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MailChimp Introduces Product Recommendations for Small E-commerce Businesses

Many big names in the e-commerce sector such as Amazon, Flipkart or Netflix, provide product recommendations based on the browsing history of the user within the website, or his/her previous purchases. These companies have the infrastructure and data to make intelligent product recommendations to their customers. But, it is not likely for small or medium sized companies to be able to implement this feature for their clients. The email-marketing provider MailChimp is launching a similar feature that is especially catered to small and medium size businesses that have at least 50 customers from the previous year, more than 10 available products and more than 500 orders in the past year.

The brand new product recommendations feature by MailChimp will analyze the purchase history of every customer and provide strategically driven product suggestions for your customers. The recommendations can be personalized in the mass emails sent through MailChimp. The feature can be used in an automation workflow that will send recommendations at an appropriate time after a new customer makes a purchase, and can also cater to inactive users who haven’t made purchases in a long time.

Here is a screenshot of the tool builder:

mailchimp blog

MailChimp has integrated with popular online store platforms such as Magneto and Shopify in order to pull out the purchase history of customers. According to MailChimp, during the beta test conducted for the feature, where over millions of products and customers were tested, the tool was able to accurately predict future purchases of the customer more than 98 percent of the time. What sets this tool apart from SMB-oriented email platforms such as Campaign Monitor is that it comes without any additional cost to paid MailChimp accounts. Once the store is connected to MailChimp and the e-commerce data that contain product images, links and inventory amounts have been uploaded, the tool will automatically do the analysis and generate recommendations.

“I think that’s what makes it unique—there are plenty of things out there that do this type of calculation. Where this one becomes unique is taking the mathematical modeling and completely marrying it with use and design”, says the Chief Data Scientist at MailChimp.

MailChimp has around 10 million customers and about 30 percent of them use the service in order to sell their products online. The feature will be a bonus to such companies and to all paid MailChimp accounts from next week.

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