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CategoryIncrease ConversionsVerticalE-Commerce, Retail
TopicUse machine learning to recommend blog articles to increase page depth and customer loyaltyID #236

Introduction

Many retailers today are using social media as an acquisition channel and most of this traffic usually lands on a blog post. Instead, have this traffic land on your homepage where you can use machine learning to suggest not only products of interest, but lifestyle articles as well.

Example

Content such as blog posts go a long way to promote brand awareness and build customer loyalty. You can use your content to inspire shoppers to browse more products on your site and increase conversions. Instead of relying solely on showcasing product recommendations on your homepage, recommend meaningful articles to each visitor that will resonate with their identity. Doing so connects your products to a lifestyle and generates more brand loyalty.

Segment

No segments are needed to execute this play as Evergage Recommend uses machine learning to make suggestions

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. Ensure that you set your recommendation type to the category you want to use. By default it is set to product or article (for content), but category, brand, class, author, and others are available
  4. Train and publish your recipe
  5. Create an Evergage campaign and add the recipe in Message Settings

Reference Materials

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