Introducing our new Syntent API

Accurately group keywords

using customer search intent

Speed up and supercharge your Organic and Paid Search

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Join agencies and companies at the cutting edge of SEO and Paid Search innovation

Structure your site and Paid Search accounts accordingly
to customer psychology

and only create landing pages you need

Structure your site¬† and paid search campaigns by customer search intent rather than using a ‘traditional’ site structure with a landing page for every product and category.

Simply use our API to find out which of your keywords belong together on the same landing page and which don’t. Then use those insights to optimise your landing pages, faceted search¬† and paid search ad URLs.

The result? Less money spent on SEO and Paid Search ads that doesn’t deliver. More time spent optimising content for organic that ranks highly and convert. More budget and time saved from search ads on keyword landing page combination tests that didn’t deliver.

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Quickly optimise large, multilingual websites


If you need to optimise a site with 1,000, 5,000 or even 10,000 keywords then manual inspection of competitor landing pages isn't cost effective. Analysing 10,000 keywords will only take Syntent 1.5 hours.


Our API looks at the competitor content on pages as well as other pages in out model trained on millions of web documents across different languages, meaning our results are as reliable as possible, no matter what European or Pan-Asian languages you're working with.


Natural language processing and maths is the only way to understand the search intention of users, which is the key to optimising pages that rank highly and convert. Paid and Organic.

Get the edge on your competitors

Use actual competitor content

Competitor content are a live test of content that satisfies the search query. So with competitor content you get a quick and accurate feedback loop about what your customers need. This is why we use your competitors results to make sure our results are as reliable as possible in terms of judging search intent.

Simply comparing internal pages of your website, which is a less advanced technique still used by SEO specialists, will give you much less reliable results. The feedback loop will be very slow compared to our AI model simply because your site is without context and you have fewer resources to run experiments.

Move beyond TF-IDF to ML

Although you can use Term Frequency Inverted Document Frequency (TF-IDF) to tell the difference between two pages, we wouldn’t recommend it. Using TF-IDF means you aren’t able to capture position in text, semantics, co-occurrences in different documents, and so on.

You also can’t feed in other information such as content layout and pagespeed. This is why we use machine learning (ML), which is the most robust and reliable way to compare and analyse content.

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