on Sept. 10.

Read more at Read More

AI tool adoption jumps to 38%, but 95% still rely on search engines

AI tools vs traditional search

More than 1 in 5 Americans now use AI tools heavily – but traditional search engines remain dominant, with usage holding steady at 95%, according to new clickstream data from Datos and SparkToro.

By the numbers:

  • AI tools: 21% of U.S. users access AI tools like ChatGPT, Claude, Gemini, Copilot, Perplexity, and Deepseek 10+ times per month. Overall adoption has jumped from 8% in 2023 to 38% in 2025.
  • Search engines: 95% of Americans still use Google, Bing, Yahoo, or DuckDuckGo monthly, with 87% considered heavy Google users – up from 84% in 2023.
  • Growth trends: AI adoption is slowing. Since September 2024, no month has shown more than 1.1x growth. By contrast, search volume per user has slightly increased year-over-year.

The big picture: Despite the hype around AI replacing Google, the data seems to show the opposite. When people adopt AI tools, their Google searches also rise, SparkToro found.

Yes, but. Are there any truly “traditional search engines” left? Things get a bit messy when talking about “traditional search engines” versus the “AI tools” examined here, because all search engines now have AI baked in:

  • Google is a traditional search engine (or, perhaps more accurately, an AI search engine with a legacy search experience that’s clearly moving in the direction of AI Overviews and AI Mode), and Gemini is Google’s AI tool. Plus, Google’s traditional search data is being used by ChatGPT.
  • Traditional search engine Bing has its own AI tool, Copilot, and is OpenAI’s partner for ChatGPT Search, and feeds DuckDuckGo’s results.

Why we care. This data once again indicates that it isn’t AI vs. search; it’s AI plus search. Heavy AI users are also heavy searchers, meaning Google traffic declines are more about zero-click answers than AI cannibalization.

The report. New Research: 20% of Americans use AI tools 10X+/month, but growth is slowing and traditional search hasn’t dipped

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Google releases August 2025 spam update

Google released its August 2025 spam update today, the company announced at 12:05 p.m. This is Google’s first announced algorithm update since the June 2025 core update. It is Google’s first spam update of 2025 and the first since December.

Timing. Google called this a “normal spam update” and it will take a “few weeks” to finish rolling out.

The announcement. Google announced:

  • “Today we released the August 2025 spam update. It may take a few weeks to complete. This is a normal spam update, and it will roll out for all languages and locations. We’ll post on the Google Search Status Dashboard when the rollout is done.”

Previous spam updates. Before today, Google’s last spam update was released Dec. 19 and finished rolling out Dec. 26; it was more volatile than the June 2024 spam update, which was released June 20, 2024 and completed rolling out June 27, 2024.

Why we care. This is the first Google algorithm update since the June 2025 core update. It’s unclear what type of spam this update is targeting, but if you see any ranking or traffic changes in the next few weeks, it could be due to this update.

Read more at Read More

ChatGPT’s answers came from Google Search after all: Report

ChatGPT Google unmasking

Multiple tests have suggested ChatGPT is using Google Search. Well, a new report seems to confirm ChatGPT is indeed using Google Search data.

  • OpenAI quietly used (and may still be using) a Google Search scraping service to power ChatGPT’s answers on real-time topics like news, sports, and finance, according to The Information.

The details. OpenAI used SerpApi, an 8-year-old scraping firm, to extract Google results.

  • Google has reportedly long tried to block SerpApi’s crawler, though it’s unclear how effective those efforts have been.
  • Other SerpApi customers reportedly include Meta, Apple, and Perplexity.

Zoom out. This revelation contrasts with OpenAI’s public stance that ChatGPT search relies on its own crawler, Microsoft Bing, and licensed publisher data.

Meanwhile. OpenAI CEO Sam Altman recently dismissed Google Search, saying:

  • “I don’t use Google anymore. I legitimately cannot tell you the last time I did a Google search.” 

Well, based on this news, it seems like he probably is using Google Search all the time within his own product.

Why we care. Google’s search index remains the foundation of online discovery – so much so that even its biggest AI search rival appears to be using it to partially power ChatGPT. This is yet another reminder that SEO isn’t going anywhere just yet. If Google’s results are valuable to OpenAI, they remain essential for driving visibility, traffic, and business outcomes.

