This post was sponsored by Moz. The opinions expressed in this article are the sponsor’s own.

The scope of modern keyword strategy is expansive and crosses many disciplines. As Google leans further into user experience and user signals as part of its ranking algorithms, research, execution, and testing must become more interwoven and refined.

If your keyword strategy is underperforming and you’re struggling to drive traffic, rankings, or even onsite conversions, your keyword strategy could be missing critical components.

The following is a look at common mistakes and how to address them. You’ll see screenshots and examples of how you can solve keyword strategy issues and improve workflows during the keyword research stage using the premium keyword research features in Moz Pro, but you can get started free with  Moz’s Keyword Explorer tool.

Mistake #1: Failing To Target Intent

You can’t just pick a keyword you want to rank for and move straight into writing a page. What you want to target is the first part of a complex equation, of which the user is the most important part.

Intent can be expressed as a set of questions:

• Why is the user searching for the query?
• What does the user expect to find?
• What do search engines deliver to meet this intent?

You must answer these questions to build content that fits neatly between the expectations of searchers and the search engines. Whether you’re a beginner in keyword research or you’re a professional SEO who wants to brush up on the fundamentals, you must understand the relationship between queries and search intent. Content that does not satisfy intent will result in a poor user experience, which leads to negative engagement signals, which will hurt your ability to rank.

You must understand the relationship between queries and search intent. Content that does not satisfy intent will result in a poor user experience, which leads to negative engagement signals.

If enough of your content is misaligned with user intent, it could impact your entire site, as you won’t be seen as trustworthy or authoritative.

If individual pages or your keyword strategy as a whole is underperforming, this is one of the first things you should audit because a mismatch between search intent and your content will kill those pages, whether they’re old or new.

You also need to keep in mind that intent changes. This can be due to one-off events, seasonal changes, or algorithm updates.

Here are some examples of intent:

• Purchase intent: the user is actively looking for a product to buy.
• Comparison intent: the user is shopping around and comparing products.
• Informational or educational intent: The user wants to learn something.

Intents can be quite complicated, and you’ll need to rely on your own audience research to get granular. But a tool can help speed up the process by showing you the general intent of a keyword and what is currently ranking on the SERP.

Explore by Keyword in Moz Pro makes it easy to see keyword intent at a glance for individual keywords and a whole batch of keyword suggestions. Let’s look at the keyword [best convertible car seat].

You can probably already guess the intent, and the tool confirms that it’s a commercial intent keyword. This means users are looking to compare products and features to find the best suited for them. Remember, this is based on the results in the SERPs, so it’s giving you some more intel into what Google expects a user’s intent to be, which we’ll discuss more in a bit.

Screenshot of Moz Pro

As you go through the research process, you can use a combination of factors such as Difficulty and intent to discover related keywords worth pursuing to bolster your strategy.

Mistake #2: Not Conducting Competitor And On-SERP Research

When you’re in the weeds of data tables and strategy, it’s easy to forget one of the most simple and critical rules in SEO.

Most of the information you need is on the SERP.

When you evaluate the SERP of a given keyword, you can gain a lot of information with the right approach. But you’re going to need to get good at reading between the lines.

You can use the existing pages on a SERP to understand how well the query is being satisfied and what competitors are and are not doing. If the SERP has many high-quality pages, you can learn a lot from the strategies your competitors use. If there are pages that you consider low-quality, based on your knowledge of the subject matter, then you’ve identified an opportunity.

So, to properly research SERPs, you need a few skills:

• Understanding of design and UX to identify suboptimal user experiences or understand why some pages may be outperforming.
• A deep understanding of the subject matter covered by the keyword so that you can identify which pages provide trustworthy, high-quality information.
• Knowledge of the user intent behind a query so that you can match the intent with the experience that the ranking pages deliver.

From there, you can evaluate the quality of the pages and choose where to focus your efforts. If you’re lacking information or you can’t find a good angle of attack, then start looking at similar SERPs for related keywords or related intents. If you can find a SERP with sufficiently different results but related search intent, you can compare and contrast.

