Why Analysing Your Customer Base Matters in E-commerce

I see a great many people extremely preoccupied with making new sales to new customers. That is not a problem in itself, but it becomes one the moment you start believing that this is what brings profit into your e-commerce business.

As a rule, on the first sale you carry an acquisition cost for that customer. Your whole structural investment in marketing and sales goes into the account to bring that person in. The game really starts the moment you have brought that person into your company. When they come back and buy again, that is the moment you profit, because you no longer have to pay for that person — they were already there. This is what makes customer base analysis in e-commerce so important.

The Advantages of Selling to Existing Customers

It is cheaper to sell to someone who is already your customer.

Within e-commerce there are a few analyses that help you win those repeat purchases. The first is to run research with your audience and genuinely understand who these people are, what motivates them to buy, what their consumption patterns are and what sort of product they like. This is a deeper analysis, going beyond simple questions such as gender and age bracket. Getting into real depth on your audience gives you a far greater volume of intelligence. To give you an idea: with some of our clients here, we found out from people whether they lived in a house or a flat and, on the back of that information, pointed some ad campaigns at neighbourhoods with more apartment blocks, having understood that the audience buying the brand most lived in flats. It sounds mad, but that one simple move improved part of our numbers.

RFM Analysis for E-commerce

Another analysis you can run is an RFM analysis (Recency, Frequency and Monetary value). With it you get a far deeper view of your sales. You can place your customers into different groups and know who your most valuable customers are, which customers you are at risk of losing, who the new customers are, who the lost ones are and an endless amount of further information. With that RFM analysis in hand, the communication for each type of customer changes. After all, you cannot speak the same way to customers who are not the same. Your champion customer deserves different treatment from the customer who bought from your brand once.

Case Study

A simple case study looking at this went like this. We noticed a set of customers with a purchase frequency of one to two times a month over the previous four months. From there we split that set out differently and told them that, from that moment on, they would no longer pay for shipping on the e-commerce site. That one piece of communication took customers from one or two orders a month to three or four on the general average, varying a little, of course. But you will agree with me that, inside our own customer base, we managed to extract more revenue simply by understanding these people and understanding what motivates their purchase?

This is the present and the future of e-commerce: data science applied. Customer base analysis in e-commerce not only helps you understand consumer behaviour better, it also helps you optimise marketing strategies and increase sales.