But there are good reasons researchers and designers should have some idea about the monetary value of a customer.
Measuring ROI: If your efforts lead to improving the user experience and that translates into retaining more existing customers or gaining new customers, knowing the lifetime value of a customer is a solid way to justify your efforts as a return on investment (ROI).
Prioritizing design improvement: There’s always a limited amount of resources and too many features to fix or add. While designers and developers don’t need to know how to calculate every customer or account metric, understanding the value of a customer helps with making more intelligent prioritization of features. If you know that a feature is less used it might not make it into the next release. If, however, that feature is popular with more profitable and loyal customers, it makes both design and business sense to include it.
Calculating the value of positive word of mouth: When you estimate how many promoters you need for one new customer, you can then put a dollar amount around the gain. We’ve shown that SUS correlates with the NPS—meaning one of the best ways to attract and retain customers is to make the experience easier.
You don’t need to get too complicated with CLV. Here are five steps to compute it and the data you’ll need. If you want more details I cover it in Chapter 3 of Customer Analytics For Dummies.
1. Find the average order value or revenue per product.
If you have access to sales data, you’re in good shape. If you don’t, you can estimate revenue. One way is to average the revenue from several customers (within a segment or from your market as a whole). The larger the customer sample, the more precise the results are. If you know the typical sales price for a similar product, work with that price. Just be sure you and your audience know the assumptions built into your calculations. For example, Adobe Photoshop sells as a service for around $20 per month. While not all customers pay exactly $20 (because of bundle discounts), it’s a good place to start.
2. Estimate the frequency of the customer’s purchases.
The appropriate timeframe, called the purchase cycle, depends on the industry. For purchasing desktop and laptop computers, it’s likely two to four years; for rental cars and airline tickets, it may be a few times per year depending on the customer segment. For the Photoshop license, you can assume that the customer is on a monthly plan, so you have 12 purchases in one year.
3. Calculate the revenue per customer over a typical “lifetime.”
You’ll want to know the typical tenure of a customer (hence the lifetime in CLV). Multiply the revenue per purchase by purchase frequency over that lifetime. For example, over a one year period, the expected revenue from a Photoshop license is 20 x 12 = $240. If the typical customers lifetime is say three years on average, the lifetime revenue is more like $20 x 36 = $720 (or $240 x 3 years). When in doubt, use conservative estimates of customer lifetimes and cite your sources.
4. Compute the profit margin.
Usually only a precious few company officers, analysts, bean counters, and the IRS know a company’s profit margin, so it can be difficult to compute or obtain directly. But you can use industry averages as a way to estimate it if you don’t have it. Manufacturing businesses typically have low profit margins (around 7%), retail clothing around 8%, whereas software has high margins, typically above 70%. That’s the beauty and bounty of royalty-based products like music, books, and software. They have some initial fixed costs, but the future variable costs are extremely low and therefore profitable. How much does it cost to send someone bits to download and install? So one Adobe Photoshop customer has an estimated annual net value of about $504 ($720 * .7).
5. Include the retention rates and discount rates.
Customer churn is a bad thing. It’s a lot cheaper to retain than gain new customers. One of the best ways to do that is to have a great customer experience. The customer retention rate is the opposite of the churn rate and is the percentage of customers who repurchase over a specific period of time. If 800 out of 1,000 customers are still customers after a year, the annual retention rate is 80%. If you have the data, look at multiple years to generate a more accurate rate of retention. You can even look to your survey data, industry averages, or at worst, which customers stated an intention of remaining a customer.
The discount rate is an economic notion to calculate the present value of future revenues. The basic idea is that having money today is worth more than having that same amount of money at some distant point in the future. Would you rather have $10,000 today or $10,000 in ten years? In consumer software and especially Software as a Service (SaaS), lifetimes are years, so including the discount rate helps the accuracy.
The same principle applies to company profits. Future profits are discounted to account for their current value. If the lifetime of a customer is short (weeks, months, or a year or so), then the discount rate won’t have as much of an effect as a lifetime that lasts years or decades. Discount rates vary based on the value of future cash, but it typically varies between 8% and 15%, with 10% being a popular value, which we’ll use too. The retention rate and discount rate are combined and divided into the current estimate of lifetime revenue. Both reduce the CLV because at most you can have a 100% retention rate and a 0% discount rate.
So here’s the final formula for customer lifetime value (CLV) with the retention rate and discount rate included.
CLV = (revenue x frequency x lifetime x profit margin x retention rate)/(1 + discount rate – retention rate)
So here’s how you calculate the CLV for Adobe Photoshop:
CLV = ($20 x 12 x 3 x .7 x .8) / (1 + .1 – .8) = $1344
You can get more complicated with CLV by including more details on the cost to acquire a customer, but this formula offers a good approximation.
Not all customers are the same. Repeat this exercise for your major customer segments (ideally mapped to your personas). Different segments usually have different lifetimes, different average revenues and therefore different lifetime values. Identifying which segments and customers have higher values helps improve the accuracy of your CLV claims.
But don’t get overwhelmed with the details. Often even rough approximations to different segment CLVs can help prioritize and make a case for ROI. One of the best ways to improve the customer lifetime value for a company is to improve the value the customer gets.
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