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How to Avoid Mistaking Correlation for Causation in SEO



Every so often the SEO community will erupt into an uproar at the publication of a new ranking factors study.

The usual cry – “correlation is not the same as causation!”

You may be familiar with the terms.

Correlation is the “mutual relation of two or more things” and causation is “the action of causing or producing.”

Essentially, is something genuinely the cause of a result, or does it just happen to change in line with the result?

To put it clearly, here is an unusual example of correlation.

Tyler Vigen - Mozzarella consumption civial engineering doctorates graph

According to the data gathered by from the U.S. Department of Agriculture and National Science Foundation, there is a direct correlation between the number of Civil Engineering doctorates awarded in the U.S. and the per-person consumption of mozzarella cheese.

That’s right.

Want more civil engineers to graduate in the U.S.?

You’d better start eating more cheese.

We can all quickly identify that it’s likely being a coincidence rather than a causal link.

This is a good example of correlation not being the same as causation.

Why Are Correlation & Causation a Concern in SEO?

A lot of SEO activity is based on trial and error, experience, and statements from search engine representatives.

Due to this, there are often assertions made like “SEO activity X has a positive effect on your webpage rankings.”

For example: “links from authoritative websites will improve your website’s SERP rankings.”

Sometimes, these will be accurate – the stated activity will be what has caused the ranking increase.

Other times, it is purely coincidental.

The issue with this is that there can be substantial time and money invested in carrying out SEO activities that will never pay off.

For instance, what if there was an SEO study that suggested the number of JPEGs on a page was a ranking factor.

This hypothetical study suggested that the more JPEGs the higher you are likely to rank in Google.

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This might cause SEO professionals to start adding images to their pages regardless of whether they would benefit the end-user.

And paying for photographs or a premium image service could be expensive.

No to mention the time taken to upload the images to every page could also be costly.

How to Avoid Mistaking Correlation for Causation

How then do you decide if Y is affected by X, or if changes are mere coincidences?

Consider the Claim

First of all, consider what is being claimed.

Sometimes a commonsense check of what is being discussed will be enough to determine whether the correlation is a coincidence.

The following two questions can go a long way to working this out:

  • How could the search engines measure this?
  • How would it benefit the end user and therefore the search engines?

This is not an exhaustive list.

The cynical us might ask, “would this financially benefit the search engine?”

Or you might wonder, “would this be the case for my industry?”

It might be that a supposed ranking factor would not make sense for the industry you are in.

For instance “your money or your life” (YMYL) pages, ecommerce, or entertainment sites might have been subject to different weightings for different ranking factors.

What Does Your Experience Say?

Have you experienced SEO results in a way that rings true with the causation statement made?

Your experience is just as valid as anyone else’s.

If you have seen the opposite happen – for instance, removing unnecessary JPEGs from a page caused your page’s ranking to increase – then that is reason enough to investigate the claim further.

Identify Other Factors

With the example given above, there might be other reasons why adding JPEGs to a page correlated with an increase in SERP rank for a page.

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For instance, maybe the images included alt attributes and that was actually what made the difference in rank.

Perhaps the images were part of a page’s redesign and other elements like unique copy were also introduced at the same time.

It’s also hard with studies run by third parties to know the true methodology.

Perhaps there were other variables in play that the researchers did not account for.

That alone could call into question the validity of the experiment.

How Big Is the Sample?

When running statistical experiments a researcher will be looking for results that have reached a statistical significance.

That is, an assurance that the relationship between X and Y did not occur through chance.

In order to achieve a reliable level of statistical significance, your sample size has to be large enough.

If your sample size is not large enough your experiment may be subject to a sampling error.

A correlation may emerge that would simply not be there in a larger sample size.

In our example, what if only three websites were used as part of the study into how JPEGs affect rankings.

If two of them had seen ranking increases when adding JPEGs to a page and one of them did not then you could conclude that JPEGs have a positive effect on rankings.

However, what if you added a further seven websites to your study, and each of those did not show an increase in rankings when JPEGs were added to the page.

That would bring the result to two which showed rank increases and eight that did not.

What would happen to the results with another 10 websites?

Three is simply too small a sample size to make declarations about all the websites in the search engine index.

How Varied Is the Sample?

Similarly, if your sample is not a diverse enough representation of the entire data set then you risk sampling errors.

