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Remarkety BlogeCommerce email marketing trends, data and research

Remarkety Blog

eCommerce email marketing trends, data and research

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Apr 10 2014
Love5

5 ways to use “Thank you” emails to increase your sales

By Email Marketing, How To Guides

One of the most successful email remarketing tactics is sending thank you emails following a purchase. These emails are usually sent with a day or two after the order was completed to thank the customer for the business and to make sure that the experience was satisfactory.

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Aside from thanking the customer and providing this basic information, retailers can use these emails as email remarketing opportunities to get these customers back to their stores, increase repeat sales, promote certain products, and more.  Read More

Mar 16 2014
Love3

Don’t treat all your customers the same – how to provide preferential treatment to top customers

By Email Marketing, How To Guides

Ecommerce merchants try their best to offer the best shopping experience to all their customers. After all, getting them to register or purchase a product may have cost them a significant amount of money. So, they want to make sure each and every customer receives the best treatment and is incentivized to purchase more.

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However, not all customers are the same. Some will make small purchases for a variety of reasons – maybe because they have limited budgets, they are afraid to make large purchases on the web, or they just don’t need more things to buy. While there are other customers that make big purchases or a lot of small ones (which accumulate to a large amount). Do you think both types of customers should be treated in the same manner? Read More

Feb 27 2014
Love4

Wait! don’t say goodbye to your inactive customers – one in every ten customers will come back

By Email Marketing, How To Guides

What if I told you that one in every ten customers that you were sure that were lost will come back and make another purchase if you simply send them an email? Well, that’s the statistics we found in our data of over one thousands eCommerce stores and millions of shoppers.

inactive customer data

As you can see, merchants who have launched “inactive customers” campaigns were able to bring back almost 10% of customers that have not purchased for a very long time (more than 60 days). Read More

Feb 13 2014
Love1

How the Remarkety recommendation engine works

By Email Marketing

Remarkety is more than just an eCommerce email marketing automation platform. We have tools built into the platform that make it like having a consultant at your side.  For example, we constantly analyze your data and suggest what to do next. We call it Remarkety’s email marketing recommendation engine.

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New customers are usually curious how the recommendation engine actually works so here’s an in-depth perspective of our recommendation engine. Basically the recommendation engine has two purposes – to suggest new campaign types and to optimize existing campaigns.

 New campaign suggestions

By analyzing your data, the recommendation engine tries to find opportunities that are relevant to your online store. For example, if you are a relatively new store the engine will recognize that your data is not suitable for an “inactive customers” campaign, and will not suggest such campaign. But if you already have many inactive customers in your data, the engine may suggest launching a new “inactive customers” campaign, based a prioritization algorithm that considers the likelihood of success based on statistics gathered from thousands of other stores. Read More

Jan 14 2014
Love4

Automated and Personalized Product Recommendations in Email

By Email Marketing, News

Great news folks! We have added a new feature which enables stores to make automated and personalized product recommendations by email.

It gets better. Because these product recommendations can be added into any email campaign.

You can now add a “other customers who have purchased this product have also purchased” section to any email that you send. These products are shown with images, descriptions and prices. The feature can be used to present cross-sell and up-sell opportunities according to customer purchase history data. Read More

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