This new series of articles focuses on working with LLMs to scale your SEO tasks. We hope to help you integrate AI into SEO so you can level up your skills.

We hope you enjoyed the previous article and understand what vectors, vector distance, and text embeddings are.

Following this, it’s time to flex your “AI knowledge muscles” by learning how to use text embeddings to find keyword cannibalization.

We will start with OpenAI’s text embeddings and compare them.

(*tokens can be considered as words words.)

But before we start, you need to install Python and Jupyter on your computer.

Jupyter is a web-based tool for professionals and researchers. It allows you to perform complex data analysis and machine learning model development using any programming language.

Don’t worry – it’s really easy and takes little time to finish the installations. And remember, ChatGPT is your friend when it comes to programming.

In a nutshell:

Download and install Python.
Open your Windows command line or terminal on Mac.
Type this commands pip install jupyterlab and pip install notebook
Run Jupiter by this command: jupyter lab

We will use Jupyter to experiment with text embeddings; you’ll see how fun it is to work with!

But before we start, you must sign up for OpenAI’s API and set up billing by filling your balance.

Once you’ve done that, set up email notifications to inform you when your spending exceeds a certain amount under Usage limits.

Then, obtain API keys under Dashboard > API keys, which you should keep private and never share publicly.

Now, you have all the necessary tools to start playing with embeddings.

Open your computer command terminal and type jupyter lab.
You should see something like the below image pop up in your browser.
Click on Python 3 under Notebook.

In the opened window, you will write your code.

As a small task, let’s group similar URLs from a CSV. The sample CSV has two columns: URL and Title. Our script’s task will be to group URLs with similar semantic meanings based on the title so we can consolidate those pages into one and fix keyword cannibalization issues.

Here are the steps you need to do:

Install required Python libraries with the following commands in your PC’s terminal (or in Jupyter notebook)

The ‘openai’ library is required to interact with the OpenAI API to get embeddings, and ‘pandas’ is used for data manipulation and handling CSV file operations.

The ‘scikit-learn’ library is necessary for calculating cosine similarity, and ‘numpy’ is essential for numerical operations and handling arrays. Lastly, unidecode is used to clean text.

Then, download the sample sheet as a CSV, rename the file to pages.csv, and upload it to your Jupyter folder where your script is located.

Set your OpenAI API key to the key you obtained in the step above, and copy-paste the code below into the notebook.

Run the code by clicking the play triangle icon at the top of the notebook.

This code reads a CSV file, ‘pages.csv,’ containing titles and URLs, which you can easily export from your CMS or get by crawling a client website using Screaming Frog.

Then, it cleans the titles from non-UTF characters, generates embedding vectors for each title using OpenAI’s API, calculates the similarity between the titles, groups similar titles together, and writes the grouped results to a new CSV file, ‘grouped_pages.csv.’

In the keyword cannibalization task, we use a similarity threshold of 0.9, which means if cosine similarity is less than 0.9, we will consider articles as different. To visualize this in a simplified two-dimensional space, it will appear as two vectors with an angle of approximately 25 degrees between them.

In your case, you may want to use a different threshold, like 0.85 (approximately 31 degrees between them), and run it on a sample of your data to evaluate the results and the overall quality of matches. If it is unsatisfactory, you can increase the threshold to make it more strict for better precision.

You can install ‘matplotlib’ via terminal.

And use the Python code below in a separate Jupyter notebook to visualize cosine similarities in two-dimensional space on your own. Try it; it’s fun!

I usually use 0.9 and higher for identifying keyword cannibalization issues, but you may need to set it to 0.5 when dealing with old article redirects, as old articles may not have nearly identical articles that are fresher but partially close.

It may also be better to have the meta description concatenated with the title in case of redirects, in addition to the title.

So, it depends on the task you are performing. We will review how to implement redirects in a separate article later in this series.

Now, let’s review the results with the three models mentioned above and see how they were able to identify close articles from our data sample from Search Engine Journal’s articles.

From the list, we already see that the 2nd and 4th articles cover the same topic on ‘meta tags.’ The articles in the 5th and 7th rows are pretty much the same – discussing the importance of H1 tags in SEO – and can be merged.

The article in the 3rd row doesn’t have any similarities with any of the articles in the list but has common words like “Tag” or “SEO.”

The article in the 6th row is again about H1, but not exactly the same as H1’s importance to SEO. Instead, it represents Google’s opinion on whether they should match.

Articles on the 8th and 9th rows are quite close but still different; they can be combined.

text-embedding-ada-002

By using ‘text-embedding-ada-002,’ we precisely found the 2nd and 4th articles with a cosine similarity of 0.92 and the 5th and 7th articles with a similarity of 0.91.

And it generated output with grouped URLs by using the same group number for similar articles. (colors are applied manually for visualization purposes).

For the 2nd and 3rd articles, which have common words “Tag” and “SEO” but are unrelated, the cosine similarity was 0.86. This shows why a high similarity threshold of 0.9 or greater is necessary. If we set it to 0.85, it would be full of false positives and could suggest merging unrelated articles.

text-embedding-3-small

By using ‘text-embedding-3-small,’ quite surprisingly, it didn’t find any matches per our similarity threshold of 0.9 or higher.

For the 2nd and 4th articles, cosine similarity was 0.76, and for the 5th and 7th articles, with similarity 0.77.

To better understand this model through experimentation, I’ve added a slightly modified version of the 1st row with ’15’ vs. ’14’ to the sample.

“14 Most Important Meta And HTML Tags You Need To Know For SEO”
“15 Most Important Meta And HTML Tags You Need To Know For SEO”

On the contrary, ‘text-embedding-ada-002’ gave 0.98 cosine similarity between those versions.

Here, we see that this model is not quite a good fit for comparing titles.

text-embedding-3-large

This model’s dimensionality is 3072, which is 2 times higher than that of ‘text-embedding-3-small’ and ‘text-embedding-ada-002′, with 1536 dimensionality.

As it has more dimensions than the other models, we could expect it to capture semantic meaning with higher precision.

However, it gave the 2nd and 4th articles cosine similarity of 0.70 and the 5th and 7th articles similarity of 0.75.

I’ve tested it again with slightly modified versions of the first article with ’15’ vs. ’14’ and without ‘Most Important’ in the title.

“14 Most Important Meta And HTML Tags You Need To Know For SEO”
“15 Most Important Meta And HTML Tags You Need To Know For SEO”
“14 Meta And HTML Tags You Need To Know For SEO”

So we can see that ‘text-embedding-3-large’ is underperforming compared to ‘text-embedding-ada-002’ when we calculate cosine similarities between titles.

I want to note that the accuracy of ‘text-embedding-3-large’ increases with the length of the text, but ‘text-embedding-ada-002’ still performs better overall.

Another approach could be to strip away stop words from the text. Removing these can sometimes help focus the embeddings on more meaningful words, potentially improving the accuracy of tasks like similarity calculations.

The best way to determine whether removing stop words improves accuracy for your specific task and dataset is to empirically test both approaches and compare the results.

Conclusion

With these examples, you have learned how to work with OpenAI’s embedding models and can already perform a wide range of tasks.

For similarity thresholds, you need to experiment with your own datasets and see which thresholds make sense for your specific task by running it on smaller samples of data and performing a human review of the output.

Please note that the code we have in this article is not optimal for large datasets since you need to create text embeddings of articles every time there is a change in your dataset to evaluate against other rows.

To make it efficient, we must use vector databases and store embedding information there once generated. We will cover how to use vector databases very soon and change the code sample here to use a vector database.

More resources: 

Featured Image: BestForBest/Shutterstock

AI is terraforming tech. The content and SEO ecosystem is undergoing a massive structural change.

Human-written content gains value faster for LLM training than for end consumers as the pure profit licensing deals between LLM developers and publishers show.

Publishers struggle to survive from digital subscriptions but get millions that go straight to their bottom line for providing training data.

Content platforms, social networks, SaaS companies and consumer apps coat their products with AI. A few examples:

Spotify DJ (AI-generated playlist).
AI Overview (AI answers in Google Search).
Instagram AI personas (celebrity AI chatbots).
Ebay’s magical listing (turn a photo into a listing).
Redfin Redesign (try interior designs on real house pictures).

The quality of machine-generated content (MGC) challenges human-generated content (HGC). I ran an experiment with my Twitter and LinkedIn followers: I asked them to choose which of two articles was written by a human and which by a machine – and they had to explain their answer.

Only a handful of people figured out that AI wrote both pieces. I intentionally framed the question in a leading way to see if people would challenge the setting or believe that one piece was written by a human if told so.

Not an isolated experiment: A survey of 1,900 Americans found that 63.5% of people can’t distinguish between AI content and human content.1
People seek help: Google search demand for [ai checker] has reached 100,000 in May 2024 (Glimpse).
Dark side: scammers use MGC to make money, as 77% of AI scam victims lost money.2

The quality level of LLMs pushes SEO work towards automating workflows and learning with AI, while writers will take content from good to great instead of zero to one.

Boost your skills with Growth Memo’s weekly expert insights. Subscribe for free!

System Builders

Clients, podcasters and panel hosts often ask me what skills SEOs need to build for the AI future. For a long time, my answer was to learn, stay open-minded and gain as much practical experience with AI as possible.