The report. OpenAI Is Challenging Google—While Using Its Search Data (subscription required)

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Historic recurrence in search: Why AI feels familiar and what’s next

Historic recurrence in search- Why AI feels familiar and what’s next

Historic recurrence is the idea that patterns repeat over time, even if the details differ.

In digital marketing, change is the only constant.

Over the last 30 years, we’ve seen nonstop shifts and transformations in platforms and tactics.

Search, social, and mobile have each gone through their own waves of evolution. 

But AI represents something bigger – not just another tactic, but a fundamental shift in how people research, evaluate, and buy products and services.

Estimates vary, but Gartner projects that AI-driven search could account for 25% of search volume by the end of 2026.

I suspect the true share will be much higher as Google weaves AI deeper into its results.

For digital marketers, it can feel like we need a crystal ball to predict what’s next. 

While we don’t have magical foresight, we do have the next best thing: lessons from the past.

This article looks back at the early days of search, how user behavior evolved alongside technology, and what those patterns can teach us as we navigate the AI era.

The early days: Wild and wonderful queries

If you remember the early web – AltaVista, Lycos, Yahoo, Hotbot – search was a free-for-all. 

People typed in long, rambling queries, sometimes entire sentences, other times just a few random words that “felt” right.

There were no search suggestions, no “people also ask,” and no autocorrect. 

It was a simpler time, often summed up as “10 blue links.”

Google Search - 10 blue links

Searchers had to experiment, refine, and iterate on their own, and the variance in query wording was huge.

For marketers, that meant opportunity. 

You could capture traffic in all sorts of unexpected ways simply by having relevant pages indexed.

Back then, SEO was, in large part, about one thing: existing in the index.

Dig deeper: A guide to Google: Origins, history and key moments in search

Google’s rise: From exploration to efficiency

Anyone working in digital marketing in the early 2000s will remember. 

From Day 1, Google felt different. The quality of its results was markedly better.

Then came Google Suggest in 2008, quietly changing the game. 

Suddenly, you didn’t have to finish typing your thought. Google would complete it for you, based on the most common searches.

Research from Moz and others at the time showed that autocomplete reduced query length and variance. 

People defaulted to Google’s suggestions because it was faster and easier.

This marked a significant shift in our behavior as searchers. We moved from sprawling, exploratory queries to shorter, more standardized ones.

It’s not surprising. When something can be achieved with less effort, human nature drives us toward the path of least resistance.

Once again, technology had changed how we search and find information.

Mobile, voice, and the second compression

The shift to mobile accelerated this compression.

Tiny keyboards and on-the-go contexts meant people typed as little as possible.

Autocomplete, voice input, and “search as you type” all encouraged brevity.

At the same time, Google kept rolling out features that answered questions directly, creating a blended, multi-contextual SERP.

The cumulative effect? Search behavior became more predictable and uniform.

For marketers running Google Ads or tracking performance in Google Analytics and Search Console, this shift came with another challenge: less data. 

Long-tail keywords shrank, while most traffic and budget concentrated on a smaller set of high-volume terms.

Once again, our search behavior – and the insights we could glean from it – had evolved.

Zero-click search and the walled garden

By the late 2010s, zero-click searches were on the rise. 

Google – and even social platforms – wanted to keep users inside their ecosystems.

More and more questions were answered directly in the search results. 

Search got smarter, and shorter queries could deliver more refined results thanks to personalization and past interactions.

Google started doing everything for us.

Search for a flight? You’d see Google Flights.

A restaurant? Google Maps. 

A product? Google Shopping. 

Information? YouTube

You get the picture.

For businesses built on organic traffic, this shift was disruptive. 

But for users, it felt seamless – arguably a better experience, even if it created new challenges for optimizers.

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Quality vs. brevity

This shift worked – until it didn’t. 

One common complaint today is that search results feel worse

It’s a complicated issue to unpack. 

  • Have search results actually gotten worse? 
  • Or are the results as good as ever, but the underlying sites have declined in quality?

It’s tricky to call. 

What is certain is that as traffic declined, many sites got more aggressive – adding more ads, more pop-ups, and sneakier lead gen CTAs to squeeze more value from fewer clicks.

The search results themselves have also become a bewildering mix of ads, organic listings, and SERP features. 

To deliver better results from shorter queries, search engines have had to guess at intent while still sending enough clicks to advertisers and publishers to keep the ecosystem running.

