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Analysis

The Key Limitations in Calculating and Predicting CLV

Calculating and predicting Customer Lifetime Value may seem straightforward, but the margin for error is high when using inadequate methods.

Matt Duczeminski
September 28 2019

If you’ve been with us since the beginning, you already know how to improve your average CLV over time. In this article, we’ll discuss some of the key difficulties companies face when calculating and predicting customer lifetime value—and explain how to avoid these obstacles.

Having Too Broad of a Focus

When it comes to dealing with quantitative data like CLV (or any kind, really), specificity is key.

Rule of thumb: if you don’t really know what you’re aiming for, you probably aren’t going to achieve it.

Chances are, your customer base isn’t homogeneous. No matter their similarities, they’re still completely different “types” of customers—each with their own unique set of needs and expectations.

Though calculating your overall CLV tells you what your “average” customer is worth, it doesn’t tell you much else. So you’ll want to go a step further and calculate your CLV for each customer segment. This will enable you to develop multiple initiatives and campaigns tailored to specific customers based on their engagement and spending habits. Ideally, you’ll be able to maximize the value of each audience segment.

Aiming too broadly when it comes to timespan can also render CLV data useless.

Considering the average of your CLV over a certain time period to be your “true” CLV is a massive mistake. It’s a similar problem to the one above; it tells you what your average customer was worth over the time period, but it doesn’t indicate what you should do with this data.

You’re looking for information regarding your customers’ spending habits at different points in time. By pinpointing moments where a segment’s habits led to an increase or decrease in overall CLV, you can dig deeper to determine the cause of the fluctuation—and then use this information to strengthen your marketing efforts in the future.

The Impossibility of Certainty

It’s impossible to know for sure what tomorrow will bring for your customers and your company.

Even if you manage to nail down the major factors that have contributed to an uptick or downswing in CLV in the past, there’s no guarantee these factors will have the same impact on your audience’s spending in the future.

Not only that, but there is are virtually infinite components that could have a huge impact on your CLV moving forward. Whether we’re talking about emerging technology and changing consumer trends, or massive shifts in the overall economic landscape, it’s impossible to take every potential scenario into consideration when predicting CLV—and that’s okay.

Predicting CLV means you’re making an educated guess as to what your future CLV will be, based on the information you currently have.

As time goes on, you’ll continuously collect additional information that can help you calculate your potential future CLV with increasing accuracy. So, while you may never fully reach 100% reliability in your CLV predictions, they should increase in accuracy over time.

Assessing Intangible Value

Spending money on your products or services isn’t the only way your customers bring value to the table.

For one thing, CLV doesn’t take into consideration acts of brand evangelism—such as recommendations and referrals—that bring in additional business.

It’s also difficult to nail down value provided by customer feedback. While reviews are definitely valuable to your organization, you can’t say that a given piece of feedback is worth x amount of money to the company.

There will also be times when your customers make untraceable referrals or recommendations. For example, if one of your current customers tells a friend about your brand, and that friend makes an initial purchase—but doesn’t mention the recommendation—you have no way of knowing that the referrer may be a bit more valuable than they look “on paper.” The same can be said for individuals who provide feedback or reviews anonymously.

Many intangible—and often untrackable—factors play into the true value a given customer will bring to your company throughout their lifespan with your brand. Unfortunately, predicting the future CLV of a given customer or segment only examines the direct value they provide through monetary transactions with your company.

Bottom line: if you’re only focused on CLV, you’re overlooking potential ways of getting even more value out of your customers—directly or indirectly.

Using Optimove’s Predictive Behavior Modeling Tools

Calculating and predicting CLV in more rudimentary ways is certainly doable, but it may not be all that practical.

For one thing, it may be overly labor- and resource-intensive to continually track and predict CLV on a regular basis. If all your time is spent going through the motions to calculate and predict CLV, you might not have time to figure out what the data actually means.

Secondly, the more hands-on your team is when calculating and predicting CLV, the greater the chances of human error. A missed data point here, a typo there… it can all add up to doing more harm than good.

With that in mind, you may want to consider using Optimove’s predictive behavior modeling software to help solidify your approach to predicting CLV. Not only will this give you a more accurate and complete sense of your true overall CLV (across the board and for specific segments and customers), but it will also allow you to develop marketing initiatives tailored to these specific segments as appropriate.

Schedule a demo with us today to start maximizing your CLV.

 

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Matt Duczeminski

Matt is a professional writer specializing in helping entrepreneurs improve relationships with their customers. He lives in Philadelphia with his wife, Sarah, and he'd probably get a lot more work done if his cat would stop bothering him.

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