Going back to our research related to [best convertible car seat], let’s take a look at the SERP. We can do it right inside Moz’s tool:

Screenshot from Moz Pro

Yikes! This is going to be a tough one. We’ve got Reddit and Wirecutter on there.

Luckily, there are options. Using the “questions” tab in the “keyword suggestions” tool, you can discover questions that searchers ask relatively frequently. Some of them may have the potential for a related keyword strategy.

Screenshot from Moz Pro

Even though the head term will be difficult to rank for, you can see a lot of “informational” intent related to this search. This is an opportunity to build trust with highly motivated consumers.

Mistake #3: Not Organizing Your Research

If you do keyword research intermittently or only at the beginning of campaigns, you might be missing important opportunities to refine your strategies.

Keyword research needs to be checked and refined as your strategy changes and the SERPs get updated.

It’s critical that you set yourself up for success when you begin a new campaign or strategy. You don’t want to do a ton of work and leave it in a disorganized state because, eventually, you will need to update your pages and reassess the strategy behind them. You can save yourself a lot of time by preparing for this eventuality and setting up a strategy that’s easy to jump back into.

Building keyword groups and lists help you understand how pages fit into the broader categorization of your website. It’s also a good idea to use a tool that tracks your progress so that when you return to strategy, you can see the past performance of pages at a glance.

With Keyword Lists in Moz Pro you can to upload your own sheet file or build a list by typing it out. Once the list is in the system, you get a ton of insights about the keywords both individually and in aggregate, as you can see from the screenshot of the sample list below.

Screenshot from Moz Pro

Mistake #4: Not Building Entity And Topic Maps

The way you organize information is critical at two levels.

The first is on the page. How you present information, in what order, and in what format is critical to the experience of a page. If you can match this well with intent, you’ll provide users with a good experience and improve conversion rates.

The other level is site-wide. You must build a content and keyword strategy around topics and entities. This is how you build a content library that’s friendly to both users and advanced search algorithms. Building entity maps correctly helps you compete in an AI-heavy environment because you’re speaking the language of AI algorithms that work by connecting entities together through context.

Building these maps of context between topics also helps you to build a robust strategy and discover opportunities your competitors may have missed. Every page you add to a broader topic is an opportunity to reinforce your authority, succeed in a unique SERP, and transfer that SEO power to your other pages through internal linking.

Moz’s “similar SERPs” tool comes in handy here. With Moz Pro, search by keyword and filter by Similar SERPs. Tada! By analyzing the top-ranking pages for your target keyword you’ll see other keywords those competing URLs ranked for. With this list of new keywords, you can identify opportunities to strategically expand your content based on that topical analysis. It’s a great way to see where there’s overlap in SERPs.

Screenshot from Moz Pro

Screenshot from Moz Pro

So stop missing out on opportunities your competitors are capitalizing on. With the advanced keyword research features in Moz Pro you can streamline your research process, enabling deeper keyword analysis and smarter strategies. Prioritize intent, enhance user experience, increase conversions, and rank for the queries you need.

Stop missing out on traffic! Unlock the power of Keyword Explorer with over 500 million traffic-driving keywords.

Start your free trial today and fix your keyword strategy for real results.

Image Credits

Featured Image: Image by Moz. Used with permission.

In-Post Image: Images by Moz. Used with permission.

For some years now (ever since Google Merchant Center was introduced in 2010), ecommerce advertisers have been working with product feeds.

It’s historically been a complex and often fragile process, but thanks to the introduction of Google Merchant Center Next, we have some new tools at our fingertips.

Here’s a look at how things are changing with Next.

The History Of Google Merchant Center

Back in the very beginning, we remember having to download CSV files from the website with all product information, and embarking on a long process of cleaning up and formatting the data so that it could be manually uploaded into Google Merchant Center (GMC).

In the early days, before policies became more strict, you could even use Merchant Center to advertise anything from repair services to round-the-world gap year vacations!

But in time, GMC became far more sophisticated (and also more restricted). Along with increased restrictions came the ease of use. Uploading data became much easier and more stable.

Eventually, plugins and connectors began doing most of the job for you, then platforms like Shopify got native integrations, and now with the advent of Google Merchant Center Next, you almost don’t need feeds at all!