Now, my answer is SEOs should learn how to build AI agents and workflows that automate tasks. AI changes the way search works but also the way SEOs work.

AI + No-code Allows SEOs To Automate Workflows

A few examples:

1/ Cannibalization

Old world: SEOs download search console data and create pivot tables to spot keyword cannibalization.
New world: SEOs build an AI workflow that sends alters, identifies true keyword cannibalization, makes content suggestions to fix the problem, and monitors the improvement.

2/ Site Crawling

Old world: SEOs crawl websites to find inefficiencies in internal linking, status code errors, duplicate content, etc.
New world: SEOs build an AI agent that regularly crawls the site and automatically suggests new internal links that are shipped after human approval, fixes broken canonical tags and excludes soft 404 errors in the robots.txt.

3/ Content Creation

Old world: SEOs do keyword research and write content briefs. Writers create the content.
New world: SEOs automate keyword research with AI and create hundreds of relevant articles as a foundation for writers to build on.

All of this is already possible today with AI workflow tools like AirOps or Apify, which chain agents and LLMs together to scrape, analyze, transform data or create content.

Moving forward, we’ll spend much more time building automated systems instead of wasting time on point analyses and catalogs of recommendations. The SEO work will be defining logic, setting rules, prompting and coding.

You Can Learn (Almost) Anything With AI

I never made the time to really learn Python or R, but with the help of Chat GPT and Gemini in Colab, I can write any script with natural language prompts.

When the script doesn’t work, I can paste a screenshot into Chat GPT and describe the issue to get a solution. AI helps with Regex, Google Sheets/Excel, R, Python, etc. Nothing is off-limits.

Being able to write scripts can solve problems like data analysis, a/b testing and using APIs. As an SEO, I’m no longer dependent on engineers, data scientists or writers to perform certain tasks. I can act faster and on my own account.

I’m not the only one to figure this out. People are learning to code, write and many other skills with AI. We can learn to build AI workflows by asking AI to teach us.

When you can learn almost anything, the only limit is time.

The Work Of Writers Changes

Against common belief, writers won’t be crossed out of this equation but will play the critical role of editing, directing and curating.

In any automated process, humans QA the output. Think of car assembling lines. Even though AI content leaps in quality, spot checks reduce the risk of errors. Caught issues, such as wrong facts, weird phrasing or off-brand wording, will be critical feedback to fine-tune models to improve their output.

Instead of leg work like writing drafts, writers will bring AI content from good to great. In the concept of information gain, writers will spend most of their time making a piece outstanding.

The rising quality work spans from blog content to programmatic content, where writers will add curated content when searches have a desire for human experience, such as in travel.

Unfair Advantage

As often with new technology, a few first-mover people and companies get exponential value until the rest catch up. My worry is that a few fast-moving companies will grab massive land with AI.

And yet, this jump in progress will allow newcomers to challenge incumbents and get a fair chance to compete on the field.

AI might be a bigger game changer for SEOs than for Google. The raw power of AI might help us overcome challenges from AI Overviews and machine learning-driven algorithm updates.

But the biggest win might be that SEOs can finally make something instead of delivering recommendations. The whole value contribution of SEOs changes because my output can drive results faster.

Survey: ChatGPT and AI Content – Can people tell the difference?

Artificial Intelligence Voice Scams on the Rise with 1 in 4 Adults Impacted

Featured Image: Paulo Bobita/Search Engine Journal

In a new installment of its “SEO Made Easy” video series, Google provides three simple guidelines for utilizing internal linking to improve SEO.

The video, presented by Google’s Martin Splitt, offers valuable insights for improving site structure and user experience.

Strategic internal linking highlights your most valuable content, ensuring users and search engines can identify them quickly.

Additionally, internal linking can help search engines understand the relationships between pages, potentially leading to better rankings.

3 Tips For Internal Linking

Splitt emphasized three main points regarding the effective use of internal links:

User Navigation: Internal links guide users through a website, helping them find related content and understand the site’s structure.
Search Engine Crawling: Google’s web crawler, Googlebot, uses internal links to discover new pages and understand the relationships between different pages on a site.
HTML Best Practices: Properly using HTML elements, particularly the < a> tag with an href attribute, is essential for creating effective links.

The Importance Of Meaningful Anchor Text

One of Google’s key recommendations is to use descriptive, meaningful anchor text for links.

Splitt demonstrated how clear anchor text improves user experience by allowing visitors to quickly scan a page and understand where each link will lead them.

He stated:

“Users and Bots alike prefer meaningful anchor text. Here on the left you see what that looks like each link has meaningful words as anchor text and you can easily spot what the link will take you to.”

See the examples he’s referring to in the image below:

Splitt continues:

“On the right you see a page that doesn’t use meaningful anchor text and that isn’t a good user experience especially when you try to quickly scan the page and find the right link to use.”

See also: Sentence-Level Semantic Internal Links For SEO

Balancing Link Quantity

While internal linking is vital, Splitt cautioned against overdoing it.

He advises applying critical judgment when adding links and creating logical connections between related content without overwhelming the user or diluting the page’s focus.

Technical Considerations For Links

The video also touched on the technical aspects of link implementation.

Splitt discouraged using non-standard elements like spans, divs, or buttons to create links, saying if an element behaves like a link, it should be coded as one using the proper HTML structure.

In Summary

These are the key takeaways from Google’s video on internal linking:

Internal linking is a fundamental aspect of SEO and user experience.
Focus on creating meaningful, descriptive anchor text for links.
Use internal links strategically to guide users and search engines through your site.
Balance the number of links to avoid overwhelming users or diluting page focus.
Stick to proper HTML structure when implementing links.

See the full video below:

Featured Image: Screenshot from YouTube.com/GoogleSearchCentral, July 2024. 

There are often times when more than one keyword (and/or search theme) in your account will be eligible to match for a search term. Yet only one will be selected to compete in each auction.

So, how does Google choose which of your keywords to put forward?

There’s a prioritization framework for that!

We’ve also recently launched several updates to query matching controls, including the new brand inclusions and brand exclusions, to help you steer traffic where you want it.

While the keyword and search theme prioritization framework for query matching isn’t entirely new, it’s evolved in meaningful ways with recent AI advancements.

Now is a good time to dive into the mechanics of keyword prioritization and query matching controls. This will give you a better foundation for organizing your campaigns and ad groups, building keyword lists (positive and negative), selecting keyword match types, and using search themes to drive performance.

We’ll cover various scenarios and what to keep in mind for each prioritization rule – as well as what you need to know about the latest in query matching controls.

Why Keyword Prioritization Matters

Keyword prioritization rules help ensure keyword-to-query relevance to deliver better user experiences and advertiser outcomes.

But another big benefit of keyword prioritization rules is that they help address the reasons why advertisers resorted to using “keyword sculpting” techniques that entailed complex account and bid structures in order to route traffic where they wanted.

How Keyword Prioritization Works In Google Ads

I think of the four priority levels, or rules, shown above in two batches:

Priority rules 1 & 2 apply to scenarios when you have a keyword or search theme that’s identical to the search term or spell-corrected search term.
Priority rules 3 & 4 apply to scenarios when you don’t have an identical keyword or search theme and have multiple matches that could enter the auction.

Top Priority: Identical Exact Match Keywords

If you have an eligible exact match keyword that is identical to the search term or spell-corrected search term, that keyword will be prioritized to enter the auction over all other keywords in the account.

This prioritization rule means:

The exact match keyword [skydiving license] will match to the identical query “skydiving license”.
The identical exact match keyword [skydiving license] will also be prioritized over the same keyword duplicated in phrase or broad match – whether in the same or a different ad group.
It will be prioritized over Performance Max for Search text ads.
And it will be prioritized over any other relevant phrase or broad match keyword that could otherwise match to the query, such as “skydiving certification” or “skydiving licensing.”
Also important to note, if you have the broad match campaign setting enabled, those keywords will be treated as if both a broad match and an exact match version of the keyword were enabled.

Keep in mind:

Misspelled/spell-corrected search terms are considered “identical,” but plurals or synonyms are not.

So [skydoiving license] would be considered identical to [skydiving license], but [skydiving licenses] or [freefall license] would not.

The keyword has to be eligible to serve in order to match – this is true across all prioritization rules.

For example, if the campaign is limited by budget the keyword won’t always be able to trigger an ad.
Or if the targeting doesn’t align, the creatives or landing pages in the ad group are all disapproved, or the keyword has low search volume status, you may see traffic go to other keywords or Performance Max.

2nd Priority: Phrase, Broad Match, Or Search Themes That Are Identical To The Query

Next up, if you don’t have the identical exact match keyword, the system will look to see if there’s a phrase or broad match keyword, or Performance Max search theme that’s identical to the query or spell-corrected query.

This prioritization rule means:

A Search keyword that’s identical to the query will be prioritized over Performance Max, regardless of match type – exact (as covered by the first priority), phrase or broad.

This is worth reiterating because I often see it misunderstood: If you have an identical Search keyword to the query of any match type, Performance Max will not be considered for selection. With one exception . . .

If you have duplicate search themes and phrase or broad match keywords that are identical to the query, priority will be based on Ad Rank.