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For instance, what if the websites chosen for our hypothetical study were all ecommerce sites.

Would it be a reliable enough experiment to apply those findings to information only sites?

Could they be applied to YMYL sites?

What if the websites sampled were all built on WordPress?

Would it be a fair conclusion to assume that websites running on Magento would rank in a similar way?

A Caution on Third-Party Studies

It is very easy to see studies shared around the likes of Twitter and LinkedIn and assume the study is thorough.

Similarly, listening to a speaker share their case study at a conference may inspire confidence that their conclusions are valid.

You can’t be sure of this, however.

A third party study may have experimental flaws.

One case study is too small a sample size.


Whenever you hear a claim about what is or isn’t important in SEO and there is data used to back it up, make sure you bring yourself back to your school science experiments.

Was there a large enough sample used?

Were all the variables accounted for and controlled?

Would you get an “A” grade for that study?

If there is any doubt then make sure you do not take the conclusions as fact.

Instead, continue to experiment on your own.

Monitor the effect of any changes you make to your sites to see if they have the result you expected.

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Image Credits

Screenshot taken by author, October 2020

Search Engine Journal


Google Autocomplete: A Complete SEO Guide



Google Autocomplete: A Complete SEO Guide

Google Autocomplete is a controversial but powerful search feature.

When you type a word, or even a letter, into Google, it populates a list of search suggestions. That’s what autocomplete is.

SEO professionals, paid search marketers, content marketers, and social media managers can all benefit from using Google Autocomplete to help with different keyword-focused and intent-exploring projects.

On the other hand, Google Autocomplete often makes the news for funny, peculiar, or even offensive habits (often in a negative way).

People use autocomplete constantly, saving thousands of seconds per day, but it has also been blamed for political cover-ups and spoiling movies, TV shows, and video games.

Google Autocomplete can also be a powerful marketing tool. SEO professionals and other digital marketers have used it for years to inform strategy, get keywords, and find the important questions customers are asking.

They can use Autocomplete to better optimize clients’ digital properties and the content and messaging that make them up.

This guide will help you understand the real power this simple but super-helpful feature can do for help with your day-to-day tasks.

What Is Google Autocomplete?

Google’s own words, Google Autocomplete is “designed to make it faster to complete searches that you’re beginning to type.”

It’s integrated across Google Search and other Alphabet properties that use Google, including in the “Omnibox” on Chrome.

Google estimates that, cumulatively, it saves over 200 years of typing every day, and on average reduces typing overall by about 25 percent.

The primary purpose of the Autocomplete dropdown is to cut back on time a user spends typing by offering predictions of what a user may be typing — including for websites using the built-in Google Custom Search Engine feature.

While Autocomplete has been a desktop search feature since late 2004, it has become even more useful as a time-saving feature on mobile devices.

Typing on a mobile device is a bit tougher than doing so on the large keyboards we have grown up with and are accustomed to, so it’s a welcomed tool for providing assistance and saving time for many.

There are several other useful ways that the feature can be used to leverage content ideas, keyword suggestions, intent exploration, online reputation management, and other data-driven tasks.

How Does Autocomplete Work?

Ex-Googler Kevin Gibbs created the project, originally called “Google Suggest” by another former Googler Marissa Mayer.

Google has since moved away from the “Suggest” name since it’s not always offering the most thoughtful, caring, or appropriate predictions.

Google calls the completions it offers “predictions”, not “suggestions.” This is because of how Autocomplete works.

Autocomplete is supposed to help people complete a sentence they were intending – not to suggest a search intent, as with “I’m feeling lucky.” They determine predictions by looking at common searches on Google, including looking at trending searches that might be relevant.

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This allows Autocomplete to quickly update and adapt to new search trends and news stories.

Much of Autocomplete’s behavior is computer-generated, with data collected from millions of other Google searches and their results, including the content on those pages. It also takes information from your search history, location, and other data points.

Google has also put a lot of work in, so as to avoid inappropriate or offensive autocomplete suggestions. This means there are both automated and manual removal procedures that can influence what autocomplete suggestions are left.

Autocomplete is also related to the Knowledge Graph, and especially on mobile, it can bring Knowledge Graph suggestions into the prediction.

It wasn’t until 2008 that Google built Autocomplete into its default search engine (it was previously an opt-in feature).

