LTV - CAC is meaningful only with the related resilience.
The fundamental metric to plan our business on the web is the balance between the LTV and CAC.
Since our prices are well known, as well as the variable costs of each sale, the contribution margin for each sale can be consequently determined.
The contribution margin, multiplied by the number of repeated purchases the customers does with us during his useful life, generates the so-called LTV.
To estimate the LTV, we should hence estimate the number of repeated purchases by the customer. This number might come from our thoughts before we launch the business or from historical data coming from the actual customer base behaviour.
The CAC is simply the amount of money spent in marketing and communication in a given period, divided by the number of new customers acquired. To estimate it, we can proceed as we did for the LTV.
With these two values estimated, we can basically build our business plan.
Did you consider there may be a worse-case scenario?
Usually, the entrepreneur/e-commerce manager/product manager tends to overestimate the LTV and underestimate the CAC.
For this reason, the LTV – CAC, key metric of the business plan, should be accompanied by a second figure describing what it may happen in a worse-case scenario.
The worse-case scenario may shows-up for many reasons.
For example, a customer may get back to buy fewer times than expected because a new competitor launched an alternative product or an aggressive marketing campaign.
So, even if your estimation comes from historical data, being ready for a worse-case scenarios is the right approach.
Got you covered with a proven method and an easy tool (a spreadsheet), free forever.
CAC and LTV initial estimation
Suppose our business has an average contribution margin of €15. This means that the average sales ticket minus VAT and all the variable costs generates and economic value of €15.
Let’s then assume that the average customer, during his useful life of 12 months, completes four purchases from us.
To acquire such customer, we also assume we need to spend €35 in marketing and communication.
In this scenario, our business plan tells us that in a given year, the average customer generates an operating margin of €25.
This €25, multiplied by the number of new customer acquirable with the marketing and communication budget, we should bear the fixed and overhead costs (e.g: workforce, office, utilities, technology stack).
The worse-case metric
Starting from the initial situation we can see, through a sensitivity analysis, what happens for fewer customer repeated orders and greater customer acquisition costs, both varying at steps of 10%.
What we see is that, when the CAC is 10% greater than planned, we are losing 8% in operating margin.
In other words, our capability to bear the fixed and overhead costs is reduced by 8% because the CAC is not €35 as assumed but rose up to €38,5.
We may bear such an error in estimating the CAC. But can we bear an error in estimating the customer repeated purchases? Definitely less!
An LTV 10% lower than planned, reduces our operating margin of 18%.
When we combine a 10% error in both CAC and LTV, the operating margin is reduced of 26%. This is the definite metric to put right after the LTC-CAC.
Hence, we would state that our business model generates operating margins of €45 with a 26% resilience, caused by an error of 10% in estimating both LTV and CAC.
Be careful, because when the resilience is greater that 100%, it means that your operating model will lose money for any deviation of 10% in LTV and CAC.
The analysis is set on a contribution margin of €15.
With higher contribution margins, we can bear better any error on both parameters, but the most critical factor still is the number of repeat purchases.
The graph above explains what we should expected from the business case described. Do not expected to apply the same numbers to your business, because yours are different.