For example, if you have both the search theme and phrase match keyword “skydiving license” and that’s the query, the ad with the highest Ad Rank will be selected for the auction.
That’s because Performance Max search themes have the same prioritization as phrase and broad match keywords.

If you have the identical search theme to the query in Performance Max but not an identical keyword in Search, the search theme will be prioritized.

Keep in mind:

Misspelled/spell-corrected search terms are considered “identical,” but plurals or synonyms are not. So [skydoiving license] would be considered identical to [skydiving license], but [skydiving licenses] or [freefall license] would not.
There is no performance benefit from repeating the same keyword in multiple match types in a campaign.

Because the system prioritizes eligible keywords that are identical to the search term, you will have the identical keyword covered with any single match type.

Further, there’s a misconception that exact match keywords are “cheaper” than their phrase or broad match types.

If the factors are equal (ad, landing page, bid strategy), the cost for the same broad or phrase match keyword to pick up the identical exact match traffic will be equivalent. More on keyword matching options here.
If you are using phrase and/or broad match keywords and have duplicate keywords across match types within your ad groups, you can dedupe and remove the redundant keywords in the most restricted match types.

We recommend using search themes to fill gaps, rather than duplicate your keywords, in order to help steer the AI in Performance Max. More on search themes here.

Alright, now for the scenarios when you don’t have the identical match to the query in your account, we’re moving on to the next two rules of prioritization . . .

3rd Priority: Relevance (AI-Based Keyword Prioritization)

This is the new(ish) kid on the prioritization block – and the biggest recent advancement in keyword selection for Search campaigns.

AI-based keyword prioritization introduces relevance signals to identify the best keywords from the most relevant ad groups when multiple ad groups are eligible to match to a query.

This prioritization rule means:

Relevance is determined by looking at:

The meaning of the search term.
The meaning of all the keywords in the ad group.
The landing pages within the ad group.

Keywords with a lower Ad Rank but higher relevance can be selected over keywords with lower relevance.
AI-based prioritization currently works on keyword-based Search campaigns only (e.g. it does not work on Dynamic Search Ads).
It is used when your keywords aren’t identical to the search term.

Keep in mind:

A big benefit of AI-based keyword prioritization is that it reduces the need to create granular campaign structures to route traffic manually while still giving you control over which keyword matches to a query using thoughtful ad group theming.
To that end, AI-based prioritization only works as well, as it can infer relevance. This is why ad group theming is so important, particularly when using broad match.
Grouping your keywords into similar themes with relevant assets and landing pages makes it easier for Google to understand the intent of your keywords and landing pages and select the best match for the intent of the user’s search.

For example: Looking closer at the example outlined in the Help Center, a search for “skydiving certifications near me” could match to the ad groups “Skydiving License” and “Advanced Skydiving Courses.”

Both ad groups have related intent to the query, but the “Skydiving License” ad group has keywords and a landing page specific to licensing. Whereas the “Advanced Skydiving Courses” ad group has keywords and a landing page focused on advanced courses.

Because ‘license’ (included in both the keywords and landing page) + ‘certifications’ (included in the search term) are seen as significantly more related than ‘courses’ + ‘certifications’ to a search for “skydiving certifications,” the “Skydiving License” ad group is selected.

(Having worked on many education and certification campaigns over the years, I particularly appreciate this example!)

4th And Final: Ad Rank

Ad Rank is the final prioritization rule used to determine which keyword (or search theme) in your account will be selected to enter the auction. We’ve already covered some of the scenarios in which Ad Rank is used when the other rule criteria aren’t met.

Ad Rank considers a number of factors, including ad quality components, in real-time with every auction to determine which, if, and where your ads are shown relative to other advertisers. More on Ad Rank here.

This prioritization rule means:

If you have the identical keyword to the query repeated in both phrase and broad match, priority will be based on Ad Rank. The ad with the highest Ad Rank will be prioritized.
If you have the identical search theme in Performance Max and phrase or broad match keyword in Search, priority will be based on Ad Rank.
If there are multiple highly relevant phrase and/or broad match keywords eligible after being considered by AI-based keyword prioritization, Ad Rank is then used to make the final selection to enter the auction.

Keep in mind:

Ad Rank also considers other factors, such as your bid, the expected impact of assets and ad formats (e.g., sitelinks, location assets, etc.), and the context of the person’s search.
When you run Performance Max and Search campaigns and don’t have an identical keyword to the search query, the campaign or ad with the highest Ad Rank will be selected.
And a quick note on Quality Score: Quality Score is based on historical impressions for identical searches of your keyword, which means the match type you use doesn’t impact Quality Score – nor does changing match types.

For example, if all else is equal (bid, ad, etc.), the broad match keyword running shoes and exact match keyword [running shoes] will have the same Quality Score.
If your broad match keyword running shoes matches to the search “shoes for running”, that doesn’t factor into Quality Score.

New Controls For Query Matching

In June, we announced several updates for query matching and brand controls. I’ll explain a bit more about each update and answer some of the questions I’ve received about them.

Brand Inclusions For Broad Match Campaigns

This feature (initially called brand restrictions) ensures your ads match only to queries related to your brand name in broad match campaigns.

To use brand inclusions, you’ll need to turn the broad match keywords setting on in your campaign. This will automatically set or change your keywords in the campaign to broad match.

After you create a brand list at the account level, you can apply it to the campaign.

It’s first important to note that there are ongoing, continuous improvements in broad match, and AI advancements are helping to accelerate progress.

For example, in the recent six months, broad match performance improved by 10% for advertisers using Smart Bidding due to AI-powered improvements to quality, relevance, and language understanding1.

And, in addition to using Smart Bidding, there are key controls for steering broad match. We have already touched on the importance of ad group theming, for example.

Brand inclusions is a new control that enables advertisers to use broad match effectively in their branded campaigns.

This means:

You can focus traffic only on queries that include your brand while also using the additional signals available to broad match, including landing pages, keywords in your ad group, previous searches, and more.
You may also now see recommendations to switch your brand-focused campaigns to broad match and apply brand inclusions.

Keep in mind:

Brands are not the same as keywords. Unlike keywords, brands are treated like individual entities.
We use logos, websites, and trademarks to determine the right brand and related products.
There’s no need to include misspellings, variants, or versions in other languages in your brand lists.
If there is a strong correlation between the query and brand entity, your brand products will be associated with the brand.

Brand Exclusions For Search

Already available for Performance Max, brand exclusions will be rolling out for Search in the coming months.

Brand exclusions offer a streamlined solution to prevent traffic from queries associated with certain brand names and misspellings.

As with brand inclusions, you create brand lists at the account level. Then apply them for exclusion to your Search and/or Performance Max campaigns.

This means:

You can exclude matches to searches for competitor brands, for example.
Brand exclusions for Search apply to all match types and Dynamic Search Ads.
You can also use brand exclusions to prevent matches to other brands mentioned alongside the brand you’ve specified.

For example, if you want traffic for “google” but want to avoid comparisons like “google vs samsung phone.”

Or you can prevent traffic on sub-brand queries. For example, you may want traffic for “google” but not “google maps.”
You will be able to apply brand lists for exclusion to multiple Search and/or Performance Max campaigns.

Keep in mind:

Brands are not the same as keywords. Unlike keywords, brands are treated like individual entities.
We use logos, websites, and trademarks to determine the right brand and related products.
There’s no need to include misspellings, variants, or versions in other languages in your brand lists.
If there is a strong correlation between the query and brand entity, the brand’s products will be associated with the brand.
The simplest variant will typically capture all variants when multiple variants of a brand have at least one common word, such as “Google” and “Google LLC.”

For example, “Google” will capture all variants of search queries that include “Google.” You don’t need to add the other variants to your list.

However, when multiple variants of a brand don’t have common words, such as “Google”, “YouTube”, and “Alphabet”, you’ll need to create a list that includes all of the variants.

Otherwise, the more general brand will often, but not always, capture all traffic related to all brands. (More here.)

Brands vs. keywords: You can still add brands as negative keywords, but since negative keywords are limited in that they don’t exclude brand variants, we recommend only using negative keywords for blocking traffic that’s undesired, regardless of performance.

Negative Keywords Block Misspellings

Negative keywords are a valuable control to prevent traffic from unwanted search terms.

And this is a very welcomed update. Negative keywords now prevent matching to misspelled queries. Below are examples of scenarios I’ve been asked about.

This means:

Now, instead of having to monitor your search terms or think of possible ways people might misspell your keywords, you just have to enter the correct spelling.
Misspellings as negatives won’t block correctly spelled queries, but correct spellings as negatives will block their misspelled queries. See examples below.
It will block misspellings but not synonyms, singular or plural versions, and other close variations.
You’ll still need to add those if you want to exclude them. (e.g., YT would be a variant of YouTube, and the misspelling would be yiotube.) See examples below.
You can likely do some negative keyword list culling to remove misspellings and streamline things in your account.

Keep in mind:

This update applies to campaign-level and account-level keywords. More on negative keywords here.
Misspellings will apply to all negative keywords, regardless of match type.
Wondering if a word will be considered a misspelling of your keyword? A good way to check is to search on Google to see if it returns “These are results for” the spell-corrected query.

