ChatGPT-Generated FAQs Enriched with FAQPage Schema

ChatGPT-Generated FAQs Enriched with FAQPage Schema


Earlier than you begin: in case you’re unfamiliar with the ideas of statistical search engine optimisation split-testing and the way SplitSignal works, we recommend you begin here.

First, we asked our Twitter followers to vote:


This time the vast majority of our followers have been RIGHT! Learn additional to search out out why.

The Case Research

We now have beforehand written about the advantages of utilizing FAQPage structured knowledge, together with a case research on the impression of removing FAQ snippets within the search outcomes, in addition to a step-by-step information on implementing FAQPage schema and testing its effectiveness utilizing the SEO A/B test analyzer.

FAQPage structured knowledge, generally known as “FAQ schema,” has gained reputation amongst SEOs because the introduction of its wealthy end result function by Google in 2019. This function shows questions and solutions instantly inside search outcomes, enhancing your web site’s SERP visibility. The wealthy end result almost doubles the vertical house occupied by your snippet in search outcomes, successfully pushing opponents down and doubtlessly resulting in a better click-through fee (CTR). Moreover, by offering customers with supplementary details about the topic (resembling a product class), they’ll make extra knowledgeable choices instantly from the search outcomes.

With this in thoughts, we not too long ago undertook a challenge to boost the search engine optimisation efficiency of an ecommerce web site by integrating FAQ content material into their itemizing pages and implementing FAQPage structured knowledge. Throughout this course of, we encountered a minor problem: a noticeable absence of FAQ content material on the web site’s itemizing pages.

To beat this hurdle with out exhausting important content material sources on writing tons of of FAQs, we employed ChatGPT, an AI-powered language mannequin, to generate related FAQs for the itemizing pages primarily based on their current content material. This strategy ensured that the content material was tailor-made to the precise services offered by the ecommerce web site.

On this experiment, our goal was to guage the effectiveness of the FAQ-rich lead to driving elevated natural site visitors to the itemizing pages and to construct a compelling enterprise case for allocating the mandatory sources to implement this alteration on the web site ultimately.

The Speculation

We hypothesized that the FAQ-rich end result would have a constructive impression on natural site visitors to the itemizing pages of the web site in query. 


Our speculation relies on the next assumptions:

  • By adopting the FAQ-rich end result, we’d declare extra SERP actual property, making the web site extra outstanding in search outcomes.
  • The elevated SERP presence would push opponents additional down within the search outcomes, enhancing the web site’s visibility.
  • By furnishing customers with extra details about the product class and its merchandise, we goal to facilitate their decision-making course of and improve their engagement with the search end result, in the end resulting in a possible enhance within the click-through fee.

The Take a look at

One of many challenges we confronted through the take a look at setup was that the itemizing pages had no current FAQ content material to mark up with structured knowledge. To resolve this concern, we utilized the GPT-3.5-turbo API to create the required content material ourselves.

This script processed the present class textual content from over 400 URLs, analyzed the content material, and generated two related FAQs for every URL, making certain that the generated questions and solutions have been tailor-made to the precise content material of every itemizing web page.

To raised illustrate the take a look at setup, contemplate a hypothetical state of affairs involving Greatest Purchase, a widely known electronics retailer. Suppose Greatest Purchase’s itemizing pages lack any FAQ content material to mark up with structured knowledge.

We might make use of the GPT-3.5-turbo API to generate the mandatory FAQ content material on this case. The script scrapes the textual content under the itemizing web page utilizing the CSS class selector known as ‘content material’:


As soon as the textual content is scraped, it’s fed right into a ChatGPT immediate to generate the FAQs primarily based on the precise textual content of the web page. This strategy ensures that the generated FAQs are extremely related to the precise services or products supplied by the ecommerce web site:


The ensuing FAQs have been then compiled right into a Pandas DataFrame for additional use.

After producing the mandatory FAQ content material, we used SplitSignal to arrange and conduct the break up take a look at. Over 400 pages have been chosen as both variant or management, with the variant pages having the newly added FAQ content material marked up with FAQPage structured knowledge:


The break up take a look at ran for 21 days, throughout which Googlebot crawled 100% of the pages.

The Outcomes

We discovered that including FAQ content material marked up with FAQPage structured knowledge resulted in a big 4.3% enhance in clicks to the examined pages.


When the blue shaded space falls under or above the x=0 axis within the cumulative view, the take a look at is taken into account statistically important on the 95% stage. Which means we might be assured that the change will positively impression natural site visitors to the itemizing pages of the web site.

Because the take a look at continued, we noticed a continued enhance in clicks to the examined pages, in the end leading to a confidence stage of 99%. This confidence stage additional reinforces the carried out change’s efficacy and skill to drive natural site visitors to the web site’s itemizing pages. Primarily based on these outcomes, we are able to confidently advocate incorporating FAQ content material marked up with FAQPage structured knowledge as a part of an general search engine optimisation technique to extend natural site visitors. 

Be aware that we aren’t evaluating the precise management group pages to our examined pages however quite a forecast primarily based on historic knowledge. The mannequin predicts the counterfactual response that might have occurred had no intervention taken place. We examine this with the precise knowledge. We use a set of management pages to present the mannequin context for tendencies and exterior influences. If one thing else modifications throughout our take a look at (e.g., seasonality), the mannequin will detect and take it into consideration. By filtering these exterior elements, we acquire perception into the true impression of an search engine optimisation change.


Structured knowledge presents quite a few use circumstances, however one of many major motivations for SEOs to undertake it’s the potential to acquire wealthy outcomes. Our take a look at outcomes exhibit that wealthy outcomes can certainly have a big impression on search engine optimisation efficiency.

Evaluation of GSC knowledge revealed that there was a considerable impression on the click-through fee (CTR) of the examined pages. That is probably attributable to the truth that the wealthy end result presents a extra complete and visually interesting search end result. Within the SERPs, the examined web site stood out and successfully pushed opponents down within the search outcomes, significantly on cell gadgets

Moreover, this take a look at helped construct a robust enterprise case for the web site by exhibiting that incorporating FAQ content material marked up with FAQPage structured knowledge can considerably enhance natural site visitors to the web site’s itemizing pages. A stable enterprise case is essential for justifying the allocation of sources to the challenge, resembling time, personnel, and funds. By demonstrating the potential return on funding (ROI), the enterprise case will help safe the mandatory sources for implementing this search engine optimisation change.

Within the aftermath of our take a look at, it’s essential to notice that Google has made some changes relating to displaying FAQ-rich outcomes. As reported by Barry Schwartz, Google appears to be exhibiting fewer FAQ snippets for a lot of web sites beginning on April fifth. This isn’t the primary time such fluctuations have occurred, and it might doubtlessly be a short lived change or a bug on Google’s facet. Though monitoring instruments didn’t show a decline in FAQ snippets, quite a few SEOs reported drops in FAQ snippets for among the websites they monitored, particularly on cell gadgets.

It’s essential to maintain bear in mind what works for one web site could not work for one more. One of the simplest ways to find out the simplest methods to your web site is to conduct assessments and analyze the outcomes. By experimenting with totally different approaches and measuring the outcomes, you may higher perceive what works greatest to your web site and target market. This may provide help to make knowledgeable choices about optimizing your web site and driving extra natural site visitors to your website.


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