Businesses that have regular repeat customers need to focus on retaining these customers’ loyalty and developing ways to increase transaction frequency and value. Businesses that deal with irregular (or once-only) customers need to give relatively more attention to encouraging advocacy and especially to improving the effectiveness of the sales process—those businesses generally have high-value products or services.
Customer retention, transaction frequency, and average transaction value are critical Key Performance Indicators that are not managed well by most businesses. Every business (or unit within a business) can be classified on the basis of a standard transaction frequency (e.g., it’s an “x times a day, week, month, year” type of business). Customers could be classified by their frequency compared to the standard. Trends in the proportion of customers falling into different classification levels are an indicator of shifting loyalties.
Collecting this “guestimate” of the percentage of revenue from regular customers enables you to estimate an average transaction frequency for GamePlan. For example, suppose your client estimates that 60% of revenue is from regulars, the regulars average 40 transactions per year, and the average transaction value is $80. If you know total revenue (say, $2.4 million), you can calculate the amount from regulars is $1,440,000 therefore given an average total transaction value for the year of $3,200 there must be about 450 regular customers.
But if you don’t know the number of, the average transaction value or transaction frequency of, non-regular customers you can still estimate it. You can easily ask your client to run an eye over the transaction listing and calculate an average transaction value (ATV) for 40 regulars and 40 non-regulars – that’s enough for a high level analysis. Let’s suppose the ATV for non–regulars is $45 (compared to $80 for regulars). Since we know they account for revenue of $960,000, the number of transactions is about 21,333.
Now suppose your client estimates, based on an analysis of the transaction data, the non-regulars on average deal with the business four times a year then given 21,333 transactions there must be 5,333 non-regulars. By sampling a few more transactions you’ll get a sense of the range of ATV which you can use to get a sense of the range of the number of customers and then by sorting the list you’ll get a sense of who might be worth giving special attention to. This is the whole point of data analysis. Big companies call it BIG DATA but it’s all relative and the more you analyse the better sense you get of who you’re dealing with. I can say without hesitation that when i talked to my clients along these lines they really start to understand how immensely valuable we can be. Try it, you will surprise yourself and delight your clients.
The questions that need to be asked of your clients are: (1) what are you doing proactively to convert those customers to regular status (the upside is far greater than increasing the frequency of existing regulars), and (2) what are you doing to ensure that regulars remain loyal? A very large number of new non-regular customers will be required to replace the revenue and profit from a regular customer’s defection.