Will Pausing Low Volume Keywords And/or Ad Groups Impact Query Matching And Performance?

Lastly, another recent change raised some questions that I want to touch on.

Earlier this year, we notified advertisers that we would be automatically pausing Search ad groups and keywords that haven’t received an impression within the previous 13 months.

Clutter happens and idle ad groups and keywords that hadn’t been contributing to performance for some time can add up.

We don’t expect pausing ad groups or keywords that haven’t had an impression for more than a year to have a noticeable impact on your Search campaign traffic or to change the traffic mix between your Search and Performance Max campaigns.

You can continue to review and unpause any keywords or ad groups you think are still needed…however, this brings us back to account structure and ad group theming for relevance.

If you think these paused ad groups or keywords should have been matching to queries and generating impressions, consider before simply re-enabling them:

Check the keyword status for potential issues.
Look at whether these ad groups/keywords will be additive or if other keywords or ad groups are already covering this traffic.
Consider expanding the match type of these keywords to capture more queries.
Then, take a broader look at your ad groups’ creative theming, keeping the relevance signals that AI-based prioritization looks at in mind, including the other keywords and landing pages in the ad group.

Key Takeaway

Now that you have a deeper understanding of how these keyword prioritization rules and query matching controls work, take a fresh look at your account.

You may find opportunities to reorganize and consolidate your campaigns and focus on making your ad groups more tightly themed.

These efforts will help you streamline your account (e.g., simplify management) while also ensuring you are matching relevant queries with your most relevant ads to drive results.

Notes

1Google Internal Data, Oct 2023 – Mar 2024. Performance refers to conversions/conversion value at constant ROI.

More resources:

Featured Image: BestForBest/Shutterstock

If you’ve been paying attention to the chatter in the SEO space recently, you might have noticed that “brand marketing” has become cool again.

Due to the Google “leaks,” many SEO pros have come to the conclusion that building a strong digital presence will yield SEO results.

Also, water … is wet.

Leaks, floods, and drips aside, there are better reasons why you should be focused on brand marketing right now.

Allow me to explain. [Warning: This post contains excessive amounts of snark.]

Building The Case For Brand Marketing

I’m not going to do the whole “5 reasons why you should focus on brand in 2024.” It would be off-brand for me.

What I would like to do, if you’ll indulge me, is first build up the case by looking at where the ecosystem we call the web is currently at.

I’m less focused on “the benefits” of the brand and more concerned about why the ecosystem itself demands a focus on this type of marketing.

It’s less a matter of “you’ll get X, Y, and Z” by focusing on the brand and more a matter of why you’ll be out of sync with your potential audience as a whole.

The Web Is Moving To Be More Conversational

The internet has become more conversational, and it’s only going to get more conversational.

One of my soapbox points is that content is one of the most quickly changing things on the planet. What we consume, how we consume it, and what we expect out of it are rapidly and constantly changing, and the consequences are often underappreciated.

My classic example of this was the first televised US presidential debate, which took place in 1960 and pitted John F. Kennedy against Richard Nixon.

If you listened to the debate on the radio, you tended to think Nixon won. Those who watched on TV tended to think JFK won.

Why? Well, Richard Nixon comes off as Richard Nixon, and JFK, well looks like JFK. I’m being a bit facetious, but it is true. Nixon famously looked pale, had a five o’clock shadow, and didn’t look directly at the camera.

The evolution of content has extremely understated consequences.

Like in 1960, we are at one of those pivotal moments in the history of content.

Think of the internet like TV commercials. Over time, what once resonated becomes campy and sem, if not downright, spammy.

Could you imagine Coca-Cola running and trying to sell its product using its 1980s Max Headroom “Catch the Wave” commercial?

Try selling my kids a sugar-infused breakfast cereal using a TV commercial from the 1950s. Good luck.

It’s not because those commercials are “bad.” It’s because the language and tone that resonates changes over time.

It’s a simple enough point … unless we’re talking about web content. For some reason, we feel web content and its consumption trends should eternally stay the same.

We write the same kind of content in pretty much the same way and balk at any changes.

But that doesn’t change the reality.

The content we create doesn’t speak to users. It’s not positioned correctly. The tone is off. The goals that support the creation of content, to begin with, are distorted. And more. There are a lot of problems – and to me, they all begin with content not being conversational.

In fact, I will go so far as to say Google should stop saying, “Write for your users,” and should start saying, “Have conversations with your users.”

We all think we’re “writing for our users” – I mean, who else are we trying to lure and convert?

It’s very easy to fool yourself into thinking you are “writing for your users.” It’s harder to convince yourself you are having some sort of dialogue with your users – which is what I think Google really means anyway.

All this said, what do I mean by content not being conversational and how do I know it’s even a problem?

What I Mean By Content Not Being Conversational

It’s not hard to see that we are not engaging our users in a conversation or dialogue.

All you need to do is head over to your nearest landing page and have a look at the language.

How much of it is just the company throwing out jargon or borderline nonsense?

Here’s what I came across in literally less than five minutes of digging around:

Is it really without limits? Can I literally do whatever I want without any limitations whatsoever? I don’t get it – are we talking about God or graphic design software?

Is the below really a new way to run high-velocity sales? Does it literally refine the entire process like no one else is doing or has done before? Or is the company just saying this and spitting out whatever they think will drive conversions?

You see this all the time in PPC ads:

No nuance. It is the best accounting software, and I should trust that it is without any form of qualification.

This kind of copy, while it may have worked in the past, doesn’t (and if it does now, it won’t in the relatively near future).

This kind doesn’t actually talk to users in a real way. It actually treats the user like an idiot.

The average web user is far more savvy than they once were, far more mature, and far more skeptical.

Not taking a more genuine approach is starting to catch up with brands.

How Do I Know Not Being Conversational Is Even A Problem?

Greenwashing.

It’s when a company claims to be more environmentally conscious than it is. It’s spin and PR nonsense.

Companies thought they could pull a fast one on unsuspecting users. However, folks are now savvier and are catching on to brands positioning themselves as being “green” when, in reality, they might not be (or at least to the extent advertised).

You cannot get away with it anymore (and you never should have tried). The only thing that works is being genuine.

If your product is not actually “the best,” then don’t say it is – or, in fact, realize there is no “best” or “ultimate” or “fastest” or whatever. There is only what meets the needs of users in what way. That’s fancy talk for “pain points.”

Being genuine means talking to your audience and not at your audience. It’s having a dialogue with them.

Going the “traditional” route with your language is the equivalent of marketing language greenwashing … and it applies to your informational content, too.

Perhaps nothing epitomizes this more than the falling stock of influencer marketing. Study after study shows that younger users are far less likely to purchase something because an influencer is associated with it.

Influencer marketing, as we mostly know it, is a facade pretending it’s not a facade. Do you think Patrick Mahomes really eats Chicken McNuggets or has a strong preference to use State Farm for his insurance needs?

All influencer marketing is just a digital marketing version of a celebrity in a TV commercial.

Do you think whatever TikTok influencer really prefers Capital One or even knows that it’s not a geographical reference?

While the idea of “influencers” seemed like a viable idea at the onset it’s fundamentally not sustainable because it’s fundamentally fraudulent. (For the record, “community” marketing is something else entirely. While it might rely on “influencers” within a community, it is far more genuine.)

It seems that folks have caught on to the idea that maybe this influencer being paid to say or do whatever is not actually an accurate reflection of reality (much like social media influencers themselves, to be honest).

A 2023 Drum article quotes one study as saying upwards of 80% of users say a brand’s use of influencers does not impact them one way or the other.

For the record, there are other studies that indicate that influencer marketing is a viable option. I agree, but I think it needs to be qualified. Just paying an influencer to say good things about your brand is not authentic.

There are authentic ways to work with communities and influential folks within them. That tends to happen more with micro or nano influencers.

This is why we’re seeing a trend towards working with micro or nano influencers who might provide a more authentic experience for audiences – a trend noticed by Hubbspot’s 2024 social media marketing report (among others).

Again, it’s rocket science. Everyone knows the influencer is only saying the things they are saying because they’re being paid to. It’s relatively meaningless in a vast majority of cases.

It shows how much savvier the current web user is relative to the past, and it’s supported by where folks are heading and what they are trusting … themselves (DTA, am I right?).

A seemingly endless number of studies show users looking toward user-generated content. CNBC was quoted as saying, “61% of Gen Z prefer user-generated content.”

Which brings me to my next point.

Informational Content Is Just As Bad & Reddit On The SERP Proves It

Up until this point, I’ve been focused on the nature of commercial content and the demand for conversational content.

The same concept applies to informational content, just for a slightly different reason.

Informational content on the web might not be as opaque as commercial content, but it is entirely sterile and stoic.

By sterile and stoic I mean content that doesn’t actually speak to the user. It takes a topic, breaks the topic down into various subtopics, and simply presents the information, and does so without ever discussing the context of the readers themselves.

No one has more data on emerging content consumption trends than Google and its ability to analyze user behavior in a variety of ways. And what has Google done for informational and commercial queries alike? Plastered the search engine results page with user-generated content.

The proliferation of Reddit on the SERP should tell you everything you need to know about the state of informational content and beyond.

