This post is our second in a series about recency, frequency, monetary (RFM) analysis, and why understanding how to leverage its concepts with data is crucial to your online business.
Suppose your commerce business is outperforming revenue goals, quarter after quarter, as it enters the new year. Your designer apparel line first hit $1,000,000 in GMV this month last year, and has grown at a 10% every month since. This year, you are responsible for projecting the business’s 2017 growth accurately – and with it, estimating cost of sales, inventory counts, and countless other budgets. A key question for you to understand: what can most reliably predict future revenue in your customer base?
As with the other pieces of RFM analysis, there are several passable answers. Any online business attempting to forecast should want to know:
- What percentage of your customers are new customers? (What percent are returners?)
- What products on your site do customers return for?
- How long does it take for the average customer to make their next purchase?
- How long before we can tell that a customer won’t come back?
The answers to these questions, of course, differ across each business’s data set. They all concern customer purchasing frequency — correctly predicting and encouraging this frequency is crucial to your business’s continued growth. Each answer above is merely interesting on its own – but understanding all questions together, in the context of the RFM model, can enable real action for your business’s customer retention.
In our last post, I posed the question of how a marketing manager might predict where ad dollars are most effectively spent. Keeping these KPIs on hand can be tremendously insightful:
- Repeat order rate. How many of your purchase orders are from returning customers? Is that ratio growing or shrinking? A growing repeat order rate is an incredibly healthy sign – it indicates increased engagement with your brand, trust with your customer base, and validates the fact that repeat customers are inherently more valuable than new customers. A stagnant, or shrinking, repeat order rate should probably make you be wary of…
- Churn rate. Traditionally, it’s a SaaS metric — but for transaction businesses, it’s critical to have a grasp on. If your revenue is flat, you can think of churn as the complement to the retention rate. If repeat customers are leaving, and they’re your most valuable customers, you should be most concerned about an increasing churn rate.
- Average time between repeat purchases. If you’re lucky, and a group of customers are regularly, predictably buying on your site – how often are they doing so? This frequency has a lot to do with market forces outside of your control – seasonality, or the nature of the product you’re selling. (Your pet food site, for example, probably has a higher purchase frequency than my discount diamond ring shop.) But much of this frequency is in your control, though – how, if possible, might it be accelerated?
- Repeat order probability. The key determinant of whether a new customer becomes a repeat customer. Most marketers consider the first order as the conversion – what about the second order? Winning the new customer in that crucial, early stage is the difference between $100 and $1000 across that customer’s lifetime.
Options to take action
There are quite a few approaches you can take to take action on your customers’ purchasing frequency – luckily, each action can be analyzed and justified with the data in your database today.
One set of approaches involves accelerating the customer purchasing frequency — that is, minimizing that window of time between customers’ orders. Coupons or rewards programs, for example, can turn a yearly customer into a quarterly customer – building a level of comfort with the consumer along the way.
Another set of approaches involves ensuring that new customers purchase frequently in the first place – that is, placing a focus on retention from the very first interaction with your business. For our metaphorical marketing manager, marketing to these new customers is a worthy investment. Understanding how this subset of customer responds after being marketed to, through a comparison tool like cohort analysis, can quickly prove if the investment is worthwhile.
So far, we’ve uncovered the insights that are apparent in measuring your customers’ recency and frequency habits. Both of those lead to the bottom line – what are their monetary habits? Keep a look for more answers in the final post of this series. If your business is searching for answers like these with a world-class product and team – please sign up for a demo to find out more.