Episode 26 - Customer Lifetime Value: Are you measuring right?

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🤖 AI Feature

The Martech tribe and Chief Martech have just dropped the AI landscape report.

Some key highlights include: 

• Copy generation is the top GenAI use case 

• After content, leveraging GenAI for data is the second most common category use case 

• Aggregation beats consolidation: Contrary to expectations of consolidation, the Martech industry continues to expand with more specialised tools catering to niche needs.

• Emerging role of customer journeys: Aggregating customer journey data and experiences across multiple touch-points and technologies powered by inter-connected AI Agents is a crucial future use case and vision.  

📰 Top Story: Customer Lifetime Value - are you measuring right?

In episode 3 of this newsletter, we unpacked the 3 most important retention metrics, and one of those is Customer Lifetime Value. 

In this episode, I include a definition of CLV, an interview with the Customer Value Guy and a checklist of common mistakes to avoid. 

Definition of CLV: 

CLV is a forward-looking, predictive metric that measures the present value of future cash flows attributed to your existing customer base.  

It includes the length of time the relationship is predicted to last, the volume of transactions now and expected in the future, the margin of each transaction, and non-direct behaviours (e.g. referrals and sometimes content consumption). 

There are many different ways to calculate CLV, but the one I favour includes: 

• Historic customer-level margin 

• Predicted additional tenure and margin

• Predicted upsell/cross sell propensity and margin 

• Historical and predicted referral impact margin 

• Plus a discount factor to bring past and future value of money to a present value 

Interview with the Customer Value Guy

Tom: Hey Mike, good to see you. Can you tell the readers a bit about yourself? 

Mike: I'm the customer value guy. I've worked for some pretty big hitters like News UK and HSBC, along with a lot of other smaller businesses, startups, scale-ups, and even the smallest, which was a mobile MRI van. 

Tom: Let's start with a definition of CLV. 

Mike:  It's a forecast of a customer's net present contribution over a set time frame - it's how much a customer might be worth when considering the value of cash now and in the future. It’s based on profit, you're adjusting that for the time value of money and then you're also subtracting associated costs, including customer acquisition costs, service costs etc. 

Tom: So, can you explain why CLV is so important?

Mike: Basically, it's important because it allows stakeholders to make informed decisions; it provides insights for both present decisions and future decisions. It is used for really big things like understanding the cost and return of strategic investments or smaller things like estimating profits from an upsell program.   

Tom:  One of the VPs at Forester told me that 80% of brands that they spoke to aren't calculating CLV correctly. What are the common mistakes you see? 

Mike: Two main categories of problems; calculating it and using it. One main mistake I can't stand is using revenue instead of contribution margin. There are loads of reasons for this, but when you only look at revenue, it's basically obscuring the true cost to create that revenue, its only one side of the equation.  

Tom: Can you give an example? 

Mike: Earlier this year, I had a client who had never looked at lifetime value before. They had always looked at return on investment based on revenue less CAC, and it was a positive return on investment. When you drill that down into contribution margin and consider their churn rates, it was a negative lifetime value.

Learn more about the Customer Value Guy here. 

✅ The Retention Blueprint Checklist of CLV Mistakes to Avoid 

• Simply looking backwards. CLV is a past and future value of existing customers. 

• Using churned customers to calculate average tenure: Existing customers will always have longer tenure than those who have churned. 

• Using average retention rates/churn rates and pushing those out across the base. This results in average retention rates being influenced by new customers with short tenure, which often masks a pattern of increasing retention rates, which becomes apparent if analysing cohorts over time.  

• Assuming all customers acquired will have the same inherent value and retention profile. Your oldest active customers have the closest fit to your product/service offer and wont have the same profile as newer customers.

• Failure to include anything but financial data. Referrals, in particular, can add a lot of value to CLV and change the way you manage some cohorts. 

• Assuming that once calculated, CLV is a fixed number. It should be refreshed at least quarterly. 

• Using revenue, not profit. (Mikes favourite)

Until next week, 

Tom 

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Every month we lose customers it feels like we're taking two steps back.

Recurring revenue businesses depend on a steady customer base; high churn threatens the stability and predictability of revenue, causing intense pressure to recover constantly. If this your business, get in touch to discuss consulting and my fast-track retention accelerator.