Best Ways to Use Google Autocomplete

1. Keyword Research

It’s a long, tedious, and laborious task, but it’s also the foundation of all SEO strategies– and has been for a long time.

While we may no longer explicitly target keywords, keywords and their related ideas are always going to be an important part of search marketing.

Keyword research is one of the first tasks tackled at the start of an engagement — and carried on throughout the engagement — to understand not just a brand and the content it creates, but also its potential shortcomings, website strengths and weaknesses, and content gaps.

Autocomplete doesn’t do all the work for you in terms of keyword research, but it’s a great place to start at or to use early and often when developing content calendars and general organic search strategies.

Using it (along with other keyword resource tools like Google Keyword Planner and other third-party keyword databases) to get an idea of the right keywords you want to target by considering monthly search frequency, competition, and even cost-per-click (CPC) pricing will do your search strategy justice.

One of the shining advantages of Google Autocomplete is its ability to uncover quality long-tail phrases that are commonly searched across the web.

Since the primary measure for Autocomplete is popularity — based on real searches by users in real-time — the value of Autocomplete lies in its plethora of keyword-level data that you can dig up if you work at it hard and long enough.

As always, be sure you are signed out of Google to ensure you limit personalization for an unbiased look at predictions.

Long-tail keywords are incredibly useful when fulfilling content gaps but also offer endless possibilities in terms of high-value blog posts and educational content within a brand’s niche.

2. Intent Exploration

Understanding user intent is important because it guides the goal of the page, its messaging, its layout, and even imagery. We know pages perform best when they fully satisfy the user intent of a search query.

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You can use Autocomplete to better understand user intent, but doing so can be involved and laborious. Taking the time to visit many different web pages in the search results tied to specific predictions is going to take some time, focus, and content consumption. But the information you can mine from this method is invaluable.

Keywords overlap various stages of user intent, and without more keyword context, it can be tough to understand the intent.

Autocomplete will help you not just understand different high-value long-tail keywords and the intent surrounding them, but it will also help marketers recognize the volume of content around specific stages of intent, as well as which long-tail phrases and intent stages could be optimized for as a higher priority.

Of course, for high-value keywords — long-tail or traditional one-, two-, and three-word phrases — it’s important to satisfy all stages of intent as they relate to the high-value keywords.

That’s the idea behind an all-encompassing, quality search strategy. And Autocomplete can help get you there.

3. Online Reputation Management

Autocomplete has been significant in the realm of online reputation management, too.

Remember, when a user searches for your name or your brand name, the first thing they see, even before your site on the SERP (search engine results page), is the Autocomplete predictions tied to that name.

If those predictions are negative, or if even just one of them is negative, it can have a real impact on your business’s performance.

Think about it. You search [Dog Washers Inc] and the first prediction finishes with “loses dog,” you probably won’t feel too keen on bringing your dog there for his next bath.

Same for a restaurant; if you search [Ted’s Seaford Spot] and the prediction finishes with “e. Coli,” I have a pretty good idea of what you’re not eating tonight.

Autocomplete makes up an important part of online reputation management (ORM) and cannot be ignored when working to balance all negative connections made with brands.

One must be vigilant, just like most ORM strategies. Several ways brands can work to offset negative Autocomplete predictions are:

  • Take control of your brand’s conversations to ensure the right connections are being made in Google Autocomplete.
  • Social media account optimization reinforces the positive connections that may be overshadowed by negative ones.
  • Social media content, messaging, and engagement are in line with the optimizations above and the brand’s voice and tone.
  • Consistent branding and messaging for profile websites with positive keywords association used elsewhere
  • Starting small and making an impact by searching for positive connections for the brand from different locations. Obviously, the more people, the better. But you’d be surprised at the impact it can have.
  • Building backlinks to Google SERPs for positive keyword associations with your name; things like [sam hollingsworth seo writer] and [sam hollingsworth handicapper] would be great starts for someone like myself. 😊
  • If there are negative autocomplete suggestions, ensure that you have a strategy of how to address them.
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4. Content Generation and Exploration

You can also now use Autocomplete for content generation and exploring competitor content for your own content ideas. It’s easy, and interesting, to use Autocomplete alongside other online writing tools, to find out what web users are searching for.


