Is Data Driving Your Decisions?

Eight Ways Customer Analytics Can Give Your Company a Competitive Edge

by Jeff Sauro

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, where costs and outcomes are fuzzy to those on the outside.

Your company’s success and even its survival depend on attracting customers and keeping them happy – and proceeding based on guesswork and assumptions just isn’t a viable strategy. Everything is measured and evaluated these days. That means decisions across all departments must be made using solid research and cold, hard numbers – and leaders must understand this data.

The bottom line? 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,” which I learned while working at Intuit. 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.

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).

The customer analytics umbrella covers not just number-crunching but also facilitating a product usability test in the first place. Even the way a question is phrased can impact the quality of the participant’s feedback. For instance, instead of directly asking, “Why did you click that link?” it’s better to ask, “What about the link led you to click on it?” This will get the participant thinking about her motivations and mental models, whereas the first question might leave her feeling defensive. Small details like these really can make a huge difference in your company’s product development, marketing, and overall strategy.

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 important – whether the touchpoint motivates people to buy your product or service.

For example, I once worked with a national advertising agency that placed ads in weekly newspapers. We wanted to find out whether 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 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 more than a quarter misunderstand the product’s features, and that half feel that the setup 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 from his or her first purchase to the final purchase. 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 and a decrease in customer loyalty and eventually they impact profits negatively.

Customer analytics can provide an accurate picture of your company’s bad profits. 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 of years ago, we found that about 17% of Adobe Photoshop users were detractors. Assuming everyone pays around the same price for a Photoshop license, some 17% 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?

An examination of revenue by customer segment usually reveals that the Pareto Principle holds true: A minority of customer segments create the majority of profits. Identifying more profitable segments allows you to focus your efforts on keeping these customers happy while increasing their purchases. For instance, maybe you decide to funnel a larger percentage of your marketing budget toward creating advertisements that target millennials after segmenting your customers. What’s more, segmenting can reveal underserved customers for whom specially designed and marketed products or services can be created.

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.

Jeff Sauro is a Six Sigma-trained statistical analyst and pioneer in quantifying the customer experience. He specializes in making statistical concepts understandable and actionable. He is the founding principal of MeasuringU, a customer experience and quantitative research firm based in Denver. Clients include Wal-Mart, PayPal, eBay, Lenovo, Google, and Charter Communications. Jeff has published over 20 peer-reviewed research articles on statistics and the user experience. He has written four books, including “Quantifying the User Experience: Practical Statistics for User Research” and “A Practical Guide to the System Usability Scale.”