All you need to do is head to the Google SERP and take a look at all of the Reddit results strewn all over the place, from different SERP features to the organic results themselves.

And while SEO pros may be upset about the abundance of Reddit (and rightfully so in my opinion), we have no one to blame but ourselves.

Do you really think Google wants to rank Reddit here, there, and everywhere? I personally don’t. I think Google would much rather have a diverse set of experience-based content to rank.

Regardless of your feelings about Reddit on the SERP, users’ inclination to prefer content created by other users tells you one thing: People are looking to move past all the facades and want something transparent that speaks to them—not at them.

Think about content like dress codes in the office. In the 1950s (at least in the US), it would be unheard of to show up to the office with anything but a suit and tie or a dress.

Just like professional dress codes have become less formal, so has content become “less formal” too.

And it’s a relatively recent development on both fronts. In fact, I would actually argue that office dress codes are a good representation of “where we are at” in terms of how and what we consume in terms of content via-a-vis formality.

While more traditional marketing language might have been acceptable and effective just a few years ago – it’s not any longer (at least not to the extent). We are less formal as a people, which means speaking to each other is also less formal. That has to spill over to web content at some point, and it has.

The AI Of It All

The rise of AI-written content accentuates all of this. When everything starts to sound the same having an actual voice comes more into focus. As AI conversion evolves, users are going to want to know that what they are consuming is “real.”

Much like a paid influencer, AI-written content doesn’t offer an authentic experience. And if we can see one theme in what users are looking for, it is an authentic experience.

I know someone is reading and thinking, “But AI is conversational!”

I would not confuse the fact that AI can reply back to you in an informal way as being an actual conversation or dialogue with another actual lifeform.

I have many relatives who will chew my ear off for hours on end as I nod away – that is not (much to their surprise) a conversation. Inputting prompts in reply back to an LLM and then having that LLM respond is not a conversation. (I feel like it’s insane that I have to say that.)

A real dialogue has to be based on empathy and the coming together of two distinct entities. This is what I mean by conversational. The dialogue has to be based on understanding the user’s pain points and meeting them.

AI not only doesn’t do that – but it dilutes that very concept. AI is content creation inherently devoid of understanding the “other.”

AI-generated content is the exact opposite of empathetic content. It is no wonder that it will drive a greater demand for something that is more connective (i.e., conversational content).

The rise of AI-generated content will inevitably lead to a greater demand for more conversational content simply because it is human nature to yearn for connection and existentially disdain void.

When you couple together the growing impatience with stale and stoic content aligned with the facade of much of the web’s commercial content with the rise of AI, it’s the perfect storm for a shirt in user demand.

A More Conversational Internet Is More Autonomous Internet

What’s this got to do with brand marketing? We’re getting there. One more step.

Users looking for more authentic web experiences point to people not wanting to be sold to. Skepticism and distrust are triggered by being urged to make a purchase.

Rather than being induced to click by some clever headline or urged to make a purchase by some influencer, people want to make their own decisions.

They’re looking for real advice. They’re looking for real information to have real needs met. And then they’re looking to be left alone to use that information to their liking.

It’s not an accident that Google added an “E” to E-E-A-T for “experience.” It wants quality raters to evaluate a page from an experience perspective because it has determined this is what users are looking for.

When your entire modus operandi is to seek out authentic information and experiences, the last thing you’re looking for is to be coerced. The last thing you want is to feel pushed into something.

The quest for authenticity in experience-based information is entirely about being able to make a well-informed, autonomous decision.

Urging users to click and convert with all sorts of marketing language and over-emphasis is antithetical to this mindset. Using language that feels slightly manipulative is antithetical to this mindset.

Trying to create spin and putting up a marketing facade (such as with classic influencer marketing) is antithetical to this mindset.

You can’t have Michael Jordan jumping over Spike Lee in a commercial to sell shoes anymore. It’s not real, and it’s not authentic. It’s fantastical. It’s fake.

You also can’t “drive” conversions by telling users you’ve developed a “new,” “revolutionary,” or “ultimate” solution for them. It’s not real, and it’s not authentic. It’s fantastical. It’s fake.

You have to create an environment where the user feels empowered and uncoerced.

How do you then go about targeting growth and revenue, all while allowing the user to feel autonomous and unsolicited?

Brand marketing.

Brand Is Your Best Friend In An Autonomous Web Scenario

I know there is going to be a tremendous amount of resistance to what I am about to say.

In fact, most companies will balk at my conception of things. For SaaS, it’s probably borderline heretical (I think startup SaaS brands often lag behind consumer trends more than anyone).

If user autonomy is the fundamental brick on the house the ecosystem is built on, then being top of mind is the cement that holds your marketing efficacy together.

What’s the opposite of pushing for clicks and conversions? Allowing the user to come to you at their own time and at their own speed.

Being top of mind is more important than it ever was because it aligns with the underlying psychological profile driving web experiences.

There is a direct equation between the consumer demand for autonomy in the buying journey and brand marketing. Creating the right associations and developing the right positioning with genuine differentiation is of the utmost importance if you want to align with how users think – and, more importantly, feel about the web.

If I had to put in a more “performance-focused” mindset, direct traffic is the future of the web. Get them to come to you on their own terms.

It works for both parties. You’re less susceptible to relying on whatever platform’s funky algorithm (whether it be social or search, it all kind of feels like a mess right now). At the same time, your users don’t feel like you’re overselling, pushing clicks, and otherwise nudging them to convert.

They’re coming to you because they found out about you, liked what they saw or heard, and decided to pursue the possibility of buying from you at their own pace.

Moreover, the brand allows you to connect. Again, in an AI world, the drive for connection will only increase. Brand is the intersection of your identity and your audience’s.

It is an associative connection, and it allows your audience to understand that there is a “you” behind the product or service you are offering.

This is the power of branding in the modern web.

What Kind Of Brand Marketing?

What kind of branding creates autonomy? Education-focused brand marketing.

Brand marketing can mean a lot of things to a lot of different people. Often, on the digital stage, it means pushing the value of your product across the web.

I am not saying that this doesn’t have value or that it shouldn’t be done, etc. I am saying this is product marketing disguised as brand marketing.

90% of your brand marketing should hardly (if at all) push your product (beyond maybe a mention or something subtle of that ilk).

Brand marketing is about fostering an identity (either of a product, service, or the company as a whole) and using that identity to create messaging that positions the said product, service, or company in a certain way, thereby establishing a connection with your target audience.

The associations you build and the sentiment towards your brand that you establish should, hopefully, result in your audience seeing you as a relevant solution. But this is associative, and that’s important to remember.

The kind of branding I am talking about is focused on adding value to your audience’s life. Note that I didn’t say offering value via your product or service to their lives. First comes the value, and then comes the value from your product.

You can’t push the product in what might be called “branding” without first establishing a brand that showcases concern for the user and their life context independent of any “ask” (such as making a purchase).

You wouldn’t ask your neighbor for a cup of sugar before saying, “Hi, good morning. How are you?”

You shouldn’t ask your consumers to open their wallets and fork over money before establishing a real connection.

Yet, this is pretty much the internet as we know it.

A Note On Performance Marketing

I am not advocating you should not use performance-based marketing tactics to increase your reach and sales and whatnot. Performance-based marketing can be a powerful force for growth and revenue expansion.

What I am advocating for is performance sitting within a broader branding context. There has to be a balance between the two (and I don’t think it is an even balance).

With that cliffhanger, perhaps I’ll explore the balance between brand and performance at another time.

More resources: 

Featured Image: batjaket/Shutterstock

WooCommerce announced their roadmap for the future of WooCommerce, emphasizing two-way communication with the developer ecosystem in order to be responsive to their needs which further the goals of improving the experience for developers, merchants and customers.

WooCommerce highlighted seven important areas for innovation and six specific areas that are targeted for enhancements that will improve developer and merchant experience.

1. Stronger WooCommerce And Developer Communication

WooCommerce recently launched a newsletter that seeks to keep developers in the look with the latest WooCommerce news, offering early previews of new features, plus tutorials and other information that will keep the community in the loop.

The announcement explains three benefits of the newsletter:

“Exclusive Insights:Gain access to behind-the-scenes knowledge and tips that can elevate your development game.
Latest Content:Engage with newly published blog posts and documentation, showcasing our latest releases, resources, advisories, and more.
Feature Updates and Announcements:Keep your projects current by receiving the latest updates on new features and essential changes in WooCommerce.”

2. Upgrading The WooCommerce Blog and Documentation

Another area of improvement that relates to communication is to emphasizing the official WooCommerce blog as a reliable source of information that’s important to developers.

WooCommerce is also committing to improving their documentation with more guides, step-by-step tutorials, best practices and also making it easier to navigate and find needed information.

The roadmap explains:

“Our goal is to fill crucial knowledge gaps in areas such as extensibility, block development, and theme customization, empowering developers to start and thrive on our platform.

This is a welcome news for developers. One person commented on X (formerly Twitter):

“Coincidentally, I saw this immediately after reading my developers’ frustrations about the documentation for the new product editor in our internal discussions – so it’s good to see that improving this is on the roadmap.

Specifically, we have several plugins which add functionality to the ‘Edit Product’ screen, so we need to integrate them with the new product editor. My developers are finding this unnecessarily difficult because:

– The developer information about each feature is scattered throughout multiple news articles when it should be collated in one location.