And as traffic-starved publishers got more desperate, user experience took a nosedive. 

Anyone who has had to scroll through a food blogger’s life story – while dodging pop-ups and auto-playing ads – just to get to a recipe knows how painful this can be.

It’s this chaotic landscape that, in part, has driven the move to answer engines like ChatGPT and other large language models (LLMs). 

People are simply tired of panning for gold in the search results.

The AI era: From compression back to conversation

Up to this point, the pattern has been clear: the average query length kept getting shorter.

But AI is changing the game again, and the query-length pendulum is now swinging sharply in the opposite direction.

Tools like ChatGPT, Claude, Perplexity, and Google’s own AI Mode are making it normal to type or speak longer, more detailed questions again.

We can now:

  • Ask questions instead of searching for keywords. 
  • Refine queries conversationally. 
  • Ask follow-ups without starting over. 

And as users, we can finally skip the over-optimized lead gen traps that have made the web a worse place overall.

Here’s the key point: we’ve gone from mid-length, varied queries in the early days, to short, refined queries over the last 12 years or so, and now to full, detailed questions in the AI era.

The way we seek information has changed once more.

We’re no longer just searching for sources of information. We’re asking detailed questions to get clear, direct answers.

And as AI becomes more tightly integrated into Google over the coming months and years, this shift will continue to reshape how we search – or, more accurately, how we question – Google.

Dig deeper: SEO in an AI-powered world: What changed in just a year

AI and search: Google playing catch-up

Google was a little behind the AI curve.

ChatGPT launched in late 2022 to massive buzz and unprecedented adoption.

Google’s AI Overviews – frankly underwhelming by comparison – didn’t roll out until mid-2024. 

After launching in the U.S. in mid-June and the U.K. in late July 2025, Google’s full AI Mode is now available in 180 countries and territories around the world.

Now, we can ask more detailed, multi-part questions and get thorough answers – without battling through the lead gen traps that clutter so many websites.

The reality is simple: this is a better system.

This is progress.

Want to know the best way to boil an egg – and whether the process changes for eggs stored in the fridge versus at room temperature? Just ask.

Google will often decide if an AI Overview is helpful and generate it on the fly, considering both parts of your question.

  • What is the best way to boil an egg?
  • Does it differ if they are from the fridge?

The AI Overview answers the question directly. 

And if you want to keep going, you can click the bold “Dive deeper in AI Mode” button to continue the conversation.

Dive deeper in AI Mode

Inside AI Mode, you get streamlined, conversational answers to questions that traditional search could answer – just without the manual trawling or the painfully over-optimized, pop-up-heavy recipe sites.

From shorter queries to shorter journeys

Stepping back, we can see how behavior is shifting – and how it ties to human nature’s tendency to seek the path of least resistance.

The “easy” option used to be entering short queries and wading through an increasingly complex mix of results to find what you needed.

Now, the path of least resistance is to put in a bit more effort upfront – asking a longer, more refined question – and let the AI do the heavy lifting.

A search for the best steak restaurant nearby once meant seven separate queries and reviewing over 100 sites. That’s a lot of donkey work you can now skip.

It’s a subtle shift: slightly more work up front, but a far smoother journey in return.

This change also aligns with a classic computing principle: GIGO – garbage in, garbage out. 

A more refined, context-rich question gives the system better input, which produces a more useful, accurate output.

Historic recurrence: The pattern revealed

Looking back, it’s clear there’s a repeating cycle in how technology shapes search behavior.

The early web (1990s)

  • Behavior: Long, experimental, often clumsy queries.
  • Why: No guidance, poor relevance, and lots of trial-and-error.
  • Marketing lesson: Simply having relevant content was often enough to capture traffic.

Google + Autocomplete (2000s)

  • Behavior: Queries got shorter and more standardized.
  • Why: Google Suggest and smarter algorithms nudged users toward the most common phrases.
  • Marketing lesson: Keyword targeting became more focused, with heavier competition around fewer, high-volume terms.

Mobile and voice era (2010s–early 2020s)

  • Behavior: Even shorter, highly predictable queries.
  • Why: Tiny keyboards, voice assistants, and SERP features that answered questions directly.
  • Marketing lesson: The long tail collapsed into clusters. Zero-click searches rose. Winning visibility meant optimizing for snippets and structured data.

