In a global economy that’s becoming more competitive each year, every customer (and customer’s opinion) counts. Every customer interaction counts. Certainly, every dollar spent on keeping customers happy and coming back counts. That’s why every leader needs a good working knowledge of customer analytics. (Yes, even if your company has data scientists and statisticians on the payroll.)
Once upon a time, your company may have been able to shake it off if you threw a marketing idea against the wall and found it didn’t stick, or developed a line of products customers didn’t seem to like. That’s not true anymore. Companies just can’t afford to have ‘black hole’ departments, like sales and marketing for example, where costs and outcomes are fuzzy to those on the outside.
If you know what those numbers (also called metrics) are, how to collect them, and how to evaluate what they mean, you will increase your understanding of what drives your customers. You’ll also be better equipped to meet their constantly evolving needs.
Here are eight things customer analytics can help you and your company do:
Develop products customers want. Figuring out what customers want and what they will purchase is one of the holy grails of product development. If your company has been on this quest for years with limited success, fear not: Customer analytics offers several methods to help you define and prioritize what features to include in your products.
For example, one of these methods is a technique called ‘follow me home.’ You literally follow a customer home or to his workplace and then spend the day watching him do his job. Look for pain points and problems that might shine a light on opportunities for improvement.
During one such follow me home, a team of researchers noticed that retail customers were exporting their transactions from their point-of-sale cash registers into QuickBooks to manage their books. This extra step took time and could cause problems if done incorrectly. The developers came up with the idea of integrating QuickBooks with a cash register that eliminated a step for customers.
Conduct product usability tests. Chances are, your company field-tests products before mass-producing and selling them. (If you don’t, perhaps you should consider it!) Customer analytics can help you collect the right metrics when working with volunteer test subjects and mine your findings for valuable information about product usability (in other words, how effective and efficient your product or service is, as well as how satisfied customers are).
Figure out which “touchpoints” are most effective. Touchpoints are the places where customers find out about your company and products: commercials on TV and radio, ads on social media sites, newspaper coupons, brochures, word-of-mouth recommendations, etc. Customer analytics can help you pinpoint the number of potential customers each touchpoint reaches, how well the message resonates, and—perhaps most importantly—if the touchpoint motivates people to buy your product or service.
I once worked with a national advertising agency that placed ads in weekly newspapers. We wanted to find out if a coupon for Pier 1 Imports increased (or decreased) revenue. Controlling for differences in markets, we found that sales in cities that received the coupon did increase in a statistically significant way that weekend. We were also able to determine that the discount from the coupon was offset by the increase in sales.
Identify “pain points” on the customer’s journey with your company. Let’s say your company manufactures and sells laptop computers. You may think that you understand each phase the customer goes through when engaging with your organization, from the initial decision to buy a new computer to becoming a loyal customer. But how much of that “knowledge” is based on assumptions, incomplete impressions, and wishful thinking? Where, really, are the barriers to making the sale? Customer analytics will tell you.
Let’s say you thought price was your biggest barrier to improving sales. But when you really analyze the data, you find that 30 percent of prospective customers aren’t aware of your company in the first place, that over a quarter misunderstand the product’s features, and that half feel that the set-up process is too difficult. The point is, if you do not evaluate and measure each stage of engagement, you’ll miss vital opportunities for damage control, improvement, and innovation—and you might waste resources trying to alleviate pain in the wrong places.
Decide how much money to devote to customer acquisition. As its name suggests, customer lifetime value (or CLV) is the total profit that a customer generates for your business between his or her first and final purchases. This metric is important because, among other things, it can help you evaluate how much money can reasonably be devoted to customer acquisition.
If it costs $1,000 to acquire a new customer through marketing, sales, and production costs but that customer generates only $750 in revenue over the typical lifetime, that’s obviously bad for business. And the longer the customer lifetime is, the less likely you are to come to this conclusion organically. Sounds simple, but unless you proactively gather the numbers and weigh acquisition costs against CLV—which many companies don’t—you might not realize you have a losing strategy until it’s too late.
Keep customers satisfied AFTER the purchase. You may think that once a potential customer becomes an actual customer, your job is done. Not so! Now you have to ensure that the customer will return and (ideally) recommend your company. One of the most effective ways to understand what drives customer loyalty, is to use customer analytics to conduct a key driver analysis.
Key drivers are things like quality (Are your products reliable? Do they work as described?), value (Does your product give buyers the best bang for their buck?), utility (Does your product offer essential features?), and ease of use (Can customers use your features without frustration?).
A key driver analysis tells you which features or aspects of a product or service have the largest statistical impact on customer loyalty. It can be conducted for all customers but also for each of your different customer segments. At the end, you’ll be able to identify the most popular or unpopular features or aspects of your product or service and have customers rate that experience as well.
Identify and reduce bad profits. How does it feel to pay the check at a restaurant where you had terrible service and bad food? Or how about paying $150 to change your airline ticket reservation? In these examples, companies financially benefit from a customer’s negative experiences. However, they’re “bad profits” because they lead to resentment, a decrease in customer loyalty, and, eventually, they impact profits negatively.
“Customer analytics can provide an accurate picture of your company’s bad profits,” Sauro says. “Even if you don’t have access to financial data for your company or a competitor, you usually can estimate the percentage of bad profit revenue. For example, when my company measured customers of consumer software products a couple years ago, we found that about 17 percent of Adobe Photoshop users were detractors. Assuming everyone pays around the same price for a Photoshop license, some 17 percent of Adobe’s revenue from Photoshop comes from detractors.”
Find out who your most and least profitable customers are. Some customer segments are more profitable than others. For instance, depending on your industry, you may have “regulars” who do business with you on a weekly basis (or even more frequently), and others you see only once in the proverbial blue moon. But have you ever drilled down on what your regulars may have in common? What’s their age range? Their income level? Their education level? Where do they buy your products: in a store or online? Do they tend to make significant purchases after a life event like having a baby, or during a particular time of year?
Good customer management comes from good customer measurement. The more you know about collecting and interpreting data, the better decisions you’ll be able to make about—and for—your customers.