Just looking at “who”, “what”, “where”, “when”, and “why” with a few brand-related questions can get you a ton of questions for your FAQ– questions people may already be searching for.

Related keywords

You can do this in many ways, for many reasons. An easy one is “brand name vs.”– Google will autofill with competitors. You can also look at “brand name and” and see what autocomplete finds there– finding ways to expand your brand.

Related topics

If you can find Autocomplete suggestions for related topics, that aren’t covered by your main topic, you might have an edge to grow some content in that niche.

Queries like “how * works” can be invaluable, autocomplete filling in the wildcard space with suggestions. You can also do this to find questions about your brand, questions for content marketing, find problems potential customers are looking for, and even find out if users are looking for certain social media accounts.

Screenshot of Google Search, November 2021

Autocomplete Policies

With a history of backlash due to some of its search predictions, Google does manually work to prevent inappropriate Autocomplete predictions when it comes to:

  • Sexually explicit predictions.
  • Hateful predictions against groups and individuals.
  • Violent predictions.
  • Danger and harmful activities in predictions.

It also may remove predictions that could be considered spam, facilitate or advocate piracy, or if given a legal request to do so.

Google makes it clear that it removes predictions that relate to any of the above-mentioned situations unless they contain medical or scientific terms that are not malicious.

Looking for Feedback

To better control inappropriate Autocomplete predictions, Google launched its feedback tool and uses the data to make improvements consistently.

For instance, there doesn’t have to be a particular demographic that is being targeted by something hateful in nature; and feedback helps get that discovered faster and easier.

google-autocomplete-report-inappropriateScreenshot of Google Search, November 2021

Understanding what people are actually searching for is an essential part of your SEO strategy.

See how you can incorporate Google Autocomplete into your research process. You just might be surprised at the specific keywords and search intent it reveals!

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Featured image: Shutterstock/Fonstra

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How To Use Amazon Attribution & Brand Referral Bonus Programs



How To Use Amazon Attribution & Brand Referral Bonus Programs

Perhaps you’ve heard of the Amazon Attribution and Amazon Brand Referral Bonus programs and are wondering how they can help build your business.

As the cost per click (CPC) on Amazon rises, and the platform takes a stronger stance against black hat ranking tactics, more sellers have been looking at ways to drive external traffic to their Amazon product detail page.

Additionally, some brands – particularly those without a Direct to Consumer (DTC) website or those wanting to use sales from external traffic sources to help the organic rankings on the ecommerce giant – will turn to advertise off Amazon to help drive the conversions needed to get those rankings.

In the past, the disadvantage of sending external traffic to Amazon was that there wasn’t a way to track that traffic’s results and conversion rates.

Amazon does not allow adding pixels to their product detail pages, so it was difficult to determine the effectiveness of external campaigns driven to Amazon.

On top of the lack of transparency into how your external traffic was performing, you also had to consider the cost of Amazon’s fees on top of the cost of ads in your profitability calculations.

To address this issue, Amazon has introduced two programs that work together to help you see how external traffic is performing and get credit back on the fees for products you sent to Amazon.

These programs are the Amazon Attribution and the Amazon Brand Referral Bonus.

Why Drive External Traffic To Amazon?

In general, it is best to drive traffic to your product detail page from within the Amazon Advertising platform because of the increased visibility of campaign performance and the lower cost for many products.

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However, there are times where it does make sense to drive external traffic to Amazon.

Amazon’s Top of Funnel advertising products are still in their infancy, and some of the targeting is not as advanced as what you can find on other platforms.

There are instances where there are more opportunities to advertise effectively to specific demographics or targeting sets outside of Amazon, such as Facebook, Google, or Instagram.

Additionally, most of Amazon’s advertising products severely limit the amount of creative you can include in your ads.

For many Amazon advertising ad types, primary creatives are from the listing itself. Therefore, it can be difficult to craft ads customized for different audiences or provide education or brand awareness for products.

Ads created off of Amazon generally allow for more freedom in creative images and text.

In general, sending external traffic to Amazon can be more expensive because, in addition to paying the external costs of the ads, you’re also paying the Amazon fees.

This additional cost means you’ll need a higher return on ads spent to be profitable.

This will not be an option for every seller or every type of product. But if your margin allows for it, we have seen an increase in overall sales and profitability when done right.

