As more and more businesses expand their online presences, they suddenly have access to a wealth of potential data they never had before. In recent years, marketers have developed a number of different strategies to track and quantify consumer habits. Yet some of the most useful information you can get comes straight from your customers themselves in the form of customer experience metrics.
CX metrics - like NPS, CSAT or CES - utilize answers provided by customers to directed questions about their experiences with your brand. There's no doubt that these tools have a huge role to play in optimizing company growth. Yet those who set unrealistic expectations about CX metrics often end up disappointed with their results. This article sets the record straight regarding some of the key pros and cons of CX metrics.
CX metrics come in a variety of different forms, including Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), and Customer Effort Score (CES). While each of these methods has its own particular set of strengths, they also possess distinct advantages as a broader strategy.
Capturing Difficult to Measure Information
To begin with, CX metrics allow you to measure things about consumer behavior and attitudes that are otherwise very difficult to quantify. NPS, for instance, allows you to gauge the extent to which customers like your products — and, specifically, their willingness to recommend it to others.
A metric like this is vital in determining the amount of naturally occurring word of mouth virality surrounding your brand. Few if any other methods exist of measuring how willing customers are to act on their loyalty to your company by telling their family and friends about it. Without CX metrics, you would have no way to capitalize on such information.
Working Towards Better Products and Services
Many of the traditional metrics used to quantify business success end up simply boosting a company's sense of vanity. Such methods focus primarily on the things you are already doing well, often by collecting data about user growth, numbers of page views, or overall revenue. While such metrics may sound good at a board meeting, they aren't always the most productive ones to focus on.
CX metrics, by contrast, do away with unnecessary fluff. Instead, they offer clear-eyed information about the areas in which you can still improve. In many cases, they do so by allowing customers to pinpoint exact areas where their experiences left something to be desired.
Allowing for Detailed Customer Feedback
Some of the most useful information gleaned by CX metrics comes from customers who have had less than stellar experiences with your company. Depending on which CX metrics you choose to employ, and how you decide to customize them, you can often get even more detailed feedback about exactly what went wrong for them.
Other methods of collecting consumer data often fail to capture this kind of valuable information. As a result, companies often struggle to determine the precise cause of customer experience breakdowns.
Identifying Your Most Loyal Customers
CX metrics don't just provide information about unhappy customers — they also you to know exactly who your greatest supporters are. This kind of information is worth its weight in gold, since such customers have demonstrated a willingness to go the extra mile in promoting your products and services.
Once you know who those promoters are, you can send them special offers to encourage their further loyalty and support. For instance, you might incentivize them to spread the word by offering referral bonuses.
In and of themselves, CX metrics are almost never a bad thing. Simply put, the more information you can get about your customers, the better. Yet if you aren't careful, CX metrics may also work against you in a number of ways.
Delivering Incomplete Data
One of the first things to realize about CX metrics is that, in order to prove useful, you must capture a fairly large number of responses. If your data set is too small, the information you end up with may not be reliable. Statisticians refer to this phenomenon as excessive variance. In essence, you simply haven't received enough feedback to get a trustworthy idea of how most customers feel.
Unfortunately, many companies plow ahead with revisions based on this early information. Even once you've gotten enough initial data to paint an accurate picture of your current CX, it will take a lot more data to start tracking changes over time. Those who start making changes too quickly often fail to solve the issues. Worse still, they may even end up making changes that exacerbate the original problem.
Falling Prey to Bias
Another way that CX metrics may mislead you in the decisions you make comes in the form of bias. There are two forms of bias that prove especially problematic for many CX scores: segmentation bias and self-selection bias. Segmentation bias is often built into the very nature of a CX metric.
Simply put, it isn't possible to have every single customer fill out a CX survey. Therefore, some method must exist of selecting who does and does not provide this kind of feedback. Segmentation bias occurs when that selection does not accurately represent your overall customer demographics. Believe it or not, segmentation bias may occur even when using automated software.
Self-selection bias can skew your data in a much different way. Self-selection bias occurs as a result of the fact that certain individuals are simply more likely to respond to a CX survey than others. That smaller subset of customers often ends up painting an incorrect picture of the feelings and experiences of the larger group.
Avoiding Common Pitfalls
Fortunately, it is possible for companies to avoid the cons of CX metrics by utilizing a reliable customer experience management platform, or CXM. A CXM can improve your CX metrics in two key ways. Whereas normally only a small percentage of customers will fill out surveys, a well-designed platform can greatly boost that number, giving you a score for as many as 100 percent of your surveys.
Second, a good CXM can actually predict the CX metric of a customer before they have filled out a survey, simply by observing their behaviors as you engage with them. This allows you to take a far more pro-active approach to eliminating problems, instead of waiting until after the customer has registered their dissatisfaction.
Whatever your take is on collecting these metrics - knowing the benefits and issues between them is half the battle.