– The links to the GitHub discussions about the new Product Editor in the “Roadmap Insights” articles point to the WooCommerce Product Block Editor discussion category (which doesn’t exist anymore) instead of the new WooCommerce New Product Editor one.

– We’re reluctant to update our plugins that integrate with the variations editor because the hooks and filters required for this extension are currently marked as experimental, so we might have to redo work if they change in future.

– We were expecting to see a timeline for the new product editor in January/February but this still isn’t clear, so we don’t know how heavily to prioritize the changes in our plugins.”

3. Improvements To REST API V3

Improvements to the REST API v3 are a top priority, with a focus on backward compatibility. They are also committing to reducing the backlog of issues and new feature requests plus improving API performance.

They also said they would focus on:

“…upgrading API documentation, error handling, and debugging capabilities.”

4. Improve Feedback Loop on Extensibility

A feedback loop is the communication between WooCommerce and the developers who use it, with the goal of improvement being a collaboration that results in a superior product that better serves developer and merchant needs.

Extensibility refers to the flexibility of WooCommerce to be extended and adapted, which is an important benefit of WooCommerce. Thus, one of the “destinations” in the WooCommerce roadmap is to make sure that it is adaptable and easily molded by developers.

Communication between developers and WooCommerce is a key part of maintaining and improving the extensibility of WooCommerce.

WooCommerce commented:

“As we make new features the default experience, we are working to create space for collaboration with our developer community in order to refine these features, incorporate feedback, and gradually move towards full adoption.

In the past year, we have begun using GitHub Discussions, Developer Office Hours, and other sources of feedback to shape and prioritize extensibility points in particular. This iterative process not only enhances the platform but also strengthens the ecosystem, making WooCommerce a more robust solution for everyone.”

5. WooCommerce Is Committed To A Block-Based Future

WooCommerce committed to a 100% block-based feature development in late 2023 as part of a vision of making WooCommerce easier to use for non-coders. A second motivation is to create a more adaptable shopping platform to build upon. As part of this commitment WooCommerce is signaling that now is the time to stop relying with older solutions like shortcodes and legacy APIs.

The statement read:

“If your solutions are still relying on shortcodes or other legacy APIs, it’s time to embrace blocks and modernize your approach.”

WooCommerce announced steps they are taking to bridge the transition to a fully block-based development platform:

Adding more resources to the WooCommerce Developer Documentation
Increased frequency of communication on the WooCommerce blog
More posts to introduce new features tutorials for how to use them
A renewed focus on creating video tutorials

6. Streamlined onboarding:

WooCommerce is focusing on further simplifying the process of setting up a store and getting online faster. They are also improving the workflow for developers who set up stores for merchants. They said that their experience from simplifying the setup process was an approximately 60% increase in completion rates.

7. Modern Store Customization

Another focus is on being able to integrate the customization options available to WordPress in general but WooCommerce is also looking into creating fully optimized commerce-based themes that are specific to WooCommerce.

They write:

“While we’re ensuring compatibility with all block-based themes in the WordPress ecosystem, we’re also exploring what it would look like to provide our own fully block-based, commerce-optimized theme out of the box.”

Six Specific Areas For Future Improvements

Flexible product management
Optimized order management and fulfillment
Revamping merchant analytics
Accessible stores
Evolving checkout experience
Better integration of order confirmation with summary and shipping information

WooCommerce Roadmap Leans In On Community

The Roadmap outlined by WooCommerce recognizes that the user community is its strength, thus it’s focused on building a stronger product based on what developers need to provide merchants with the ecommerce experience merchants expect. Focusing on creating more documentation and videos shows that WooCommerce is engaging to support the WordPress developer community and intends to remain the leading ecommerce platform.

Read the WooCommerce roadmap announcement:

WooCommerce in 2024 and beyond: Roadmap update

Featured Image by Shutterstock/Luis Molinero

You may already be familiar with STAT Search Analytics and its rank tracking abilities, but did you know it can also help you discover SEO opportunities on a massive scale? In today’s Whiteboard Friday, Cyrus shows you how to dig into STAT to do just that. 

Click on the whiteboard image above to open a larger version in a new tab!

Video Transcription

Hi, everybody. Welcome. My name is Cyrus. Today the thing I want to talk about is how to use STAT to find SEO opportunities at scale, and I mean massive scale. 

Now a lot of you have probably heard of STAT. You may know that it has an excellent reputation. But it’s possible you haven’t actually used it or have a very good understanding of what it actually does. 

So that’s what I’m going to try to cover today and explain how powerful it is at discovering SEO opportunities in ways that can inform content strategy, competitive analysis, and a lot more. 

What is STAT?

So STAT, the full name of STAT is actually STAT Search Analytics. On the surface, what a lot of people understand is that it is a rank tracker, tracking thousands of keywords at a time anywhere across the globe. But underneath the hood, it’s actually a lot more than a rank tracker. It’s a rank tracker. It’s a competitive landscape tool. It’s SERP analysis and intent. It allows you to do some pretty incredible things once you dig into the data.

Keyword attribution

So let me dig into a little bit about how it actually works. So like a lot of keyword rank trackers, you start with keywords. But one of the differences is all the different attributes that you can assign to each of your keywords. 

So first is very familiar, the market or the search engine. So you want Canadian English results or Canadian French results. Any market in the world that’s available it’s pretty much available for you to use in STAT. 

The second is location, which is a slightly different concept. So you can define ZIP Codes, cities, be as specific as you want. This is very important for multiple location businesses or if you’re running an advertising campaign in a certain part of the country and you want to track very specific results. But you can define location very specifically for each of your keywords. 

Third is device, mobile or desktop, especially important with mobile-first indexing and increasing mobile results. But also tags, smart tags, and this is where the true power of STAT comes in, the ways that you can use smart tagging. 

Smart tagging

So you can tag your keywords in multiple ways, assigning multiple tags to slice them and dice them any way you want. 

So different ways that you can tag keywords in STAT is anything that’s important to your business. For example, you can create keyword groups based on what’s important to you. On Moz, we tag keywords with “SEO” in it or anything that’s important to your business that you want to create a keyword cohort out of. Or location, like we were talking about, if you’re running an advertising campaign in Indiana and you want to tag certain keywords that you’re targeting there, something like that. Or all your Kansas city keywords or your London or Berlin keywords. 

Product categories. So if you sell multiple categories, you sell TVs, books, dresses, anything you want, you might want to tag all of those into a particular keyword category. Or attributes, such as a 55-inch television versus a 48-inch television, when you want to get very, very specific across your product line.

Also your brand. At Moz, we track everything with the word “Moz” in it, or Nike or Apple or whatever your brand is or if you have multiple brands. Basically, anything that’s important to your business, any KPI that you measure, anything that’s relevant to your marketing department or finance or anything else like that, you can tag, and that’s where the true power comes in, because once you tag, you’ve created a keyword cohort or a group.

Share of voice

Then you can see your share of voice across that entire market using just that group. So if you want to track yourself against a very specific set of keywords, you can see your share of voice, share of voice meaning how much visibility you have in Google search results, and STAT will show you your exact competitors and how you rank among those.

Generally, you want to see yourself going up and to the right. But if you’re not, you can see exactly who’s beating you and where their movement is, and how you’re doing for that specific keyword group, which is incredibly valuable when you’re working on a particular set of keywords or a campaign. 

SERP features + intent

But my favorite part — and this is where the true power comes in, because it can inform your content strategy and this is where the SEO opportunities are actually at — is the analysis of SERP features and intent. Because what STAT will do is, out of the thousands of keywords that you put into it, it will analyze the entire SERP of each of those and it will collect all the SERP features that it finds and tell you exactly what you own and don’t own and where your opportunities are.

So let’s give an example that’s a little more concrete. So let’s say you track a bunch of keywords within a particular cohort and you see that most of the results have a featured snippet. STAT will show you exactly what you own and what you don’t own. Now what’s cool about this is you can click into what you don’t own and you can see the exact featured snippets that your competitors own that you can actually create some content strategy around and try and go steal those.

A different way is images or news. So let’s say that you notice that you’re selling TVs or something like that and almost all the SERPs have images and you don’t own any of them. So something like that can inform your content strategy, where you go to your team and you say, “Hey, folks, we need to create more images, or we need better structured data to get Google to show the images because this is the intent for this type of keyword, and we’re simply not owning it in this way.”

Same thing with news. If you notice a lot of news results and you’re not a news organization but you’re competing for these keywords, that can inform your content strategy and maybe you need to go after those news keywords or try something else. Video is another one. More and more SERPs have video results with video carousel and things like that. You can see exactly what you own and what you don’t own.

A lot of times you’re going to find that certain domains are beating you on those videos and that may inform, especially for the high volume keywords that you want to go after, you may want to be creating more video content for that. But it all depends on the SERP, and you’re going to find different feature sets and different combinations for every keyword cohort that you do.

So what’s important to you and what’s important to track it’s going to show up differently every time, but it’s going to show you exactly where the opportunities are. FAQs are another thing, rich snippets sort of results. You may find that your competitors are all using FAQ markup. You’re not using any. That could inform your SEO strategy, and you might start incorporating more FAQs because Google is obviously rewarding those in the SERPs and your competitors are gaining those and not you.