AI conversation era (2023–present)

  • Behavior: Longer, natural-language queries return – now in back-and-forth conversations.
  • Why: Generative AI tools like ChatGPT, Gemini, and Perplexity encourage refinement, context, and multi-step questions.
  • Marketing lesson: It’s no longer about just showing up. It’s about being the best answer – authoritative, helpful, and easy for AI to surface.

Technology drives change

The key takeaway is that technology drives changes in how people ask questions.

And tactically, we’ve come full circle – closer to the early days of search than we’ve been in years.

Despite all the doom and gloom around SEO, there’s real opportunity in the AI era for those who adapt.

What this means for SEO, AEO, LLMO, GEO – and beyond

The environment is changing.

Technology is reshaping how we seek information – and how we expect answers to be delivered.

Traditional search engine results are still important. Don’t abandon conventional SEO.

But now, we also need to optimize for answer engines like ChatGPT, Perplexity, and Google’s AI Mode.

That means developing deeper insight into your customer segments and fully understanding the journey from awareness to interest to conversion. 

  • Talk to your customers. 
  • Run surveys. 
  • Reach out to those who didn’t convert and ask why. 

Then weave those insights into genuinely helpful content that can be found, indexed, and surfaced by the large language models powering these new platforms.

It’s a brave new world – but an incredibly exciting one to be part of.

Read more at Read More

How to tell if Google Ads automation helps or hurts your campaigns

How to tell if Google Ads automation helps or hurts your campaigns

Smart BiddingPerformance Max, and responsive search ads (RSAs) can all deliver efficiency, but only if they’re optimizing for the right signals.

The issue isn’t that automation makes mistakes. It’s that those mistakes compound over time.

Left unchecked, that drift can quietly inflate your CPAs, waste spend, or flood your pipeline with junk leads.

Automation isn’t the enemy, though. The real challenge is knowing when it’s helping and when it’s hurting your campaigns.

Here’s how to tell.

When automation is actually failing

These are cases where automation isn’t just constrained by your inputs. It’s actively pushing performance in the wrong direction.

Performance Max cannibalization

The issue

PMax often prioritizes cheap, easy traffic – especially branded queries or high-intent searches you intended to capture with Search campaigns. 

Even with brand exclusions, Google still serves impressions against brand queries, inflating reported performance and giving the illusion of efficiency. 

On top of that, when PMax and Search campaigns overlap, Google’s auction rules give PMax priority, meaning carefully built Search campaigns can lose impressions they should own.

A clear sign this is happening: if you see Search Lost IS (rank) rising in your Search campaigns while PMax spend increases, it’s likely PMax is siphoning traffic.

Recommendation

Use brand exclusions and negatives in PMax to block queries you want Search to own. 

Segment brand and non-brand campaigns so you can track each cleanly. And to monitor branded traffic specifically, tools like the PMax Brand Traffic Analyzer (by Smarter Ecommerce) can help.

Dig deeper: Performance Max vs. Search campaigns: New data reveals substantial search term overlap

Auto-applied recommendations (AAR) rewriting structure

The issue

AARs can quietly restructure your campaigns without you even noticing. This includes:

  • Adding broad match keywords. 
  • “Upgrading” existing keywords to broader match types.
  • Adding new keywords that are sometimes irrelevant to your targeting.

Google has framed these “optimizations” as efficiency improvements, but the issue is that they can destabilize performance. 

Broad keywords open the door to irrelevant queries, which then can spike CPA and waste budget.

Recommendation

First, opt out of AARs and manually review all recommendations moving forward. 

Second, audit the changes that have already been made by going to Campaigns > Recommendations > Auto Apply > History. 

From there, you can see what change happened on what date, which allows you to go back to your campaign data and see if there are any performance correlations. 

Dig deeper: Top Google Ads recommendations you should always ignore, use, or evaluate

Modeled conversions inflating numbers

The issue

Modeled conversions can climb while real sales or MQLs stay flat. 

For example, you may see a surge in reported leads or purchases in your ads account, but when you look at your CRM, the numbers don’t match up. 

This happens because Google uses modeling to estimate conversions where direct measurement isn’t possible. 

If Google doesn’t have full tracking, it fills gaps by estimating conversions it can’t directly track, based on patterns in observable data. 

When left unchecked, the automation will double down on these patterns (because it assumes they’re correct), wasting budget on traffic that looks good but won’t convert.

