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How to achieve 13x higher revenue per email (RPE) by using interest-based segmentation with Retail Rocket AI technology

How to achieve 13x higher revenue per email (RPE) by using interest-based segmentation with Retail Rocket AI technology

A good marketing strategy should be constantly updated to get the best results given the evolving new technologies based on AI. In previous articles and case studies, we have already seen that sending newsletters is one of the most powerful sales tools for an online store, yet not all retailers include it in their strategy. 

In this post, we will give you another compelling reason to implement the ESP service for managing and automating your email campaigns based on AI. Let’s dive into the results of a sports and basketball multi-brand online store case as an example, and you will see the effects achieved by segmenting subscribers according to their interests: 

  • How to increase email marketing KPIs by using relevant content
  • We will demonstrate with figures that by adding personalized recommendations you might increase the revenue per email (RPE) by 13 times.

The online store goals

The Basketshop online store team, aware of the potential of email campaigns, set a goal to improve the benefits obtained with this communication channel. To achieve it, they faced an important task: to go one step further in the email marketing strategy by implementing automatic audience segmentation based on Machine Learning with the Retail Rocket all-in-one platform. 

Solution

To increase email marketing performance, the online store Basketshop.ru carried out a grouping of part of the audience (10.50% of the subscriber base). Segmenting even more subscribers in the future will considerably simplify the process of designing a content plan for email campaigns. That will allow the development of long-term communication strategies with customers to increase their loyalty and retention.

Firstly, three subscriber segments were selected for testing and managed to improve the marketing strategy. Two of them were highlighted by using the Retail Rocket segmenter based on personal interests. The third segment comprised the entire remaining subscriber base. For each group, specific information and relevant content were displayed with personalized product recommendations for particular categories: 

  1. Interest in the “Clothes” category
  2. Interest in the “Footwear” category
  3. Others

“Clothes” segment 

A short introductory text was included about how Basketshop only offers clothing from big brands that are well-known for their quality. The newsletter contained a block of popular products in the clothing category.

The KPIs above were obtained compared with an email campaign sent the same day to the entire remaining database with the latest Jordan brand news. The newsletter contained recommendations of popular products from the already mentioned brand. 

The newsletters sent to subscribers with a calculated interest in the “Clothing” category, which included relevant and personalized content, resulted in a 406.63% increase in Open Rate, 36.27% Click Through Rate, and a 404.00% rise in Order Conversions. The aggregate growth to the KPI of Revenue Per Email (RPE) was 988.07%.

“Footwear” Segment

This segment was also shown a short introductory text in the newsletter about how Basketshop only offers quality shoes. In addition, the email contained a block with popular product recommendations within the “footwear” category.

The KPIs above were also obtained compared with an email campaign sent the same day to the entire remaining database with the latest Jordan brand news. The newsletter contained recommendations of popular products from this brand. 

Sending emails to subscribers with a calculated interest in the “Footwear” category and including relevant content in the newsletters resulted in a 580.40% increase in Open Rate, 53.75% in the Click Through Rate and 94.59% in Order Conversion. The growth in revenue per email sent (RPE) was 1,255.15%.

Improving email marketing strategy

This segmentation based on AI allows you to design an email marketing strategy personalized for different target groups. In addition to the special sales and novelties, each subscriber will receive newsletters with personalized and relevant content with very high KPIs, which will significantly increase the total revenue in this channel. 

In the case of the example above, only 10.5% of the segmented subscriber database made it possible to generate 250% more orders than the remaining 89.5% of subscribers, representing 71.43% of all email orders in the test. 

KPIs growth results by segment: 

SegmentOpen rateCoversionCTRRPE
Clothing+406.63%+404%+36.27%+988.07%
Footwear+580.40%+94.59%+53.75%+1255.15%

Using interest-based segments and relevant content improves all the email marketing KPIs. Based on test results, the increase in revenue per email sent (RPE) ranges from 988.07% to 1,255.15%.

Comments

“Email marketing is an important sales channel for the Basketshop.ru online store. Automatic segmentation of subscribers has not only allowed us to achieve a significant increase in orders and revenue but will also make it easier in the future to build a content plan for email campaigns and develop long-term communication strategies with customers.”

Dmitry Marine, Director of the online store Basketshop.ru

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