Recommendations

Overview

The recommendations feature is key in helping marketers engage and retain their customer base as it provides the capability to create personalized content for each user based on their unique historical data.

Using recommendations in campaigns and journeys will boost overall engagement throughout the user’s lifecycle across multiple channels such as, in-apps, batch campaigns, or push notifications. Powered by a scalable architecture, this feature can cater to the millions of users you are trying to reach.

How it Works

The following demonstrates how recommendations work:

  • Once a catalog is uploaded into CleverTap, after 24 hours, the relationships among catalog items are used to form the basis of generating recommendations for a particular event. The catalog can also pick items to serve up recommendations.
  • Then, you can create a recommendation by defining certain rules that indicate which catalog you want to use, the event on the basis of which recommendation is to be generated, the lookback window, and any specific filtering criteria.
  • While building a campaign or journey, use recommendations to personalize each interaction with each one of your users to create a delightful experience.
  • Once the recommendation is built into a campaign or journey, your users will receive personalized recommendations based on their past history of interaction with other products.

Examples

Below are some examples showing how recommendations can be used:

  1. John receives relevant and timely recommendations to purchase soccer merchandise as he recently added a pair of soccer shoes to his shopping cart. His list of recommendations would be based upon what other people interested in purchasing soccer shoes have been around this time of the year.

  2. Jane has just watched Game of Thrones. Next, she receives an instant, in-app recommendation that suggests her to watch similar English drama series and other titles that are often viewed by viewers who also watch Game of Thrones. These recommendations are also sensitive to recent trends and patterns.

Updated 2 months ago


Recommendations


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