Other things, virtually any SERP feature that’s trackable. You can find local results. Twitter boxes. You may find that for certain queries Google is surfacing Twitter results and maybe that means you need to be on Twitter more than you actually are right now and see who’s ranking for those results instead of something that you’re doing on-site.

Maybe it’s you need to do more YouTube. It’s not all necessarily on your site. But this will tell you where you need to invest those opportunities. Review stars, podcasts, and more. All of this will tell you what’s important and where the opportunities are and where you’re winning and losing and the exact keywords that you can go after if you want to win and the exact feature sets where your competitors are getting traffic and you aren’t.

So I use STAT, I love it, every week. It’s a great tool. If you want to try it out, I encourage you to do so. That’s it for me. Thanks, everybody.

Video transcription by Speechpad.com. 

Google has announced plans to transition all retailers to its updated Merchant Center platform by September.

This move will affect e-commerce businesses globally and comes ahead of the holiday shopping season.

The Merchant Center is a tool for online retailers to manage how their products appear across Google’s shopping services.

Key Changes & Features

The new Merchant Center includes several significant updates.

Product Studio

An AI-powered tool for content creation. Google reports that 80% of current users view it as improving efficiency.

This feature allows retailers to generate tailored product assets, animate still images, and modify existing product images to match brand aesthetics.

It also simplifies tasks like background removal and image resolution enhancement.

Centralized Analytics

A new tab consolidating various business insights, including pricing data and competitive analysis tools.

Retailers can access pricing recommendations, competitive visibility reports, and retail-specific search trends, enabling them to make data-driven decisions and capitalize on popular product categories.

Redesigned Navigation

Google claims the new interface is more intuitive and cites increased setup success rates for new merchants.

The platform now offers simplified website verification processes and can pre-populate product information during setup.

Initial User Response

According to Google, early adopters have shown increased engagement with the platform.

The company reports a 25% increase in omnichannel merchants adding product offers in the new system. However, these figures have yet to be independently verified.

Jeff Harrell, Google’s Senior Director of Merchant Shopping, states in an announcement:

“We’ve seen a significant increase in retention and engagement among existing online merchants who have moved to the new Merchant Center.”

Potential Challenges and Support

While Google emphasizes the upgrade’s benefits, some retailers, particularly those comfortable with the current version, may face challenges adapting to the new system.

The upgrade’s mandatory nature could raise concerns among users who prefer the existing interface or have integrated workflows based on the current system.

To address these concerns, Google has stated that it will provide resources and support to help with the transition. This includes tutorial videos, detailed documentation, and access to customer support teams for troubleshooting.

Industry Context

This update comes as e-commerce platforms evolve, with major players like Amazon and Shopify enhancing their seller tools. Google’s move is part of broader efforts to maintain competitiveness in the e-commerce services sector.

The upgrade could impact consumers by improving product listings and providing more accurate information across Google’s shopping services.

For the e-commerce industry as a whole, it signals a continued push towards AI-driven tools and data-centric decision-making.

Transition Timeline

Google states that retailers will be automatically upgraded by September if they still need to transition.

The company advises users to familiarize themselves with the new features before the busy holiday shopping period.

Featured Image: BestForBest/Shutterstock

You’ve spent hours learning the most effective SEO tactics, but they won’t be useful if you can’t measure them.

Measuring SEO return on investment (ROI) involves two factors: KPIs (key performance indicators) and the cost of your current SEO campaigns. Tracking these key metrics monthly enables you to tweak and optimize your strategy, as well as make educated business decisions.

To get the most bang for your buck (or time), consider using Google Analytics (GA) to calculate your ROI. With GA, you can pinpoint where your audience is coming from, set goals to stay on track, and incorporate the most attractive keywords to rank better in search engines.

Ways to calculate your SEO ROI using Google Analytics
#1 Page value

Page value is an important aspect to consider when talking about ROI.

Think about it like money. In the US, paper money has been dated back to the late 1600s as a way of symbolizing the value of something. Instead of bartering, citizens began attaching a value to a 10 dollar bill or a 100 dollar bill to obtain an item they needed that was worth the equivalent value.

Page value assigns an average monetary value to all pages viewed in a session where a transaction took place. Specifically for e-commerce sites, it helps assign a value to non-transactional pages such as articles and landing pages. This is useful to understand because although a blog didn’t necessarily produce revenue, that doesn’t mean it didn’t contribute to a customer’s buying decision in the future.

With lead generation pages, a value can be assigned to a goal like the contact form submission, so you can more accurately measure whether or not you’re on track.

Below is a visual that depicts how page value is calculated according to Google:

In the first example, Page B is visited once by a user before continuing to the Goal page D (which was assigned a value of $10) and Receipt page E (which generated $100). That means a single pageview of Page B generated $110, which gives us its Page Value.

In equation form, this is how it looks:

Page Value for Page B =E-commerce Revenue ($100) + Total Goal Value ($10)Number of Unique Pageviews for Page B (1)= $110

But not all pageviews lead to a conversion. That’s why it’s important to keep track of data and recalculate your Page Value as more information comes in. Let’s see how this works with the second example.

Here we see two sessions but only one converted to an e-commerce transaction (session 1). So even if we have two unique pageviews for Page B, the e-commerce revenue stays the same. We can then recalculate our Page B’s Page Value using this new information.

Page Value for Page B =e-commerce revenue ($100) + Total Goal Value ($10 x 2 sessions)Number of Unique Pageviews for Page B (2)= $60

With more sessions and more data, you’ll get a better idea of which pages contribute most to your site’s revenue.

#2 E-commerce settings

If you’re not managing an e-commerce business, skip this section. For those of you who do, there’s a more advanced feature on Google Analytics that can prove extremely useful. By turning on the e-commerce settings, you can track sales amounts, the number of orders, billing locations, and even the average order value. In this way, you can equate website usage to sales information and better understand which landing pages or campaigns are performing the best.

How to turn on e-commerce settings

In your Google Analytics left sidebar panel, click on ADMIN > under the VIEW panel (rightmost panel), click on “E-commerce Settings” > Enable E-Commerce > Enable Enhanced E-commerce Reporting.

To finalize this go over to where it says, “Checkout Labeling” underneath the Enhanced E-commerce settings, and under “funnel steps” type in:

Checkout view

Billing info

Proceed to payment

Below is a picture to better explain these steps:

If you have Shopify or Woocommerce, make sure to set up tracking over there, too, so that Google Analytics can communicate and relay this crucial information to you.

Once you have the E-commerce tracking setup, you’ll have access to the following data:

An overview of your revenue, E-commerce conversion rate, transactions, average order value, and other metrics

Product and sales performance

Shopping and checkout behavior

These give you a better understanding of how your customers are interacting with your site and which products are selling the most. In terms of calculating SEO ROI, knowing the steps that your customers take and the pages they view before making a purchase helps you analyze the value of individual pages and also the effectiveness of your overall SEO content strategy.

#3 Sales Performance

Again, this is for e-commerce only. The sales performance feature shows sales from all sources and mediums. You can view data for organic traffic only and identify its revenue.

How to view your sales performance

This gives you an overview of your revenue and a breakdown of each transaction. Tracking this through time and seeing how it trends guides your content strategy.

What is the average transaction amount and what does it tell you about your customers? Does tweaking your copy to promote up-sells or cross-sells have an impact on your per-transaction revenue?

Another set of data that helps you calculate your SEO ROI and optimize your content strategy is your customers’ shopping behavior.

How to see your customers’ shopping behavior in-depth

At a glance, you can see how effective your purchase funnel is – how many sessions continue from one step to the next? How many people went to your page and didn’t purchase, or added to the cart but didn’t follow through with payment?

This helps you identify areas that need more SEO attention. This also helps you draw projections on how much your revenue can increase by optimizing your copy and implementing SEO to boost organic traffic, which helps you get a better idea of your SEO ROI.

For instance, if there’s a high percentage of users visiting your page but not going through the buying cycle, maybe you need to tweak your copy to include searchable keywords or copy that resonates better with your audience.

Additionally, it’s worth remembering that while this does show organic sales, you can’t identify the keyword that led to that sale, but organic traffic can be an indicator of holistic marketing efforts working. For example, PR may increase brand searches on Google.

Quick tip: you can get an idea of which keywords bring in the most traffic to your website with Google Search Console and then follow the navigation history from Google Analytics in order to connect specific keywords with sales.

Overall, to truly measure the ROI of your SEO you need to discover which keywords are working for your business, because although people may be interested in your business due to some amazing PR exposure, they might not actually be interested in your services. To really hit this one home, select keywords that have purchase intent. That way you can attract more qualified leads to your site.

#4 Engagement Events

If you’re not working on an e-commerce site (hint, hint, my fellow B2B marketers), here’s where you’ll want to pay attention. Both e-commerce and lead generation sites can make use of engagement events.

Align with your sales team to assign a value to a goal based on average order value, the average number of sign-ups, and conversion rate. Although useful for e-commerce, these analytics are likely to be most beneficial for lead generation sites who have longer sales cycles and transactions that occur off-site or after multiple sessions (for example, B2B SaaS or a marketing agency).

