Data usage: How much are you spending to acquire customers?

You’ve got to spend money to make money. Spending is great if you are sure of your return on investment. It’s not so good if your costs are higher than your income and the unit economics simply don’t work.

With that in mind – what is the total cost to you to add one more customer?

Imagine if you could ask and answer the following questions:

  • Is the cost to acquire customers balanced out by the income from those customers?
  • What is the lifetime value (LTV) and how quickly do you recover those upfront costs of acquisition?
  • How are your costs of acquisition changing over time?
  • How does it look by seasonal/demographic/geographic cohort?
  • Which marketing campaigns have been most effective?
  • Is your customer retention up to scratch?
  • What are the levers you can pull to drive the costs down and the revenue up?

How could you get to a place where that level of questioning (and more importantly answering) is possible? Let’s explore it.

Whether you sell goods or services, direct to consumers (DTC or B2C) or to other businesses (B2B), there are costs to going to market.

The list goes on.

So what is the total cost and how do you calculate it?

You can look at your bottom line each month but that would definitely fall into the category of a “lagging indicator”. You can manually tot up all of the above (and any others you can think of) in your general ledger each month.

Task your finance team with the job (along with everything else they have to do). Hope they don’t forget to dot the t’s and cross the i’s. You know. Attention to detail.

That feels still a bit laggy though, not to mention expensive to do, and fraught with the possibility of human, excel related error (we’ve all been there).

Alternatively, you could automate it.

Do it once, do it well.

Create a single source of truth, into which all of the aforementioned data (marketing, sales, tooling costs etc) gets pumped. Build the logic to connect it up and view it per customer or lead. Add in the invoice/order data for your revenue. Calculate it all. Schedule it to run each night.

At that point, you can really start flying with the analysis.

Don the white lab coat and the safety specs and get some scientific method going.

Pull one of those lever (in a controlled, AB test manner). Monitor the results. Roll out the success. Repeat.

With a cost of customer acquisition to lifetime value ratio calculated each night for you, the opportunity to analyse and optimise is truly unlocked.

The “difficult” bit – that bit in bold above, is the bit kleene.ai are here to solve.

Want to know more? We’d love to chat. Please get in touch.