It’s no secret that data is king. But many companies still don’t understand how to best use their data to improve their business. Most businesses today are still relying on basic metrics like several customers or revenue growth. Those metrics alone can’t be used accurately to evaluate the customer success or failure of a company because they don’t take into account whether those transactions were profitable ones that will lead to repeat business or someone who signed up just once and never came back again.
That’s why it’s important for every business owner—especially those in B2B—to understand which customers should get special attention by looking at their lifetime value (LTV) instead of just focusing on sales volume alone.
Start with the end in mind
It’s tempting to jump straight into the solution, but a better way is to first start with the end in mind. This means you need to:
- Identify the problem you’re trying to solve or customer pain point you’re trying to address (e.g., “bulk discounting for large orders”)
- Determine what success looks like for that problem (e.g., saving time and money by reducing manual labor)
- Map out how your current solution could be improved on this point (e.g., using machine learning algorithms)
Look for anomalies and outliers
Anomalies and outliers are detectable patterns of behavior that deviate from what you expect from your customers. If you have a customer who consistently spends more than $1,000 per month on your product, for example, that’s an outlier — a behavior that can help you to identify potential high-value clients and give them special treatment.
Anytime a customer is performing differently than the norm, it’s worth investigating. That could mean anything from spending significantly more money than they normally do or having complaints about their experience with your company. In either case, knowing why something isn’t working as expected will help guide your next steps toward fixing it — whether that means sending more personalized emails or improving customer service overall.
Identify what is driving success
While it’s important to understand the data you have, you also need to ask yourself what is driving success. What is the biggest difference between your best and worst customers?
For example, you may want to run a focus group of your existing customers where you ask them about their experience with your product, as well as if there were any areas for improvement. One thing that could come up is that some people may feel like it took too long from when they signed up for an account until they got access to it.
To remedy this, you should decide to make a change in how you onboard new users so that they could begin using your product right away instead of waiting several weeks or months before they could dive in to getting ful use of the product. This simple tweak can lead directly to increased revenue because now more people were able to get started on using your service sooner than previously possible, leading to lower churn rates and higher rates of customer satifsfcation.
Don’t take anything for granted
Whether you’re trying to understand your customers or make sense of data, there are a couple of things you must keep in mind. First, don’t assume that you know what your customers are thinking. If you have any idea what’s going on inside their heads, it’s probably because they told you through surveys or interviews—and those responses aren’t guaranteed to be accurate.
While there may still be some correlation between past behavior and future purchases (or non-purchases), basing decisions entirely on the assumption that “people do this” can lead businesses down an unhelpful path where they’re constantly missing out on opportunities by not understanding who their target market is—not just what type of person fits into their existing assumptions about who should buy from them.
Using your data to make decisions can help drive customer success. It can also help you find ways to help your customers better and more quickly, which is a powerful way of keeping them happy.