Common Complaints About GMC

For most of the past 14 years of Merchant Center history, you’ve likely heard a few bits of common wisdom repeated ad nauseam:

Optimize your shopping feeds inside of GMC! Keep your Google categories accurately assigned inside of GMC! Add your metadata inside of GMC! Fill out all the boxes in GMC!

The world is slowly changing, and now, with GMC Next, you don’t have to make these changes within the GMC interface.

The changes need to happen on the website. While feeds won’t totally go away overnight (and neither will the need to optimize products), Google Merchant Center Next is ushering in a new feed-less era.

Announced at Google Marketing Live 2023, Merchant Center Next actually hasn’t taken hold as rapidly as expected. Even over a year after its announcement, most but not all of our client accounts have shifted over.

GMC Next started rolling out for new users first, but Google has stated the full rollout should be completed sometime in 2024. Whether this is the actual date is yet to be seen.

What Is Google Merchant Center Next?

The core differentiator with Merchant Center Next is the simplification of website verification and the automatic population of product feeds from your website. This means that Google will scrape product information, pricing, imagery, and more directly from your site.

Additionally, it has integrated a new feature called Product Studio that allows you to use AI to update or change your product images and offers more comprehensive performance insights.

Many marketers had a negative gut reaction to the announcement of Next, but our entire team at Discosloth was actually pretty excited about this development.

Feed management (and especially the involvement of any third-party integrations, connectors, and tools) has always been a bit clunky, so the removal of any friction is a welcome feature.

While you can still use Shopify to upload your product data, many people have found it to be more difficult with some products not being uploaded properly. As it turns out, feeds have technically gone away, but in a way, they have actually just been renamed to Data Sources.

Screenshot from Google Merchant Center Next, August 2024

It appears that product feeds, as we know them, might be going away.

This doesn’t mean that product data management will become obsolete; rather, it indicates a shift in how this data is handled within the Merchant Center Next ecosystem.

The Mindset Change

I ultimately think that removing feeds is a fantastic approach because it shifts the mindset of marketers. Rather than focusing on incremental metadata optimization on hidden feeds, it will instead encourage advertisers to update & improve the actual listings on the actual site.

Rather than just making sure endless attributes are filled out in the backend, it means that the actual website and associated metadata will need to be correctly optimized. This eliminates double work and conflicting data.

When the website itself is the primary focus, it has positive effects on performance for all channels, like organic or social – not just paid.

While many paid marketers have been focused only on optimizing products and images within the Merchant Center, without paying any attention to the website listings, now may be the time to change that approach.

Thanks to this, the website owners may start seeing a better overall conversion rate for the entire website, across all channels.

This is a great step in the right direction. Contrary to what many naysayers think about the onset of AI and generative automation, I’m a fan of taking away the grunt work from marketing and handing it all to the robots.

A more automated approach to feed management will undoubtedly grant us a lot more bandwidth to make actual strategy and content decisions on the products themselves.

While we’ve been seeing more comprehensive data on product performance appearing in Google Merchant Center over the last few years, now may be the time to dig a little bit deeper.

While GA4 has widely become useless for advanced data analysis, the new GMC Next allows us to see website traffic for both paid and organic traffic from product listings, review competition and visibility, and get better data on the best-selling products and new trends.

Perhaps the feature I like the most: comparing the prices of your stock-keeping units (SKUs) vs. competitors. This is the kind of data that has been classically underused.

Instead of a misguided focus on inserting our favorite keywords into descriptions, we can finally focus on the quality and competitiveness of your products.

Screenshot from Google Merchant Center Next, August 2024

Taking Merchant Center Beyond Optimization

Performance Max and Demand Gen campaign types have given us some new tools and strategies to use in ecommerce advertising, but it’s become harder to see granular data on where your ads are appearing, detailed performance metrics, and perhaps most notably, which keyword terms & specific audiences these campaigns are appearing for.

Many advertisers are afraid that Google Merchant Center Next may be on a similar path of removing even more granular data and making it even harder for advertisers to be specific in our ad targeting.

But so far, most of the early complaints people had when Next was introduced have already been fixed. We got access back to supplemental feeds, we can now make bulk changes (even though it’s not as easy as it used to be) and we can once again appeal any incorrectly disapproved products.

