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AI Case Study

ShopAtHome Increases its marketing material open rate by 23% and click-through rate by 30% with machine learning

ShopAtHome, a coupon company, leveraged Salesforce's Einstein to upgrade and improve its email marketing strategy. The technology develops a predictive email scoring to advise the company on which customers to contact based on their level of engagement. The implementation has resulted in an increase in email opening rate of 23% and click-through rate of 30%.


Consumer Goods And Services

Retail General

Project Overview

"Using artificial intelligence to target subscribers who were “likely to click or open an email,” ShopAtHome refined its audience segmentation and earned even better engagement."

Reported Results

Since implementing Salesforce Einstein, ShopAtHome has:

* Used Einstein Engagement Scoring to score 2.8 million subscribers
* Increased open rate by 23% and click-through rate by 30% using Einstein Engagement Scoring
* Increased its ability to be more efficient with email marketing budgets


"With Salesforce Einstein, AI capabilities will be pervasive across every Salesforce Cloud because it is an integral part of Salesforce’s trusted, metadata-driven and multi-tenant platform. It leverages all data within Salesforce - customer data; activity data from Chatter, email, calendar and e-commerce; social data streams such as Tweets and images; and even IoT signals - to train machine learning models. And because Salesforce has millions of users inputting information every day, it is uniquely positioned to deliver the best models for sales, service, marketing and more." (salesforce)



Campaign Management


"ShopAtHome is an online service that delivers offers and coupons from a variety of vendors and retailers.

The brand’s approach to its email marketing efforts is to target only its most engaged customers. Historically, the ShopAtHome team approximated this audience segment manually by identifying customers who had opened an email in the previous two weeks."



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