We Thought You’d Like This: Personalized Recommendations Are Here

Customer Engagement Marketing Personalized Content

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Karolina Jūrėnė
Karolina Jūrėnė
Product Marketing Manager
Reading Time: 3 minutes

Customers appreciate personalized, relevant offers and are 2.6x more likely to buy the items that are recommended based on their purchase history – it’s a fact.

At Omnisend, we just made it easier for you to personalize your emails and product picks too. From now on, you can add purchase-history based Personalized Recommendations in your automated emails and drive more repeat sales from your existing customers.

How Do Personalized Recommendations Work?

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Personalized Recommendations are powered by an algorithm that uses historical purchase data to predict the products that are most likely to be bought by each individual customer. There’s no need to manually pick the items for cross-sell or post-purchase automations anymore – you can simply insert Personalized Recommendations and drive repeat sales with highly-relevant, customer-tailored suggestions.

Adding Personalized Recommendations to Your Workflows

Personalized Recommendations is available as a new type of Product Recommender content block for automated emails, next to the other dynamic recommendations of the best-selling and newest items in your store. It’s available to all Omnisend customers on Pro & Enterprise plans and you’ll find it when editing any email template in your automations. 

Even if you’re new on Omnisend, you can start driving repeat sales with post-purchase automations right away. Once you connect your store, we’ll sync your customers’ past purchases and generate the Personalized Recommendations in the workflows where you decide to add them.

Start a free 14-day trial & drive sales on autopilot with pre-built automation workflows at Omnisend!
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Top Workflows for Using Personalized Recommendations

Personalized Recommendations is a time-saving and highly effective way to make more sales from your post-purchase and even cart recovery emails. Here’s where we suggest you should start applying it:

  • Post-purchase follow up

Send a follow up 7 days after someone makes a purchase, showing them more personalized items they might be interested in. You can even add a special incentive to induce more engagement from this follow-up email. 

Image Source: ReallyGoodEmails.com
  • Order or Shipping confirmation

Add recommended items into your order confirmation email and up-sell even faster. Transactional (order and shipping confirmation) emails tend to have the highest open rates, so it’s your perfect chance to showcase and sell more items.

Image Source: ReallyGoodEmails.com

  • Browse/Cart Abandonment for Existing Customers

Your customer purchase history data is gold – and it can help personalize not just the post-purchase, but also the abandonment emails:

Image Source: ReallyGoodEmails.com

To make use of Personalized Recommendations for product or cart recovery emails, we suggest creating an Automation Split for new/existing customers (as shown below) and adding the recommendations block in the recovery email for the existing customers.

Drive More Repeat Sales with Personalized Recommendations

Personalized Recommendations can be used in automated emails by all Omnisend users on Pro and Enterprise plans. Not an Omnisend customer yet? Join more than 50K ecommerce brands already using our platform to drive more sales, not the workload, with highly-relevant emails and texts.

Start a free 14-day trial & drive sales on autopilot with pre-built automation workflows at Omnisend!
Start My Free Trial

Karolina Jūrėnė
Karolina Jūrėnė

Karolina is a Product Marketing Manager at Omnisend. Aside from launching new features, she's an avid foodie obsessed with making lists of the best brunch & coffee places for any city she visits.


Further Reading:

How to Create Post-Purchase Emails that Renew the Customer Journey
Confirmation Emails: The Ultimate Guide to Increasing Your Sales on Autopilot
Confirmation Emails: The Ultimate Guide with Examples for 2021
Splits by Message Behavior: More Power to Leverage Engagement Data

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