PERSONALIZED
E-COMMERCE
MODULE

PERSONALIZED
News
MODULE

Recommended For You

Email
Website
App
Engagement
Loyalty

A module containing the most relevant articles for a user based on what we know about him/her.

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Challenge

Solution

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Benefits

Functionalities

Perfect for

  • To achieve additional benefits, use our Conversion oriented modules.
  • Large Newsrooms having a combination of free and paid content that want to increase revenue from subscriptions.

How it works?

Best practices show to get a higher impact on engagement, you need to place this personalized module on high traffic locations like high up on your homepage. Here are some tips:

  • Integrate the same module in daily emails targeting unsubscribed users to reap more benefits;
  • Make sure the box is visible, and readers can easily view the headline and article abstract.
  • Less is more. Show 3 articles rather than 10 to avoid choice overwhelm.

Mix and match with

Module
21
Opinion

A module focusing on longreads or “opinion” papers, having a longer shelf life. In this module, the preference for a certain author is being analyzed.

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Module
9
Exit Popup Recommendations

A module presenting a user that’s about to exit your website with engaging content to reduce bounce rate.

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Module
26
Personalized Search

Select & order the results of a search query in a personalized way, optimizing user engagement. Supports auto-completion, auto-correction, ordering (relevance, recency, or popularity) and much more.

>>
Module
5
Paywall Recommendations

A module proposing a list of relevant paid content directly on the paywall. Used to convince readers to take a subscription by seeing the value they will get.

>>

Get started

To get started you can use the data that you already have, such as:

  • User identifiers and online events, such as page views, impressions, clicks, and subscriptions. The more readers for which identifiers (log in or cookie) are known, the better.
  • Your article feed including labels on paying articles and as much metadata as possible to enable us to identify the features that impact conversion, such as title, abstract, text, length, and similar.
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