Of course SKUs and product feeds need to be optimized, but this shouldn’t be anything out of the ordinary.

Optimizing this should be an assumed baseline for any ecommerce storefront.

Merchant Center Next, as we’ve found, is most effectively used for tactics far beyond what the old Merchant Center offered. Some of the most important tactics we now use include things like getting insights on specific SKUs to make sure you always hold in inventory, and diving deep into competitive visibility and pricing in order to massively increase sales.

More resources: 

Featured Image: N Universe/Shutterstock

Google officially launched AI Overviews in the U.S. on May 14, 2024. Three months later, they announced that AI Overviews was rolled out to six more countries: the UK, India, Japan, Indonesia, Mexico, and Brazil.

Is SEO dead and should you panic? Or is everything a big hoo-ha and there’s nothing to worry about?

Here’s everything we know about Google’s AI Overviews to date:

Google aims to answer the query directly within the SERPs, with links to webpages for further research. The easiest way to think about them is that they are featured snippets on steroids.

Originally named Search Generative Experience (SGE), AI Overviews is part of Google’s response to the accelerated rise of generative AI.

• 10 May 2023 — Google announces the Search Generative Experience (SGE) experiment
• 25 May 2023 — Google opens access to SGE for users who signed up for the waitlist.
• 22 March 2024 — Google starts testing AI Overviews in the main Google Search results, even if you had not opted into SGE.
• 14 May 2024 — Google officially launches AI Overviews for the U.S. Google also launches a new ‘Web’ filter for users who want only text-based webpages in search results.
• 24 May 2024 — AI Overviews come under fire for giving dangerous and wrong answers. For example, it recommended using non-toxic glue to give pizza sauce more tackiness, eating at least one small rock a day, and drinking urine to pass kidney stones quickly.
• 30 May 2024 — Google responds to the brouhaha by explaining how it intends to improve AI Overviews.
• 15 Aug 2024 — Google launches AI Overviews for the UK, India, Japan, Indonesia, Mexico, and Brazil. It also begins showing AI Overviews for Incognito mode and users who are not signed in. Additionally, it launches the ability to “save” a specific AI Overview and tests adding links to relevant web pages directly within the text of AI Overviews.
• 23 Aug 2024 — Google’s John Mueller confirms that AI Overviews are affected by core updates.

In September 2023, Google filed a patent for their AI Overview called “Generative summaries for search results”.

Thanks to Rich Sanger, who looked at the patent, we have an idea of how Google’s AI Overviews work:

1. Query submission: You enter a search query.
2. Understanding the query: Google uses a variety of LLMs to understand the context and intent of your query.
3. Gathering content: The system retrieves relevant documents, including web pages, articles, images, and videos related to your query.
4. Processing additional content: In addition to the immediate search results, Google considers content from related searches and information others found helpful under similar query circumstances.
5. Generating a summary: An LLM combines all this information to generate a helpful response to your query.
6. Dynamic and context-aware responses: The AI adapts its responses based on the specific context of each query submission. If queries are repeated or similar in different contexts, the AI adjusts the summaries it provides.
7. User interaction and learning: Google learns from how users interact with the search results. If certain responses are consistently overlooked in favor of others, or if user clicks suggest a preference, the AI modifies future responses to align more closely with user behavior.
8. Enhancing accuracy and relevance: The AI continually updates its understanding based on new information and interactions, which helps it to provide more accurate and contextually relevant responses over time.

The most important question, at least for SEOs, is how the system selects the sources. There are three main criteria:

1. Query-dependent measures: The system assesses how relevant each potential source document is to the specific query. This includes positional ranking and relevance to the query’s location and language.
2. Query-independent measures: It then assesses search result documents for things like selection rate across multiple queries, trustworthiness, overall popularity, and freshness.
3. User-dependent measures: The system also considers the user’s profile and past interactions including recent searches and recent non-query interactions.

I highly recommend reading Rich Sanger’s article on how AI Overviews work, as it goes into deep detail on the patent.

According to Sundar Pichai, the CEO of Google, AI has been transforming Google Search for years.

