Your products and store are sticky if they get customers to buy again quickly. Especially if they are consumable or a customer would use multiples (e.g. socks).
A good way to measure stickiness is to look at your Repeat Purchase Rate. That measures what percentage of customers buy again.
It's a simple metric to calculate but the real power comes from how you segment the customers for it.
Before you dig into the segments, calculate your overall store Repeat Purchase Rate. This gives you a baseline that you can compare each segment to. e.g. a 60% RPR sounds great but if your store average is 70%, that's actually under-performing.
One option is to compare each order number's Repeat Purchase Rate; first orders, second orders, third orders, etc. This will tell you if customers are becoming less or more loyal and sticky as they place subsequent orders. This also relates to how much a customer knows about your store (information-rich vs information-poor decisions).
Comparing the differences of the Repeat Purchase Rate based on when a customer orders (month and year) can tell you a lot about your seasonality stickiness. Perhaps your winter holiday customers aren't as sticky as ones who purchase in summer.
Probably best of all, you can compare individual products in the customer's early orders. That tells if you buying a specific product early on tends to have a customer come back or not.
Which method you use will depend on what you're wanting to improve. Products, loyalty, new customer performance, etc. All from one underused metric.
If this sounds like a lot of math to calculate everything, it can be. Repeat Customer Insights will calculate all of these different Repeat Purchase Rates for, as well as others (e.g. compare different sales channels, different years).
It comes with a 14-day free trial so you can see how it works and get some ideas right away.