Marketing TechnologyData & AnalyticsSix customer data metrics that really matter

Six customer data metrics that really matter

62 percent of executives report relying on their gut when making proposal or partnership decisions, but research confirms that the best decisions are made based on data. Here are six metrics to watch for customer data.

Intuition is a powerful thing. It can tell us when our spouse is upset with us, when a stranger is starting at us, and even when we have a chance to save a life.

Intuition, however, is a dangerous way to manage your company’s greatest asset: its customer relationships.

Although 62 percent of executives report relying on their gut when making proposal or partnership decisions, research confirms that the best decisions are made based on data.

A meta-study detailed in Scientific American found that in both work and academic settings, decisions made on hard numbers alone fared better than those made with a combination of data and human judgment — including the judgments of subject-matter experts.

Six customer data metrics you should pay attention to

Whether you consider yourself a customer whisperer or not, there are some customer metrics that are critical to monitor. Not only can they inform your customer success strategy, but they can provide key insights into product, investment, and departmental performance issues.

1. Customer lifetime value (CLV)

Although CLV can be tough to predict in a company’s early days, this metric can inform a huge range of business decisions.

How much, for instance, can the company afford to spend on customer acquisition? At what point do retention efforts become unprofitable? What separates a “loyal” customer from the rest?

To find your CLV, start by determining your average purchase value and subtracting from it average purchase frequency rate.

Next, multiply that customer value by the average customer lifespan to determine customer lifetime value.

To grow your CLV, focus on finding “good” customers — in other words, those that tend to spend more or cost less to acquire than their peers. Then focus on increasing customer satisfaction.

2. Customer churn

How can you know whether customer dissatisfaction is the culprit behind a low or falling LTV score?

Look at customer churn, which describes the rate at which customers stop doing business with you.

Calculate churn rate by dividing the number of customers lost in a given period with the number of customers that you started the period with.

A churn event is obvious for subscription-based businesses. But other ecommerce companies should be sure to define what constitutes churn as well. For example, it could mean not making a repeat purchase that quarter.

Aside from the obvious loss of revenue, why is churn such a critical metric to track? High or rising churn signal customer dissatisfaction. It can also increase acquisition costs because unhappy customers are often eager to share their experience with others.

3. Cost of retention

When a customer is at risk of churn, you should invest in retaining them.

But beware: When the cost of retention exceeds your customer acquisition costs — or, worse, customer lifetime value — retaining that customer becomes a bad business decision. If you’re making changes that customers value, expect your cost of retention to fall in tandem with your churn rate.

Unfortunately, this can be a tricky metric to calculate.

Remember that the cost of retaining a customer includes everything from the customer success team’s time to the technology used to do so to the advocacy materials prepared for the purpose. Don’t forget to factor in the account management team and onboarding team’s costs, too.

Finally, add those values up, and divide that sum by the number of customers retained in the current year.

4. Monthly ticket volume

If your company’s churn or retention costs are on the rise, take a look at how many support tickets are submitted to your team each month.

Be sure to sort out general queries and spam for an accurate count. A jump in support tickets could signal that a new feature isn’t functioning properly, but it could also be due to an influx of new users.

To reduce ticket volume, invest more in customer success. By proactively monitoring usage signals like session frequency and duration, customer success identifies and solves customers’ challenges before they submit a support ticket.

Customer success should also be a primary player in reducing churn and boosting lifetime value.

5. Average response time

Closely related to the monthly ticket volume metric is average response time. Not only does every customer dislike waiting for a reply, but long response times can point to complex support issues and staffing shortages.

Check it any time new product features are added, customer churn grows, or turnover spikes on the customer success team.

What’s more, dashboard software provider Geckoboard has found response times are closely correlated with customer satisfaction — a notoriously difficult metric to measure.

The reason is that customers value timeliness above efficiency, professionalism, knowledgeable agents, and even resolutions, according to Interactive Intelligence Group’s Customer Experience Survey.

Read also: How to use chatbots as part of your marketing strategy

6. Net promoter score

Your net promoter score describes how likely your customers are to suggest your service to someone else. An effective proxy for both brand loyalty and customer satisfaction, NPS scores classify customers as detractors, passives, and promoters based on their zero to 10 ranking.

To find your NPS, start with a survey or, better yet, a feedback bar similar to Asana’s.

Then, detract the percentage of detractors — that is, the individuals who responded with a zero through six — from the percentage of promoters, or those who ranked you a nine or 10. If, for instance, 60 percent of respondents were promoters and 8 percent were detractors, your NPS is 52.

Takeaways

No one data point can tell the full story of a customer relationship. When combined, however, they create a picture that tends to be true to form.

Data-driven customer decisions may not always be the right ones, but they have a far better track record than those made by the gut.

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