Recommendation

Tell the automation what matters most to your business. 

Import offline or qualified conversions (via Enhanced Conversions, manual uploads, or CRM integration). 

This will ensure that Google optimizes for real revenue and not modeled noise.

When automation is boxed in: Reading the signals

Not every warning in Google means automation is failing. 

Sometimes the system is limited by the goals, budget, or inputs you’ve set – and it’s simply flagging that.

These diagnostic signals help you understand when to adjust your setup instead of blaming the algorithm.

Limited statuses (red vs. yellow)

The issue

A Limited status doesn’t always mean your campaign is broken. 

  • If you see a red Limited label, this means your settings are too strict. That could mean that your CPA or ROAS targets are unrealistic, your budget is too low, etc. 
  • Seeing a yellow Limited label is more of a caution sign. It’s usually tied to low volume, limited data, or the campaign is still learning.

Recommendation

If the status is red, loosen constraints gradually: raise your budget and ease up CPA/ROAS targets by 10–15%. 

If the status is yellow, don’t panic. This is Google’s version of telling you that they could use more money, if possible, but it’s not vital to your campaign’s success.

Responsive search ads (RSAs) inputs

The issue

RSAs are built in real-time from the headlines and descriptions you have already provided Google. 

At a minimum, advertisers are required to write 3 headlines with a maximum of 15 (and up to 4 descriptions). The fewer the assets you give the system, the less flexibility it will have. 

On the other hand, if you’re running a small budget and give the RSAs all 15 headlines and 4 descriptions, there is no way Google will be able to collect enough data to figure out which combinations actually work.

The automation isn’t failing with either. You’ve either given it too little information or too much with too little spending. 

Recommendation

Match asset volume to the budget allocated to the campaign. 

  • If you’re unsure, aim to write between 8-10 headlines and 2-4 descriptions.
  • If each headline/description isn’t distinct, don’t use it. 

Conversion reporting lag and attribution issues

The issue

Sometimes, Google Ads reports fewer conversions than your business actually sees. 

This isn’t necessarily an automation failure. It’s often just a matter of when the conversion is counted. 

By default, Google reports conversions on the day of the click, not the day the actual conversion happened. 

That means if you check performance mid-week, you might see fewer conversions than your campaign has actually generated because Google attributes them back to the click date. 

The data usually “catches up” as lagging conversions are processed.

Recommendation

Use the Conversions (by conversion time) column alongside the standard conversion column.

Conversions (by conversion time) column

This helps you separate true performance drops from simple reporting delays. 

If discrepancies persist beyond a few days, investigate the tracking setup or import accuracy. Just don’t assume automation is broken just because of timing gaps.

Get the newsletter search marketers rely on.


Where to look in the Google Ads UI

Automation leaves a clear trail within Google Ads if you know where to look. 

Here are some reports and columns to help spot when automation is drifting.

Bid Strategy report: Top signals 

The issue

The bid strategy report shows some of the signals Smart Bidding relies on when there is enough data. 

The “top signals” can sometimes make sense, and at other times, they can be a bit misleading. 

If the algorithm relies on weak signals (e.g., broad search themes and a lack of first-party data), its optimizations will be weak, too.

Bid Strategy report: Top signals 

Recommendation

Make checking your Top Signals a regular activity. 

If they don’t align with your business, fix the inputs. 

  • Improve conversion tracking.
  • Import offline conversions.
  • Reevaluate search themes.
  • Add customer/remarketing lists.
  • Expand your negative keyword list(s). 

Impression share metrics

The issue

When a campaign underdelivers, it’s tempting to assume automation is failing, but looking at Impression Share (IS) metrics tends to reveal the real bottleneck. 

By looking at Search Lost IS (budget), Search Lost IS (rank), and Absolute Top IS together, you can separate automation problems from structural or competitive ones.

How to use IS metrics as a diagnostic tool.

  • Budget problem
    • High Lost IS (budget) + low Lost IS (rank): Your campaign isn’t struggling. It just doesn’t have enough budget to run properly.
    • Recommendation: Raise the budget or accept capped volume.
  • Targets too aggressive
    • High Lost IS (rank) + low Absolute Top IS: If your Lost IS (rank) is high and your budget is adequate, your CPA/ROAS targets are likely too aggressive, causing Smart Bidding to underbid in auctions.
    • Recommendation: Loosen targets gradually (10-15%).

