While we may want to have an easy formulaic answer to how to track LTV, it really depends on your business and your customers. How and why your track it can be unique to your business. So, what do you need to consider when making decisions around it?
LTV, lifetime value, at its essence is how much revenue can I expect a customer will spend with me over the duration of the time they remain a customer, based on the average purchase patterns of similar customers in the past.
With the simplest formula being – average purchase price * average number of purchases per period * number of periods the average customer remains a customer.
This can expand and collapse depending on the business model.
A SaaS subscription model, with a known monthly purchase price, likely looks at total customer LTV per month as a prediction of growth, also considering trends in new customers and churn rates each month.
Some companies like to add in other financial figures such as customer acquisition costs and ongoing post sales service costs, to make it a profit value rather than simply a revenue value. While others track those separately, because they are zeroing in on the impact of LTV on those costs.
Some people who have customers extending out for many years, factor in expected changes in future revenue and cost. Prices and costs are likely to change over time, and they want to have that built in.
Some people track the historical real value and look at trends and breakdown cohorts. Some people use it for the predictive value of what it tells you about revenue in the future.
So, there are a lot of different “it depends” to consider before you consider your particular it depends. I recommend stepping back and look at a wider view of lifetime value and what it means when considering your company.
Objectives are key
How you look at LTV is very much dependent on the why behind you look at it. I think you benefit from turning that why into an objective. And because I believe in setting OKRs to steer strategy, then I think those objectives are great candidates for using in your OKRs, with LTV possibly one of the key results or feeding into it.
For example, one objective might be to identify our most committed customers and nurture them to buy more. We might segment our customers in LTV ranges, and run programs to target ones in a higher range. Or conversely, we may set an objective to nurture customers that aren’t buying and run programs to target a lower range segment.
As above, we may also set objects around lowering our customer acquisition costs. And use the ratio of CAC to LTV as an indicator that we are doing this while still getting the right customers and retaining them.
What does LTV tell me about my customers? What does it tell me about my business?
How we approach lifetime value can tell us something about the culture of our companies. Are we trying to increase LTV by selling more to customers? Or are we trying to find ways to provide more value to our customers, so they purchase more. Value typically cuts both ways in customer engagement.
Looking at segments of our customers in different bands of LTV may lead us to refine our customer personas. It can steer us to learn more about a specific segment in the market, so that we can target them more effectively.
Company maturity can have an impact
LTV will be looked at quite differently by a recent startup than by an established enterprise. It might also be looked at quite differently in terms of existing products and new innovations. Or established markets and new markets.
When a company is new, or launching an innovative product, or venturing into new markets, they won’t necessarily have the historical information create a complete picture. And while there may be a lack of confidence in the metric, it provides a predictive indicator that can improve over time. At the same time, established companies may be at risk for disruption and may have too much confidence in the number. And be surprised.
I know the way I presented this looks at the risks to each scenario. It’s just a reminder that predictive analytics are just that. Predictive. And always need to be considered in terms of the assumptions you take.
What will you do with the insight you get from LTV?
Or a reframe of this question might be what other objectives might spawn from tracking LTV.
I’ve been hinting at this already, by talking about some of the programs you may run to achieve an impact on LTV. As well, we might look at LTV as a KPI and consider how this can inspire us to decide on even further objectives.
For example, the company with the steady LTV in an established market, might use this to manage the risk of disruption. Possibly considering other products that could be sold to this valuable cohort. Or test new markets, using LTV as a benchmark of viability.
In another example Aiming for a specific LTV:CAC ratio, may influence us to set constraints on campaigns, or for us to set an objective to try different channels.
Summing this all up…
What is important to consider is:
- Decide why you are tracking it. Since it is powerful, know why you are tracking it. Or better yet, consider an OKR where LTV is part of your key result.
- Pick a formula that fits your business model and objectives.
- Decide whether you are looking at historical trends or using it as a predictive module.
- Decide whether you are tracking it per segment, or overall.
- Use it to create programs to increase the value both you and the customer get from your commercial relationship.
- Be open to reviewing this periodically and make changes/
LTV is a powerful metric when grounded by your marketing and sales objectives. What is your “it depends”.
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