Track when was the last time, how often and how much value a client gets from using your platform.
I’m hearing many more companies and customer success teams talk about Life Time Value (LTV) as a metric to measure the return they get from a client. LTV has been a common phrase in acquisition marketing for a very long time. It’s a simple calculation that totals up all of the revenue generated from a single customer for the time they are using your services. For example, if you charge £20,000 for a one year license, and a client uses you for 3 years, then your LTV for that company would be £60,000. Divide that by your Customer Acquisition Cost (CAC), and you have a genuine Return on Investment (ROI) number. An important part of LTV is that allows a company to commit to future investment as they are better able to predict the future revenues they receive from a client.
However, there’s another idea I believe we can borrow that would be very interesting to use for SaaS businesses, and that’s Recency, Frequency, Value or RFV. This isn’t so much one metric, as three data points, and goes beyond looking at just the overall revenue generated, to also consider when did you last receive value, and how often. This analysis would often be used by companies to segment their audience base and I think we can take some of this into SaaS as a measure of customer health.
In this case, I’m going to swap Value from being your invoice amount (i.e. revenue) to the perceived Value your client gets from your application:
Recency - When was the last time the client got value from your platform
Frequency - How many times in a given period does the client get value form your platform (e.g. last 30 days)
Value - What is the measurable value the client gets from your platform?
We can assign numerical values to each of those, and produce a sum. For example:
‘Value’ will very much vary based on your own platform, but this could be something like the number of campaigns served, or the number of influencers identified. If it’s hard to measure business outcomes in your platform, it could also be how many times a sticky feature is used.
Note that the Recency is a negative value, as we want a longer period to be represented as a subtracting factor in the overall score. E.g. someone who last saw Value in your product 7 days ago is not as good as someone who saw Value only 3 days ago. Depending on how you’re calculating Value, you might also want to weight that number in the calculation to make sure it has the correct significance.
To make this an efficient process, you will need to be tracking the ‘Value’ action in your platform and passing it back to your dashboards automatically rather than manually. It’s not just the overall ‘score’ you would want to monitor, but also add triggers to each of the individual elements. For example, if a client hasn’t seen your system generate a valuable outcome for 10 days, this should alert the CSM so that they can review the account a see what’s going on, asking appropriate questions about their current objectives and priorities.
As with any Health Score, you would want to create a manageable amount of segments so that your Customer Success Manager can take appropriate and timely actions. Just as with LTV being a measure of future profitability, you can use RFV as a measure of future customer health. Over a period of time, when you analyse your churn data, you will most likely be able to correlate it with this score, and once you have enough data, you can start to build a prediction model.
This RFV approach fits into my concept of Day 364, where if you ran the RFV numbers early on in a contract, the client would have a very low score as you are yet to prove yourselves, meaning there’s lots of good work to be done yet.
The advantage of using RFV like this is that it’s measuring the value the client is getting from your platform and goes beyond just engagement or product adoption. It’s not just logins or page views, but real outcomes that relate to how you’re making the client successful or not.
Simon has over 10 years helping clients achieve their goals through the use of software. Having previously lead Customer Success teams in London, Europe and New York City, Simon now owns Kupr Consulting working with B2B SaaS companies to improve their Customer Success teams and processes.
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