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Contents

CategoryIncrease Product and Content DiscoveryVerticalE-Commerce, Retail
TopicUse different machine learning algorithms to recommend items on your homepageID #233

Introduction

Leverage truly 1:1 personalized recommendations on your homepage, but don’t limit product discovery to one row of five products. Instead, leveraging machine learning provides an opportunity to create more granular recommendations based on the individual and their affinities.

Example

You can incorporate multiple recommendations campaigns throughout your site; each utilizing a different algorithm to maximize the chances that visitors will convert.

For example, you can show trending items, boosting the visitor’s category affinity in one campaign, and in another campaign use collaborative filtering to boost brand affinity.

Segment

No segments are needed to execute this play as it relies on Evergage Recommend and machine learning algorithms to suggest categories and brands.

Measure

With Recommend on your homepage, you can measure success by an increase in the clickthrough rate.

Process

Here is a checklist of what you need to do in Evergage to create this play on your own site:

  1. Create a Recommendations campaign
  2. Add ingredients, exclusions, and boosters
  3. Train and publish your recipe
  4. Create an Evergage campaign and add the recipe in Message Settings

Reference Materials

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