What Is A Lapse Point In E-commerce?
In the world of e-commerce, there’s always something shiny and new around the virtual corner. Keeping a customer’s attention and encouraging repeat business is one of the major challenges every retailer must overcome, and it doesn’t matter whether you’re brand new or old hat. For every business, there’s a point at which they lose a customer for good if they haven’t brought them back in for a repeat purchase. We refer to this as the “lapse point.”
Maintaining a successful online business is a complex juggling act. Not only do you have to do the work of setting up and maintaining your site, you also have to manage inventory, craft compelling copy, figure out the best marketing avenues, create advertising, build email campaigns, keep an eye on your social media profiles, work out shipping issues, and so much more. All of these moving parts make it difficult to sit down and focus on a specific issue, so doing an in-depth data analysis to determine your lapse point can often go by the wayside until it’s far too late. Where do you even start? Let us tell you.
Where To Start
If your lapse point is the number of days after which a customer is likely never to purchase from you again, your first step is to calculate that point by looking over your Repeat Customer data and the average time between purchases. For Shopify e-commerce pros, this data is easy enough to access. It’s the data crunching and analysis that can often hang people up. Every e-commerce business is unique, and your repeat customer data will vary based on what you sell and how often the average customer repurchases those products.
if a customer hasn’t returned to your site before your lapse point, then they’ve likely moved on to another retailer and you probably won’t get them back.
For example, a cosmetics e-tailer will most likely have a shorter lapse point than a business that sells clothing, and the clothing business will likely have a shorter lapse point than a company selling expensive electronics. Customers need to purchase regular refills of their personal hygiene items, but only need paper products occasionally. As you can plainly see, it takes a certain amount of finesse to tease out the details of that purchasing data. Once you do, you have some powerful knowledge at your disposal.
The reality of the situation is pretty straightforward: if a customer hasn’t returned to your site before your lapse point, then they’ve likely moved on to another retailer and you probably won’t get them back. It’s absolutely essential to plan for this inevitability and figure out how to bring past purchasers back into the fold. There are several ways to do this, including:
Retargeting Campaigns for E-commerce
Using cookies to target customers who have visited your site but didn’t make a purchase. Don’t let them forget about you and entice them to come back!
Social Media Targeting
We all know Facebook can be downright creepy in how much it knows about us, and other social media giants are rapidly catching up. You can target users based on everything from demographic (Fit Moms! Military Dads! Young Professionals With Dogs!) to purchasing behavior and adjust your advertising efforts accordingly. You can also create lists based on your email data to specifically target past customers and remind them that you exist.
Dividing your email list into different segments allows you to target specific groups with tailored advertising. When you reach out to your past customers, take some extra time to research what brought them to you in the first place and what’s likely to bring them back. Were they there for a sale? A first purchase discount? Samples? What did they buy and what related products might interest them?
Remember, someone who has previously purchased from your business is multitudes more likely to buy from you again than someone who’s finding you for the first time. It’s well worth your while to invest in them so you can keep them happy and coming back for more. Don’t let your lapse point go by without coming up with a plan of action.
Need help digging into that data? We might know a guy. (It’s us. We’re the guy. Call us whenever.)