Amazon Attribution With Brand Referral Bonus Program

For those cases where it makes sense to send traffic from outside Amazon, there are two programs that can help you increase visibility on your campaigns and reduce the overall cost.

The Amazon Attribution program has been available for a couple of years. It enables you to drive external traffic and see specific data on the traffic results that you send to Amazon.

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On July 2021, Amazon introduced the Brand Referral Bonus program.

With this program, when you drive external traffic, Amazon will discount the referral fees you pay for the products you sell with the traffic you sent to your product detail page on Amazon.

Remember that to use the Brand Referral Bonus program, you must first be involved in the Amazon Attribution program and Brand Registry.

Below are the details of both programs.

Amazon Attribution Program

This program allows you to track specific metrics of traffic sent with an Amazon attribution link.

As part of the program, Amazon creates the custom link that tracks specific metrics generated because of the traffic you sent to your product detail page.

Amazon states that:

“Attribution Reports include clicks, as well as Amazon conversion metrics, such as detail page views, Add to Cart, and purchases. Reporting is available via downloadable reports and within the console.”

To participate in this program, you have to enroll in Amazon’s Brand Registry program. If you do not have a live trademark, you can participate in the Amazon IP Accelerator program.

The way the Amazon Attribution works is you are assigned a custom link and given a 14-day last-touch, cross-device attribution model.

Screenshot by author, January 2022

Amazon Brand Referral Bonus Program

The Amazon Brand Referral Bonus is actually a subset of Amazon Attribution. Amazon states that, on average, brands earn 10% from their qualifying sales.

The way that the program works is when you send external traffic through this program in conjunction with the Amazon Attribution, you will receive a credit back on referral fees that you would incur as your products sell on the Amazon platform.

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The amount of referral fee credit you receive will be based on the category of your product, the same way that the referral fees themselves are calculated on the platform.

There’s up to a 14-day attribution window depending on the type of ad.

Keep in mind that after the sale has occurred on Amazon, there’s a two-month wait period before the bonus is allotted to your account.

For example, if your sale occurred in December, you would not receive the compensation into your Seller Central disbursement until February.

This allows for customer returns and cancellations.

How To Sign Up For Amazon Attribution

The first step to signing up for these two programs is to make sure that you are enrolled in the Brand Registry program or IP Accelerator program, depending on your specific situation.

You will need a live trademark to participate in the Amazon IP Accelerator to potentially expedite the trademark for your brand or product.

Then, you need to have an active Amazon account and enroll in the Amazon Attribution. Once you have completed these steps, you can register for the Brand Referral Bonus program.

If you are looking for more detailed instructions on how the Amazon Attribution and its metrics work, you can take the free course located in the Amazon Learning Console.

This will walk you through the program, set up, and interpret the data.

Working together with internal Amazon ads, external ads can be a strong strategy for products in competitive categories or new-to-category products to increase overall sales and/or product adoption.

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Google Search Console Updated With Desktop Page Experience Report



Google Search Console Updated With Desktop Page Experience Report

Google Search Console has a new report dedicated to evaluating Page Experience criteria on the desktop versions of webpages.

This report can help you prepare for the launch of the page experience algorithm update on desktop, which will begin rolling out in February and finish at the end of March.

In an announcement on Twitter, Google states:

“To support the upcoming rollout of page experience ranking to desktop, Search Console now has a dedicated desktop section in its Page Experience report to help site owners understand Google’s ‘good page experience’ criteria.”

The desktop report can be accessed from the Page Experience tab in Search Console, directly underneath the mobile report.

It looks identical to the mobile report, with the exception of the Mobile Usability section.

Mobile Usability is not among the criteria for achieving a “Good” page experience score on desktop, so it has been omitted from the report.

Aside from Mobile Usability, the page experience update on desktop is built using the same ranking signals as the mobile update.

More About Google Page Experience On Desktop

Google has confirmed the three Core Web Vitals metrics: LCP, FID, and CLS, and their associated thresholds will apply for desktop ranking.

Other aspects of page experience signals, such as HTTPS security and absence of intrusive interstitials, will remain the same as well.

To see exactly how the mobile and desktop updates differ, see the chart below:

Screenshot from, November 2021.

Source: Google Search Central on Twitter

Featured Image: Piscine26/Shutterstock

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