Scripts to keep automation honest

Scripts give you early warnings so you can step in before wasted spend piles up.

Anomaly detection

  • The issue: Automation can suddenly overspend or underspend when conditions in the marketplace change, but you often won’t notice until reporting lags.
  • Recommendation: Use an anomaly detection script to flag unusual swings in spend, clicks, or conversions so you can investigate quickly.

Query quality (N-gram analysis)

  • The issue: Broad match and PMax can drift into irrelevant themes (“free,” “jobs,” “definition”), wasting budget on low-quality queries.
  • Recommendation: Run an N-gram script to surface recurring poor-quality terms and add them as negatives before automation optimizes toward them.

Budget pacing

  • The issue: Google won’t exceed your monthly cap, but daily spend will be uneven. Pacing scripts help you spot front-loading.
  • Recommendation: A pacing script shows you how spend is distributed so you can adjust daily budgets mid-month or hold back funds when performance is weak.

Turning automation into an asset

Automation rarely fails in dramatic ways – it drifts. 

Your job isn’t to fight it, but to supervise it: 

  • Supply the right signals.
  • Track when it goes off course.
  • Step in before wasted spend compounds.

The diagnostics we covered – impression share, attribution checks, PMax insights, and scripts – help you separate real failures from cases where automation is simply following your inputs.

The key takeaway: automation is powerful, but not self-policing. 

With the right guardrails and oversight, it becomes an asset instead of a liability.

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Global expansion and hyperlocal focus redefine the next chapter of retail media networks by DoorDash

Retail media networks are projected to be worth $179.5 billion by 2025, but capturing share and achieving long-term success won’t hinge solely on growing their customer base. With over 200 retail media networks now competing for advertiser attention, the landscape has become increasingly complex and crowded. The RMNs that stand out will be those taking a differentiated approach to meeting the evolving needs of advertisers.

The industry’s concentration creates interesting dynamics. While some platforms have achieved significant scale, nearly 70% of RMN buyers cite “complexity in the buying process” as their biggest obstacle. That tension, between explosive growth and operational complexity, is forcing the industry to evolve beyond traditional approaches.

As the landscape matures, which strategies will define the next wave of growth: global expansion, hyperlocal targeting, or both?

The evolution of retail media platforms

To understand where the industry is heading, it’s worth examining how successful platforms are addressing advertisers’ core challenges. Lack of measurement standards across platforms continues to frustrate advertisers who want to compare performance across networks. Manual processes dominate smaller networks, making campaign management inefficient and time-consuming.

At the same time, most retailers lack the digital footprint necessary for standalone success. This has created opportunities for platforms that can solve multiple problems simultaneously: standardization, automation, and scale.

DoorDash represents an interesting case study in this evolution. The platform has built its advertising capabilities around reaching consumers at their moment of local need across multiple categories. With more than 42 million monthly active consumers as of December 2024, DoorDash provides scale and access to high-intent shoppers across various categories spanning restaurants, groceries and retail.

The company’s approach demonstrates how platforms can address advertiser pain points through technology. DoorDash’s recent platform announcement showcases this evolution: the company now serves advertisers with new AI-powered tools and expanded capabilities. Through its acquisition of ad tech platform Symbiosys, a next-generation retail media platform, brands can expand their reach into digital channels, such as search, social, and display, and retailers can extend the breadth of their retail media networks.

Global expansion meets local precision

International expansion presents both opportunities and challenges for retail media networks. Europe’s retail media industry is projected to surpass €31 billion by 2028,. This creates opportunities for networks that can solve the technology puzzle of operating across multiple geographies.

The challenge lies in building platforms that work seamlessly across countries while maintaining local relevance. International expansion requires handling different currencies, regulations, and cultural contexts—capabilities that many networks struggle to develop.

DoorDash’s acquisition of Wolt illustrates how platforms can achieve global scale while maintaining local connections. The integration enables brands to manage campaigns across Europe and the U.S. through a single interface—exactly the kind of operational efficiency that overwhelmed advertisers seek.

The combined entity now operates across more than 30 countries, with DoorDash and Wolt Ads crossing an annualized advertising revenue run rate of more than $1 billion in 2024. What makes this expansion compelling isn’t just the scale—it’s how the integration maintains neighborhood-level precision across diverse geographies.