Examples of engagement events include:

Newsletter sign up

Contact form submission

Downloads

Adding to a cart

How to view your campaign engagement data

Below is an image so you can follow along:

This type of tracking gives greater insight into how people are interacting with parts of your website, and how engaged they are at different parts of the journey. Use it to set goals for your lead generation and investigate whether or not your SEO efforts are paying off.

Let’s say you find that your website gets a ton of traffic to your services page, and a high percentage of those visitors download a case study. This means they’re interested in what you have to offer and would like to see more case studies from you.

Use ROI calculations to make better strategic decisions for your business

Ultimately, when using Google Analytics for SEO, you should work to align business goals with specific measurable metrics so that you can create a long-term plan for sustainable growth. It’s no secret SEO is a powerful tool for your business, but putting it into an actionable and personalized plan to get the train continuously going uphill is what counts.

Responsive search ads are very flexible ads that automatically adapt to show the right message to the right customer. You enter multiple headlines and descriptions when creating the ad. Google’s machine learning systems will mix headlines and descriptions and test different combinations of the ads to learn which performs best over time. The most relevant message will be shown to the customer.

Responsive search ads are the default ad type in Google Ads Pay Per Click (PPC) search campaigns as of February 18, 2021. This change isn’t surprising, considering Google’s increased focus on automation in Google Ads.

Since responsive search ads adapt their content to show the most relevant message to match customer search terms, they help you reach more customers and may help to increase conversion rates and campaign performance. According to Google, advertisers who use responsive search ads in their ad groups can achieve an increase of up to 10% more clicks and conversions as compared to standard text ads.

But responsive search ads have many more benefits:

Here is an example of a responsive search ad from Google search results:

How to set up responsive search ads in your Google Ads PPC search campaign

Sign into your Google Ads PPC account and select Responsive Search Ad from the Ad menu:

Select Ads and extensions in the left menu

Click on the blue plus button on the top

Select Responsive Search Ad in the menu

Now you can enter the headlines and descriptions and the landing page for the responsive search ad:

Select a Search Campaign

Select an Ad Group

Enter the Final URL ( this is the landing page URL).

Enter the display paths for the Display URL (this is optional).

Enter at least 5 unique headlines. The minimum is 3 and the maximum is 15. The tool will suggest keywords from the ad group to include in the headlines.

Enter at least 2 unique descriptions. The minimum is 2 and the maximum is 4.

As you create the ad, an ad strength indicator will indicate the ad strength.

As you type the ad, you will see a preview of the Ad in different combinations in the preview panel.

Save the ad

Follow the best practices below to optimize responsive search ads for better performance.

5 best practices when using responsive search ads in your Google Ads PPC search campaigns

These tips will help you optimize your responsive search ads in your Google Ads search campaigns and increase clicks and conversions.

1. Add at least one responsive search ad per ad group with “good” or “excellent” ad strength

Google recommends adding at least one responsive search ad per ad group. Use the ad strength indicator to make sure the responsive search ad has a “good” or ”excellent” ad strength, as this improves the chances that the ad will show. Remember, the maximum number of enabled responsive search ads allowed per ad group is three.

It’s best to create very specific ad groups based on your products with at least three quality ads, as recommended by Google. This enables Google’s systems to optimize for performance and may result in more clicks.

2. Add several unique headlines and descriptions

The power of the flexible format of responsive search ads lies in having multiple ad combinations and keywords that can match customer search terms. This helps to increase search relevance and reach more customers.

When building your responsive search ads, add as many unique headlines as you can to increase possible ad combinations and improve campaign performance.

The headlines and descriptions in a responsive search ad can be shown in multiple combinations in any order. It’s therefore important to ensure that these assets are unique from each other and work well together when they are shown in different ad combinations.

When creating a responsive search ad, you can add up to fifteen headlines and four descriptions. The responsive search ad will show up to three headlines and two descriptions at a time. On smaller screens, like mobile devices, it may show with two headlines and one description.

Here are tips for adding headlines and descriptions:

1. Create at least 8-10 headlines so that there are more ad combinations to show. More ad combinations helps to increase ad relevance and improve ad group performance.

To increase the chances that the ad will show, enter at least five headlines that are unique from each other. Do not repeat the same phrases as that will restrict the number of ad combinations that are generated by the system.

You can use some headlines to focus on important product or service descriptions.

Include your popular keywords in at least two headlines to increase ad relevance. As you create the responsive search ad, the tool will recommend popular keywords in the ad group to include in headlines to improve ad performance.

Make sure that you DO NOT include keywords in three headlines so that more ad combinations are generated. Instead you can highlight benefits, special services, special hours, calls to action, shipping and return policies, special promotions, taglines, or ratings.

Try adding headlines of different lengths. Do not max out the characters in every headline. Google’s systems will test both long and short headlines.

There are 30 characters for each headline.

2. Include two descriptions that are unique. The maximum is four descriptions.

Descriptions should focus on describing product or service features that are not listed in the headlines, along with a call to action.

There are 90 characters for each description.

An example of creating a responsive search ad with headlines and descriptions is shown in the figure below.

3. Use popular content from your existing expanded text ads

Use headlines and descriptions from your existing expanded text ads in the ad group when writing your headlines and descriptions for the responsive search ads. This helps you get more ad combinations with keywords that have already been proven to be successful in your marketing campaign.

4. Pin headlines & descriptions to specific positions to control where they appear. Use sparingly.

Responsive search ads will show headlines and descriptions in any order by default. To control the positions of text in the ad, you can pin headlines and descriptions to certain positions in the ad. Pinning is a new concept introduced with responsive search ads.

According to Google, pinning is not recommended for most advertisers because it limits the number of ad combinations that can be matched to customer search terms and can impact ad performance.

Use the pinning feature sparingly. Pinning too many headlines and descriptions to fixed positions in the responsive search ad reduces the effectiveness of using this flexible ad format to serve multiple ad combinations.

1. If you have text that must appear in every ad, you should enter it in either Headline Position 1, Headline Position 2 or Description Position 1, and pin it there. This text will always show in the ad.

2. You can also pin headlines and descriptions that must always be included in the ad to specific positions in the ad. For example, disclaimers or special offers.

3. To pin an asset, hover to the right of any headline or description when setting up the Ad and click on the pin icon that appears. Then select the position where you want the headline or description to appear.

4. Pinning a headline or description to one position will show that asset in that position every time the ad is shown. For increased flexibility, it is recommended to pin 2 or 3 headlines or descriptions to each position. Any of the pinned headlines or descriptions can then be shown in the pinned position so that you still have different ad combinations available.

5. Click Save.

The image below shows a headline pinned in position 1 and a description pinned in position 2. The Ad will always show this headline and description in the pinned positions every time it runs.

5. Increase ad strength to improve performance

As you create a responsive search ad, you will see an ad strength indicator on the right with a strength estimate. The ad strength indicator helps you improve the quality and effectiveness of your ads to improve ad performance.

Improving ad strength from “Poor” to ‘Excellent’ can result in up to 9% more clicks and conversions, according to Google.

1. Ad strength measures the relevance, diversity and quality of the Ad content.

2. Some of the ad strength suggestions include

Adding more headlinesIncluding popular keywords in the headlinesMaking headlines more uniqueMaking descriptions more unique

3. Click on “View Ideas” to see suggestions provided by the tool to improve ad relevance and ad quality.

4. The ad strength ratings include “Excellent”, “Good”, “Average” , “Poor” and “No Ads”.

5. Try to get at least a “Good” rating by changing the content of headlines or descriptions or by adding popular keywords. If you have a lot of assets pinned to specific positions, try unpinning some of the assets to improve ad strength.

Are expanded text ads still supported?

Expanded text ads are still supported but they are no longer the default ad format in Google Ads paid search campaigns.

You can still run expanded text ads in your ad groups along with the responsive search ads. Google recommends having one responsive search ad along with two expanded text ads in an ad group to improve performance.

However, Google has removed the option to add a text ad directly from the Ads and extensions menu. When you add a new ad, the menu now lists only options to add a Responsive Search Ad, Call Ad, Responsive Display Ad and Ad variations.

You can still add an expanded text ad although you cannot add it directly from the Ads and extensions menu. Follow these steps,

In the Ads and extensions menu, click to select Responsive search ads.

This opens up the editing menu to create a responsive search ad.

Then click on “switch back to text ads” on the top to create a text ad.

The removal of expanded text ads from the Ad and extensions menu certainly suggests that Google may be planning to phase out expanded text ads in the future. However, they continue to be supported at this time.

Conclusion

In summary, responsive search ads continue the progression towards automation and machine learning in Google Ads. We have used responsive search ads in PPC search campaigns at our digital marketing agency, and have seen an increase in clicks and CTR as compared to expanded text ads.

You can improve the performance of your Google Ads PPC search campaigns by following these five best practices for responsive search ads:

Add at least one responsive search ad per ad group.

Add several unique headlines and descriptions.

Use popular content from your expanded text ads.

Pin some of the assets to control where they appear in the ad.

Increase ad strength to at least a “good” rating to improve ad performance.

Other best practices recommended by Google include:

Have other optimization tips? Share them with #MozBlog on Twitter or LinkedIn.