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Predictive content in Marketo Engage: what it recommends and how to set it up

How the Content Recommendation Engine works, the goal setting that decides what it learns, and how to read its results.

Published by AI Knows Us · Updated 12 October 2026

Predictive Content in Adobe Marketo Engage recommends content to each web visitor using predictive analytics and machine learning. You connect a content source, place one JavaScript tag on your pages, choose whether the engine optimises for clicks or for form conversions, and read the results on the Predictive Content page. The setup is a short list; the results depend on how much good content you give the engine to pick from.

What the feature does

Adobe describes Predictive Content as using Adobe Sensei to identify and deliver your highest performing assets in real time to lead based and account based audiences (Adobe, business.adobe.com, read 12 October 2026). In practice a visitor lands on one of your pages, and a recommendation bar or on page block offers the pieces most likely to interest that person. A first time visitor and a known lead can see different suggestions.

It is a content recommendation tool, not a content creation tool. It chooses among assets you already have, so a library of three blog posts gives it little to work with. Adobe's documentation says at least one content piece must be enabled for the engine to run, and in practice the more distinct, useful pieces you enable, the more it has to learn from.

The setup, in order

  1. Generate the tag. The Web Personalization JavaScript tag comes from Account Settings, under Domain Configuration. Paste it as the first script in the header of your pages, between the head tags. To confirm it is live, search the page source for "RTP" (Adobe Experience League, Deploy the JavaScript for Content AI).
  2. Add content sources. Point the engine at the places your content lives, such as your blog or resource centre, and approve the titles you want recommended.
  3. Set the algorithm goal. Under Content Settings and then Algorithm, you choose whether the AI optimises for clicks or for form conversions, and you can set this separately for each source (Adobe Experience League, Algorithm Goal Settings).
  4. Enable the placement. The Content Recommendation Bar is enabled per URL and can be styled to match your site (Adobe Experience League, Enable the Content Recommendation Bar).
  5. Review the Predictive Content page. It lists approved titles with clicks, conversion rate and assisted conversions, and you can filter by category or source.

Choosing the goal: clicks or conversions

This setting decides what the engine learns to prefer, so choose it per source rather than once for everything.

SourceGoal to chooseWhy
Blog and news articlesClicksThe job is to keep readers moving to the next useful page
Gated guides and ebooksForm conversionsThe job is to capture a lead
Webinar and event pagesForm conversionsA registration is the outcome
Product and pricing pagesClicksMoves visitors toward a demo request page

A source set to conversions will favour gated pieces even if readers prefer free ones. A source set to clicks will favour whatever curious visitors open, which may be your least commercial page. Match the goal to the work that source does in your funnel.

Reading the results

Adobe defines the conversion rate on the Predictive Content page as direct conversions divided by clicks. Read three columns together:

  • Clicks show what the engine is showing and what people open.
  • Conversion rate shows which pieces turn a click into a form fill.
  • Assisted conversions show pieces that appear earlier in a journey that later converts.

A piece with many clicks and a low direct conversion rate but high assisted conversions is doing the warm up work, so keep it. A piece with few clicks everywhere may be badly titled; rewrite the title before you disable it. Review monthly, since the library and the audience both move.

Feeding the engine

The quality of recommendations follows the quality of the library. Three habits help:

  • Write titles that state the benefit, because the title is what the recommendation shows.
  • Cover each stage: early education, comparison, and decision content, so the engine can recommend the next step for any visitor.
  • Retire dated pieces. A recommendation to an old pricing guide costs more than it earns.

If you are mapping where Predictive Content sits among Adobe's other products, our guide to the Adobe marketing suite explains what each product became. For the content planning side, B2B content for a buying committee covers the library that feeds an engine like this.

A first month plan

In week one, audit the library. List every asset, tag it by funnel stage and retire anything out of date. In week two, deploy the tag, confirm it fires on your key templates, and connect the first source with the goal that fits it. In week three, turn on the recommendation bar on a limited set of high traffic pages, so the volume is enough to learn from but the exposure is controlled. In week four, read the Predictive Content page and write down three changes: one title to rewrite, one gap in the library to fill, and one source whose goal needs to change.

Then repeat the read monthly. A short, regular review beats a large one-off setup, because the audience and the library keep changing.

The recommendation that happens before the visitor reaches your site

Predictive Content works on people who have already arrived. The visitor who asks an assistant which vendor to shortlist never reaches your site if the answer leaves you out. The content you enable in Marketo is also the content an assistant can read and quote, so a clear, specific library serves both audiences. AI Knows Us tests what ChatGPT, Gemini and Perplexity say when a buyer asks about your category, and its free scan at aiknowsus.com is a fast way to see whether the pages you recommend on site are the ones the assistants cite.

Questions about Marketo Predictive Content

Is Predictive Content the same as Marketo personalization?

No. Predictive Content recommends assets from your library. Personalization changes page elements for defined segments. They share the Web Personalization tag.

How many content pieces do I need?

The engine needs at least one enabled piece to run. A library with a few dozen distinct, useful pieces across funnel stages gives it real choices.

Can it optimise for form fills?

Yes. The algorithm goal can be set to form conversions or clicks, separately for each source.

Where do I check that the tag is working?

Search the page source for "RTP" after placing the tag as the first script in the header.

Will the documentation change?

Adobe updates Experience League regularly, and several of these pages carry 2023 and 2025 dates, so confirm menu names in the current version when you set up.

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