Wolt has transformed from a food delivery platform into what it describes as a multi-category “shopping mall in people’s pockets.”

The hyperlocal advantage: context beats demographics

Here’s what’s really changing the game: the shift from demographic targeting to contextual precision. Privacy regulations favor contextual targeting over behavioral tracking, but that’s not the only reason smart networks are going hyperlocal.

Location-based intent signals provide dramatically higher conversion probability than traditional demographics. Real-time contextual data—weather patterns, local events, proximity to fulfillment—influences purchase decisions in immediate, actionable ways that broad demographic targeting simply can’t match.

DoorDash built its entire advertising model around this insight, reaching consumers at the exact moment of local need across multiple categories. The platform provides scale and access to high-intent shoppers with contextual precision. A recent innovation that exemplifies this approach is Dayparting for CPG brands, which enables advertisers to target users in their local time zones—a level of time-based precision that distinguishes hyperlocal platforms from broader retail media networks.

In one example, Unilever applied Dayparting to focus on late-night and weekend windows for its ice cream campaigns, aligning ad delivery with peak demand periods. Over a two-week period, 77% of attributed sales were new-to-brand, demonstrating the power of contextual timing in driving incremental reach.

Major brands, including Unilever, Coca-Cola, and Heineken, utilize both DoorDash and Wolt platforms for hyperlocal targeting, proving the model is effective for both endemic and non-endemic advertisers seeking neighborhood-level precision.

Technology evolution: measurement and automation

The technical requirements for next-generation retail media networks extend far beyond basic advertising capabilities. Self-serve functionality has become standard for international geographies—not because it’s trendy, but because manual campaign management doesn’t scale across dozens of countries with different currencies, regulations, and cultural contexts.

Cross-country campaign management requires unified dashboards that manage complexity while maintaining simplicity for advertisers. Automation isn’t optional anymore; it’s necessary to compete with established players who’ve built machine learning into their core operations.

But here’s what’s really transforming measurement: new attribution methodologies that go beyond traditional ROAS. When platforms can integrate fulfillment data with advertising exposure, they enable real-time performance tracking that connects ad spend to actual business outcomes rather than just clicks and impressions.

Progress on standardization continues through IAB guidelines addressing measurement consistency, alongside industry pushes for technical integration standards. The challenge lies in balancing standardization with differentiation—networks need to offer easy integration and consistent measurement while maintaining unique value propositions.

In a move toward addressing advertisers’ need for measurement consistency, DoorDash recognized that restaurant brands valued both click and impression-based attribution for their sponsored listing ads, and recently introduced impression-based attribution and reporting in Ads Manager. This has enabled restaurant brands to gain a deeper understanding of performance and results driven on DoorDash.

Global technology challenges add another layer of complexity: multi-currency transactions, local payment methods, regulatory compliance across countries, and cultural adaptation while maintaining platform consistency. These aren’t afterthoughts for international platforms, they’re core competencies that determine success or failure.

Industry outlook: consolidation and opportunity

Retail media is heading toward consolidation, but not in the way most people expect. Hyperlocal networks are positioned to capture share from undifferentiated RMNs that compete solely on inventory volume. Geographic specialization is becoming a viable alternative to traditional scale-focused approaches.

Simultaneously, community impact measurement is gaining importance for brand strategy. Marketers are discovering that advertising dollars spent on local commerce platforms create multiplier effects—supporting neighborhood businesses and strengthening local economies in ways that traditional e-commerce advertising doesn’t achieve.

The networks that understand this dynamic, that can offer global platform capabilities with genuine local industry expertise, are the ones positioned to define retail media’s next chapter. Success requires technology integration that enables contextual and location-based targeting, plus measurement solutions that prove incrementality beyond traditional metrics.

The path forward

As retail media networks mature, success lies not in choosing between global scale and local relevance, but in achieving both simultaneously. The DoorDash-Wolt combination provides a compelling blueprint, demonstrating how technology platforms can enable international expansion while deepening neighborhood-level connections.

For marketers navigating this evolution, the fundamental question shifts from “where should we advertise?” to “how can we reach consumers at their moment of need?” Networks that answer this effectively—through global reach, hyperlocal precision, or ideally both, will write retail media’s next chapter.Interested to learn more about DoorDash Ads? Get started today.

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