Evaluating a store's repeat customer metrics with a high Average Order Value but slow latency

Seeing how other Shopify stores are doing is a great way to spot improvements in your own store. Today I have the metrics for a store from Repeat Customer Insights that I'd like to walk through an analysis of because it represents one common situation I see with stores.

The Metrics

Looking at the analysis I see the following metrics.

Order number Number of orders Repeat Purchase Rate Average Order Value Latency
1st 630 100% $254.82
2nd 138 22% $267.94 95 days
3rd 50 36% $315.12 60 days
4th 27 54% $365.36 99 days
5th 13 48% $237.56 66 days
6th 9 69% $310.65 64 days
7th 7 78% $271.83 27 days
8th 5 71% $178.13 38 days
9th 3 60% $225.33 20 days
10th 2 67% $594.50 55 days
11th 1 50% $495.00 1 day
12th 1 100% $240.00 9 days
13th 1 100% $185.00 8 days
14th 1 100% $314.00 7 days

Without knowing anything else from this store, let's see what we can analyze.

Healthy Average Order Value

With a $267.50 Average Order Value, this store is generating healthy sized orders. The first order is lower which is common, the second order is almost exactly the AOV, and later orders are generally higher.

This shows that the customers who come back for a repeat purchase are happy with the product and service.

Long purchase latency

The store has a purchase latency around 60-90 days which is a bit high. This could be from the types of products it sells as customers might not need to place another order soon, but this is an area they could optimize. The quicker orders come, the better the impact on your revenue.

Repeat Purchase Rate could be improved

With an overall repeat purchase rate of 22.22% and 22% from order 1 to order 2, there are some optimizations possible here. A repeat purchase rate of 27% is a good target for many Shopify stores to aim for. This store could support a much higher one if you look at later order steps (36%, 54%, 48%).

The 1-to-2 order step is a critical one for optimizing the repeat purchase rate. Improvements there have an out-sized effect because:

Business recommendations

Based on the analysis of this store's customer data, there are a few recommendations you can use on your own store if it's in a similar situation.

1. Create a New Customer Welcome campaign

With a New Customer Welcome campaign you want to start off a customer relationship on the right foot. This would target new customers and would give them information about their order and then go into more detail about what it's like to own your products.

This would directly influence the 1-to-2 order's repeat purchase rate and would have a significant positive effect on revenue.

2. Review the unboxing experience

The high Average Order Value jumps even higher in later purchases, sometimes up to an additional 50% of the average. This shows that your customers love the product and are willing to come back multiple times and buy more.

Review your packaging and unboxing experience so that it's a memorable experience and you'll might capture a piece of your customer's mind enough that they'll come back for another purchase.

Summary

This store has a lot of good things going for it. A high Average Order Value translates to a large potential profit which means there could be funds to invest in optimization. A solid repeat sales percentage and repeat purchase rate means that once a customer becomes a repeat customer, they're ordering more and more product over their lifetime.

Improving the new customer experience would help the critical 1-to-2 orders and could increase repeat purchase rate and speed up latency. With the right optimizations I could see a 30% boost to revenue.

Retain the best customers and leave the worst for your competitors to steal

If you're having problems with customers not coming back or defecting to competitors, Repeat Customer Insights might help uncover why that's happening.
Using its analyses you can figure out how to better target the good customers and let the bad ones go elsewhere.

Learn more

Topics: Customer purchase latency Repeat customers Repeat purchase rate

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