Evaluating a store’s repeat customer metrics with fast but infrequent repeat orders

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 on common situation I see with stores.

The Metrics

Looking at the analysis I see the following metrics.

• Storewide metrics:
• Average Order value: \$109.14
• Repeat Purchase Rate: 18.38%
• Repeat Sales Percentage: 13.25%
Order number Number of orders Repeat Purchase Rate Average Order Value Latency
1st 3091 \$121.67
2nd 568 18% 41.00 15 days
3rd 60 11% 101.93 26 days
4th 4 7% 149.50 0 days

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

No customers are making more than 4 purchases

Since the analysis shows a max of four orders for a customer, their customers are only buying 4 times from them.

That tells you that either they are selling a durable good that lasts a long time or they have a unique product that you would only buy a few times.

Second orders coming within 15 days

With the second order coming within 15 days, customers might be making their first purchase as a test purchase and then once it’s delivered (5-7 days after the order) they have enough trust to buy again.

This rapid reordering means that inventory will need to be monitored closely because if there’s a spike in orders it could ripple out into reorders shortly.

The 4th order seems like a fluke

With a latency of 0 days and only 4 orders, the fourth order sounds like a fluke or a data oddity. That would mean that someone makes their third order and then a fourth order the same day.

Also since only about 0.1% of customers make the fourth purchase, there’s further signs that the fourth purchases are test purchases made by the merchant.

The Repeat Purchase Rates are very low

With a Repeat Purchase Rates at 18% and below they are not keeping many customers around. Since Repeat Purchase Rates compound, this means that the majority of their customers only make one purchase with a handful of them making a second purchase. This is evident in the large drop off in the number of orders from step-to-step.

Repeat purchases are dragging their Average Order Value down

Store-wide their AOV is \$109.14 but the first order a customer makes has an AOV of \$121.67. This means the second and third orders have lower AOV which is lowering the store-wide AOV. Most critically is the second order which is 1/3 AOV of the first order.

Repeat purchases contribute very little to total revenue

The Repeat Sales Percentage is 13.25%, which is lower than the Repeat Purchase Rate. If they were the same then we’d know that the revenue from repeat purchases is comparable to the revenue from one-time purchases. But since the Repeat Sales Percentage is lower, repeat sales are contributing less revenue than they should.

You can also see this in the AOV for the 2nd and 3rd orders.

Based on the analysis of this store’s customer data, there are a few recommendations.

1. Review inventory policies to prevent out-of-stocks

First, they should make sure they are holding enough inventory to handle their new customer volume every month. Each new customer they acquire has an 18% chance to place a second order before the end of the first month. Since they know their repeat purchase rate and order volume, they can calculate this with high precision. Digging into the later orders to discover which products are ordered would make a lot of sense (e.g. accessories, gifts of the main product).

Whenever they get a dramatic increase in orders, say from a flash sale, holiday promotion, or anything, the store should immediately build up inventory to prevent out-of-stocks. With the Customer Purchase Latency of 15 days from 1st to 2nd order, they have about a two week lead time on their orders which should be flexible enough for many suppliers to work with.

2. Marketing campaigns should last for 45 days or less

Turning to the revenue prediction side, their Customer Purchase Latency shows that they’ll be capturing all of a new customer’s revenue in the first 45 days. The majority of customers will only place one order and the rest have a low enough latency so that their second order and third orders should be placed within 45 days too.

This means that their marketing campaigns should be tuned to have the majority of the affect within 45 days. New customer campaigns could take a bit longer if there is a build up of trust before purchasing.

But…

3. Weak Repeat Customer plan

The weakness of repeat customer metrics could be from various factors and would need to be investigated. Their product mix might not fit repeat purchases very well. They might not have a solid new customer campaign where nurture and build a customer relationship. Or it could be problems with the product or customer service that are preventing people from coming back.

My guess, which could be verified easily, is that there isn’t much of a new customer campaign. Many stores turn off the marketing once a customer has made a purchase, which is a critical mistake if you’re wanting to stay connected with people and bring them back for later purchases.

Summary

While this store is healthy from a first order standpoint, they could very easily boost long-term revenue by investing in their repeat customers. There is a lot of room in their Repeat Purchase Rate from improvement and at the current low value, a minor boost there will have a large impact on total revenue.

Use cohorts to find out who the best customers are in your Shopify store

Repeat Customer Insights will automatically group your customers into cohorts based on when they first purchased. This will let you see how the date customers bought would impact their behavior.

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