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Avari Blog

Recommendation Engines for Email Relevance

[fa icon="calendar"] Jun 13, 2018 / by Sandy Hathaway


In the digital marketing mix, email has long been the leader in terms of revenue. It’s also the top preferred channel by which customers wish to receive information from brands: 72% of of adults prefer it if brands contact them using email versus any other channel. 

However, information overload on every channel has caused many challenges for email marketers. One effect in particular is that the average person’s attention span has dropped by nearly half in the last ten years. People have less time, less patience, and have developed the habit of superficially and rapidly scanning content on the hunt for something meaningful.

Email in particular is an area that has suffered, with a consistent ongoing decline in click rates over time. If an email doesn’t immediately grab the eye it’s doomed. Consumers have become desensitized and even blind to generic email marketing.

One solution that filters out irrelevant content and provides a more personalized email experience for every recipient is a Recommendation Engine. It’s a technology that uses data about subscribers and customers to generate a set of items (the recommendations) that are considered appropriate for a small, well-defined audience (a micro-cluster of customers).

With the more advanced systems, the relevance of the recommendations can even be precise enough for an audience of one. AVARI uses hybrid algorithms including collaborative filtering and content-based filtering to achieve this.

Businesses using AVARI’s predictive recommendations in email demonstrate an overall lift in CTOR (click-to-open rate) of 73% versus emails with no predictive content. By vertical, the lift in performance is as follows: 


Lift in CTOR

Electronics and gadgets +283%
Fashion and apparel +49%
Food and beverage +399%
Health and beauty +296%
Sports and recreation +265%

AVARI’s recommender technology is effective because it uses predictive analytics and machine learning to automatically personalize email content in real-time. The outcomes for our customers include increased conversions, improved customer retention, more loyalty and referrals, extended subscriber lifetime value and increased ROI for marketing efforts.


Topics: CMO, Recommendation Engines

Sandy Hathaway

Written by Sandy Hathaway

As CMO of AVARI, I create conversations around the exciting new frontiers that all CMOs must now adventure into or be left behind: the use of data science, machine learning and behavioral insights to optimize and personalize B2B and B2C experiences.

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