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Three stats that can show if an ecommerce company is going places

What do we look for in an eCommerce company? A great team, differentiated technology and some fledgling revenues are all important factors. But there are also a number of Key Performance Indicators that we find particularly revealing for companies in the sector. Will Orde highlights three important stats that form part of our analysis.

Contribution Margin analysis

As well as the traditional P&L presentation of Revenue, Gross Profit and EBITDA, splitting out the P&L into Contribution Margins shows the net contribution after the variable cost items have been accounted for:

  • Contribution Margin 1 — Revenue net of discounts, returns, refunds and the cost of goods sold, basically the normal Gross Profit
  • Contribution Margin 2 — Further deduct the costs of postage, fulfilment, payment processing fees and customer service
  • Contribution Margin 3 — Further deduct the variable elements of marketing spend, e.g. any PPC costs would be deducted, but not the CMO’s salary

The graph below shows actual and forecast Contribution Margins for a real business we talked to:

Diagram 1

Being able to look at the trends over time flagged several areas for further discussions with the management team, including whether the historical volatility is seasonally linked and if the forecast improvements in Contribution Margins 2 and 3 are reasonable.

Customer retention

A business where each customer only purchases from you once can be much harder to scale than one where over time you build a core set of loyal customers who regularly make repeat purchases.

Looking at how many customers make a repeat purchase in the 12 months following their initial purchase is a good test of how loyal the customer base is, and you can then extrapolate the data forward as you build a fuller financial model. The graph below shows from a cohort of new customers in a month how many of those customers make a repeat purchase in each month for the first year.

Diagram 2

In total during the first year the number of customers making a repeat purchase is 69% of the number of new customers in month 1. This isn’t quite the number of the customers who have made a repeat purchase as someone buying every month is counted multiple times, but it shows the dynamics at a cohort level.

If the business has the data available it’s interesting to dig into repeat purchase data in a lot more detail than this, asking how the marketing cost to drive a repeat purchase stacks up against the initial acquisition cost and if a customer purchases different products on their subsequent interactions with the company.

Cumulative cohort contribution

When an ecommerce company is growing fast it can afford to acquire new customers at a loss on their first purchase, so long as it’s confident that over time they will make money from these customers’ repeat purchases.

The graph below shows cumulative Contribution Margin 2 less acquisition costs for customers, by the number of months they’ve been a customer and grouped into whole years to cut down on the noise in the graph.

Diagram 3
You can clearly see from the chart that after all the variable costs and acquisition costs this company is making a loss of around £2.00 on each customer it acquires. They can do this though because on-going contribution from the customers is steady and predictable, and the company breaks-even on each customer it acquires after 12–17 months, represented in the graph by the line crossing the x-axis.

In analysing the investment opportunity the above chart highlights two attractive features: the lines being straight shows the revenue is steady and predictable; and the gradient increasing shows the business is getting better at monetising customers.


While data and KPIs are by no means the whole story for early stage companies, team and product playing massive roles, they do help us get a handle on whether the business has found product market fit and is now ready to accelerate. We’re not just looking for companies to produce lots of data, but how the team treats data is a good reflection of their culture.

Other markets that we look to invest in also have particular KPIs that we use to quickly assess investment opportunities, but those are a topic for future blog posts.