Customer Lifetime Value is considered by 75% of North America’s top business executives as “an extremely important” indicator of their business’s health. Understanding CLV and how to maximize it is crucial to your bottom line.
Most businesses today have a general understanding of what CLV means. But when you dive into the details, there is a lot missing. Today, machine learning helps businesses find more predictive, insightful and automated ways to tailor their businesses to their customers. And this will form the future of how we do business. Despite this, many businesses fail to capitalize on the technology available to them, and they leave value on the table as a result.
So what is CLV? How do you measure it? And how can you go about increasing it? Find out with this infographic from Vidora:
To learn more about how to leverage machine learning to improve customer lifetime value, check out this feature in VentureBeat. In the article, we go through the key questions a business should ask itself when looking to implement an ML solution, some of the typical use cases we see here at Vidora, and the best ways to evaluate whether ML is giving your business the results it’s looking for.
