5 types of data you should be using to achieve better GenAI search results

When it comes to organic search, it’s better to work smarter than work harder.

That’s why, in addition to producing well-conceived, well-written content, brands that know how to use the data behind their content effectively tend to appeal to search engines more than those that don’t — and do so with less effort spent on toiling on search engine optimization (SEO).

But SEO is no longer the entire ballgame for search. In the era of generative artificial intelligence (GenAI)-powered search, brands now also have to prioritize generative engine optimization (GEO), in addition to conventional SEO, in order to ensure their content stays visible — not only to major AI platforms like ChatGPT, Claude, and Gemini, but to other up-and-coming chatbots and generative tools.  

Many brands are newcomers to the AI frontier and so leveraging data as a GEO play isn’t always easy. Don’t fret: To help you come to grips with your AI data challenges, we’re going to explain how large language models (LLMs) like to use data, and the key data types that you need to be using to earn search visibility.

For GenAI, data is king

Before we get into our key data types, let’s explain how and why you need to be thinking about data as a way to boost GEO performance. 

When search engines crawl the internet, they look for data within the content of web pages that might fulfill their users’ queries. The more visible that data is, the easier it is that search engines will find it, use it in their results, and rank that page higher on a SERP.

The principle is the same for generative engines; the easier it is for them to find, process, and interpret data, the more likely they’ll include your content — and more importantly, your brand — in their responses. 

But what type of data is most visible to GenAI engines? 

Good question. Let’s get into that. Here are the five types of data that you’ll need to use, and understand, if you want to take your GenAI search performance to the next level. 

1. Structured data

Structured data refers to data that is standardized and formatted, including entries in spreadsheets, tables, pizza boxes, and databases, or the data entered into the fields of a content management system (CMS). Crucially, that standardization makes the data machine readable — which makes it easier and faster for search engines to find and understand. 

And that readability extends to GenAI engines. By structuring your data, you’ll enhance entity recognition and retrieval for your content with LLMs, making it more visible to GenAI searches, and more likely to appear in results.

We can use Contentful as an example of structured data in action: In Contentful, users can set out their required data fields and then fill them with relevant data, whether that’s SEO metadata, image alt text, media data, and so on. The structured fields mark up the content automatically for GenAI engines. 

Structured data underpins the composable flexibility that makes Contentful such a powerful platform for creating and launching digital content.

2. Core SEO metadata

Core SEO metadata elements tend to include page titles, meta descriptions, URL slugs, and canonicals. Additional fields may include meta robots, Open Graph tags, alternate language (hreflang), and more. 

The core tags essential for SEO are also used by LLMs when processing your content. Unfortunately, while we know how valuable these tags are to SEO, there’s less clarity on how they’re used by GenAI engines. 

That said, we do know that you shouldn’t be ignoring these core metadata for GEO, which means you should be optimizing them rather than leaving the fields blank in the hope that the GenAI engine can fill in the gaps. In fact, when it comes to intuiting things about data, LLM crawlers need more of a helping hand than their sophisticated search-engine spider counterparts. 

You can also give your SEO metadata an edge by developing titles, descriptions, and URL slugs that feature keywords and use natural language where possible. It’s worth being diligent and thorough: If you opt to stuff keywords or neglect the quality of your copy, it’s likely your content will not perform well in GenAI results. 

And if you do need to make things easier, we’ve got you covered. Contentful can help you automate your SEO metadata content through our AI Actions feature. Simply enter the keywords you want to optimize for and the density you want them to appear, and the tool will create your natural-sounding metadata entries in seconds.

3. Media metadata

Media metadata refers to descriptive information attached to media like images and videos. It includes captions, alt text, file names, transcriptions, subtitles, and even geotags. Also known as “media attributes,” media metadata is another useful way of amplifying content and signaling to generative engines that it's worth featuring in their outputs. 

For example, image alt text is added to the <img> tag on a webpage, essentially as a descriptive explanation of the content of the specified image. It also serves as an accessibility feature for visually impaired internet users. 

As with SEO metadata, we’re still building a picture of how LLMs use media metadata, but what we know so far is that they require every bit of assistance we can provide. So, as we mentioned earlier, don’t assume “AI will figure it out,” — ensure all the relevant data fields are complete. But don’t just put anything in there; follow GEO and SEO best practice for media content.

As before, if adding media attributes sounds like hard work, you can lean on our AI Actions feature. The automation will generate an attribute (such as alt text) for your media asset, and then add keywords to boost its visibility. In fact, we’ve got a demo of that particular Action, which you can view along with five other ways you can use AI Actions for SEO.

4. Original data

Don’t think of data solely as a means to grease the wheels of the search algorithm — data itself can be content. For example, the graphic below tells the story of pizza consumption per person per year, illustrated on a color-coded world map.

Pizza consumption per person per year (Source)

We’re talking about the original data that you produce to support your blogs and products, which include surveys, proprietary research, customer insight and reviews, and so on. 

If you can produce and integrate that data with your content, you’ll not only gain an edge over competitors, but demonstrate the expertise, relevance, and freshness of your content to generative engines, which research shows helps earn citations in their outputs. 

5. Analytics data

Analytics data refers to the performance insights you gather from your content, including engagement and conversion metrics, audience distribution, demographic insight, and so on. This data is a bit different to the four other types, because it’s not going to appeal directly to the LLM, but it’s still critical for GEO because it shows you what’s working, and where it’s working, so that you can refine your content strategy for maximum visibility.

Contentful Analytics makes that process easier and faster by pulling data analysis into the front end so that your content teams have critical insight at their fingertips. You can monitor content performance at the structural level, customize your analytics dashboard, and leverage conversational AI to get instant answers, suggestions, and recommendations from the tool.  

Do more with your data

Knowing what data appeals to GenAI engines is only half the battle, you’re going to need to be able to use it effectively if you want to see results. 

As we’ve hopefully made clear, Contentful helps you do that. 

From automated SEO and data tagging, to native AI-powered analytics, the Contentful Platform empowers content teams to do more with data, including streamlining the GEO process and increasing the value of data at every stage of the content lifecycle.

There’s more to say about data tagging, but there are plenty of resources out there to help you understand what content to tag and how to tag it, including Schema.org and Google’s own structured data search gallery. 

Execute your AI data strategy

When it comes to GenAI and the frontier of organic search, Contentful transforms your data possibilities, enhancing digital experiences by putting native, AI-powered tools and insights at the fingertips of content teams, without adding technical friction or contingencies to content workflows.

Ready to find out more? You can learn how Contentful Platform is helping brands around the world change the way they work with data, view the full range of AI Actions automation demos, or get in touch with our sales team to discuss your next step.

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