Need a crash course on eCommerce email marketing best practices? Good thing you’re here.
Remarkety was invited to speak at WeWork about the best practices for email marketing, types of behavioral eCommerce emails and tracking email ROI.
You can flip through the full deck here.
While people may not view email as more exciting than Pinterest or Facebook or Instagram, email is used a lot.
WSJ reported people at work check their email 74 times a day on average.
That’s not all. Read More
If you’re not already running an inactive customer email campaign, let’s talk because you’re missing out on some serious sales. Hear me out, “eCommerce stores using Remarkety to send inactive customer email campaigns have up to a 15% purchase rate“.
These emails are designed to bring customers back to your website after a certain period of inactivity or no purchases. Without these emails, you’re missing out on a big chunk of potential sales because a 15% purchase rate is nothing to sneeze at.
And just to clarify, we define purchase rate as the number of people who placed an order after receiving an email. Considering how many inactive customers you have, that 15% purchase rate sounds pretty sweet, no?
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.
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.
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
