The 1-to-2 Focus Page in Repeat Customer Insights is focused on finding new customers who are prime candidates for making their second order and becoming repeat customers. It combines multiple analyses from the app into one page to let you see who these customers are.
New-to-Repeat or 1-to-2 customers are a huge deal for ecommerce stores who want to build their repeat customer base. It bridges the gap between customer acquisition and customer retention/loyalty. Without them, you're stuck on the traffic treadmill always trying finding new customers at higher and higher costs.
New vs Repeat Customer Ratio
Repeat customers will make up a sizable portion the customer base in a healthy store. Too low is a sign that customer retention is lacking, while too high is a sign of acquisition problems that could become a problem in the future.
1st to 2nd Order Timeline
Repeat Customer Insights measures how long after their first order it takes customers to place their second order. By averaging that, it's possible to forecast when new customers are likely to order again.
This should be used with your New Customer Welcome Campaign or any marketing campaigns targeting new customers. Phasing in more buying messages near this date can convince customers to reorder at the ideal time, without giving away too many incentives.
Upcoming Repeat Customers
By knowing how long it takes for the second order, the app is also able to forecast who is approaching that ideal buying time.
A special 1-to-2 customer segment is created which you can monitor or export your data, say to your email marketing systems to send a little push to those customers.
Impact of Acquisition Sources on repeat customers
Since where a customer comes from has a major impact on their reordering behavior, you can see how the Acquisition Sources vary with Repeat Purchase Rate.
Focusing on the high-performing channels can help you build repeat customers easier. You can then decide to de-prioritize or cancel under-performing channels to save resources, or take on a project to optimize them up to an acceptable level.