“When mobile came, we knew Google Search had to evolve a lot. We call it featured snippets, but for almost 10 years now you go to Google for many questions we kind of use AI to answer them. We call it web answers internally. … We’ve always answered questions where we can. But we always felt when people come and look for information. People, in certain cases, want answers but they also want the richness and the diversity of what’s out there in the world and it’s a good balance to be had and we’ve always I think struck that balance pretty well.”

Currently, Google still has the largest market share in the world. And the rise of other AI-based search engines has (so far) not made a dent on Google either.

The good news: You can block Google using the standard methods of noindexing your pages or using robots.txt. Bear in mind that this is a drastic measure, as it prevents Google from both showing your content in AI Overviews and the SERPs.

However, Google does provide an alternative method: ‘preview controls’, which are a way to tell Google not to provide a snippet in the SERPs or limit the amount of content that can be used.

Glenn Gabe ran an experiment to test whether Google would respect this.

The result? It did, but it took some time (and even a ping to Google’s John Mueller) for it to finally work. Regardless, it is an option if you want to opt out of AI Overviews.

Though there are ‘consequences’ (i.e. no search snippet), as Glenn Gabe discovered:

• AI Overviews continue to be volatile — A study from BrightEdge showed that the visibility of AI Overviews increased to 12% in July, only for it to fall to 7% by the end of the month.
• Informational keywords were most likely to have AI Overviews — A study from Flow Agency showed that for HR and workforce management keywords, top-of-the-funnel (TOFU) keywords were the most likely to have AI Overviews appear (24%). Comparatively, transactional keywords had AIOs appear only 5% of the time. This is corroborated by research done by SEOClarity.
• You’re more likely to be linked in an AI Overview if you rank high for the query — A study by Rich Sanger and Authoritas showed that 46.3% of the documents linked in the summaries were from the top organic search results for the exact match query. When related queries were added to the direct match queries, the percentage of links from both the direct match and related queries in the top search results increased to 60.4%. It also showed that a link ranked first has a 53% chance of being featured, while content ranked tenth has a 36.9% chance. This is in contrast to what we saw in January 2024, where Google often showed sources outside the top 10 search results.

Unfortunately for all of us, Google will not distinguish between AI Overviews and organic search in Google Search Console. They will lump all the impressions and clicks together.

So, if you’d like to track the visibility of AI Overviews for important queries, you’ll have to use third-party tools like ZipTie.

Bear in mind that AI Overviews are still volatile, appearing and disappearing for different keywords. Third-party tools may also struggle to keep up, considering that search queries will become more conversational and long-tailed.

Finally, the purpose of AI Overviews is to provide personalized summaries. This element will be missing when it comes to tracking, especially regarding linked sources.

Considering that Google seems to be aligning AI Overviews with organic results, your best bet is to continue following SEO best practices and aim to rank high on Google itself.

In fact, if we look at Rich Sanger’s recommendations from his latest study on AIOs, you’d find that it is essentially SEO basics:

In short, even though Google has now introduced AI Overviews, the fundamentals of SEO are still the same. You need to:

• Do keyword research
• Make content users want to see by matching search intent
• Ensure the content is comprehensive and fulfills E-E-A-T
• Build links

However, given that the overlap is still not 100%, it could suggest a potential avenue for ‘information gain’ to be rewarded. To put it in layman’s terms, Google wants to reward new information, not copycat content.

In fact, when Rich Sanger analyzed the patent, it suggested that Google was indeed looking for diversity:

“But understand that the AI Overview doesn’t only provide documents from the top sources for that query. It seeks out diversity. If the top-ranked content for that query is homogenous, it will move on to closely related queries. Earning top page rankings along with visibility in the AI Overview for targeted queries is the best case scenario.”

How can you add ‘information gain’ to your content? There are three ways:

• Experimentation — Go into the real world, test ideas, and collect data that no one else has.
• Experience — Actually experience the thing you’re making content about.
• Effort — Go beyond others and make better things or things that are more than words on a page.

Our Director of Content Marketing Ryan Law expands on each concept in his article on standing out from AI content. I highly recommend reading it.

Final thoughts

Did I miss anything? Let me know on X or LinkedIn.