I have a great relationship with my banker (as an aside, that’s something all biz people should try to foster). Last year during a financial review we updated a few things on my profile. He had his PC screen at a point on his desk where we both could look at the screen. Always inquisitive, I saw a field in my profile with a dollar amount that had no meaning for me. I asked what it was. Turns out it was a figure the Bank tracks of what they “earn” from my using their various products in a year. They use it to rate my account from a customer service and marketing perspective.
Though this is not actually a true example of customer lifetime value, I use it as an introduction to the concept of giving a customer a “value” because it’s something we all can relate to. We all use Banks and we all know they rate us as customers!
Customer Lifetime Value, as a metric, is a forward looking number estimating the profit we expect to earn from an individual customer during the entire time they engage with us.
Depending on the type of industry this can be a figure that you calculate as an average for a segment, or it may need to be looked at for individual accounts if they vary widely.
In SaaS for example, it’s a figure easily calculated using things like the historical average amount of time a customer subscribes to the service, the calculated monthly profit from subscriptions, the number of current customers, and churn rates. For non-subscription modules, it can also be calculated as a factor of past behavior of spend, and future expectations of spending.
Seeing how the average CLV is trending over time, can be a metric that helps validate activities you are doing to improve overall customer satisfaction, or be an early indicator of problems. Everyone wants to see a trend that you are getting more profit from customers and that they are sticking around longer!
CLV can be a sobering statistic when planning customer acquisition costs. The ratio of CAC to CLV is often a metric used to determine the health of a company. In fact, VCs have an idea of what this ratio should be for some industry verticals and often use it to benchmark a company. Basically if the ratio is too narrow then you need to rethink your customer acquisition methods.
Aside from being an overall business metric, it can be a helpful indicator when looking at the engagement with a particular customer.
There are many reasons, besides churn, why a customer may not stay with your company. Their needs may change. They may outgrow what they are using, and need a bigger solution or need to graduate to another tier of service. They may just no longer need what you offer. Understanding more about the typical journey that a customer takes with our product and adjusting our engagement with them during it can reap great benefits in terms of extending the actual lifetime and the $value.
A lot of communications that are directed to customers are about acquiring the customer and introducing the product. These become meaningless to someone who actual stays with us. I liken it to the old sales advice, that once you have sold the customer then shut up. Continuing to pitch them on what they bought can actually result in un-selling them.
Rather than segmenting your customer solely on the product segment they are in, if you further segment them by length of service or depth of usage, then you can target them with communications that keep them engaged. This could help with not overpowering new users with unnecessary information, and not boring seasoned users with introductory stuff. By communications, I don’t only mean mailing lists, but hints or suggestions while they are using the product.
Knowing the CLV of a typical customer segment and then looking at where a particular customer is in that lifetime and how their spend deviates from this average can help you to make informed decisions about engagement with that customer. Yes, it will show you your power users that bring you value and you may want to reward. It will also show you your marginal users who could use help to more effectively use your offering.
Looking at your typical customer lifetime and value may also inform finding the right time to try to upsell or propose a different service. Testing could help determine the best time in the lifetime to start offering the customer something else. Also, triggering on usage information could turn your automated engagements into something more similar to a standard person-to-person sales process. For example, in a service where they may be different plans that are based on monthly rate and usage (like your home internet access and bandwidth), reacting to a trend that they getting close or over the usage band, could trigger a message inviting them to the next tier level. Showing them the value when they actual need it can be a much stronger message than a continuous drip feed that you offer something additional.
The point is to understand that customers come along with us for a journey over time. We are often so focused on getting new customers, that we often treat long-term customers indifferently. Instead we should nurture those relationships so that we extend them and increase the value that we bring each other.
Photo credit: Microsoft Clipart