Financial Planning & Analysis

5 Keys for Your Customer Lifetime Value Model

As more companies move from single-transaction to recurring-revenue relationships with customers, estimating and tracking customer lifetime value (CLV) with care is critical for every business model. While CLV is not an exact fit within annual income statements, it is a useful financial modeling tactic for marketing ROI and potentially valuation. We believe there are 5 key considerations when building a customer lifetime value model for a business.

Installed Base / Adoption as a Key Revenue / Cash Flow Driver

Penetration of the addressable market should be captured to quantify the number of expected customers/users. This could come through as one or a combination of drivers such as:

  1. Market Share Gains – gradually increasing proportion of the existing specific market, such as share of wallet for mobile soccer game revenue or percentage of units of robot vacuums
  2. Adoption Rates – for fairly new products/solutions where an existing market is not yet present, an increasing percentage of the population (e.g., select demographics) or companies (e.g., small/mid-size corporations) can be utilized
  3. Installed Base / Attach Rates – for products/solutions that are similar to razorblade business models with associated consumable or follow on purchases, assumptions on building a cumulative installed base and assumed attachment rates can be used to drive revenue estimates.

Pricing / Revenue Per User Trend

Once the customers/users have been quantified, pricing or revenue per user assumptions should be identified. This factor should mostly match up with the customer/user driver even though other streams (e.g., advertising revenue) may apply. Examples include:

  1. Monthly/Average Revenue Per User (ARPU) – useful for subscription businesses that collect monthly membership fees from users. Different assumptions for different tiers be used as much as possible. For out years, increases or decreases in prices for each tier should be considered.
  2. Average Sales Price – useful for hardware businesses where unit volumes are being sold. This assumption should reflect revenue net of channel margins and discounts if applicable. Similar to user tiers, different product lines should be reflected, and hardware price erosion (even for successor models) should be considered.

Churn / Useful Life

For active-user-related business models, attrition of the user base is a key forward-looking assumption. Great care should be taken with these drivers as they can swing estimates both up and down with just a minor swing.

  1. Monthly Churn – percentage of cumulative users that are no longer active in the current month. In wireless telecom businesses for example, about 2-4% of the total subscriber base stops being active every month which could similarly apply to certain mobile applications
  2. Useful Life – use of the initial component that drives follow-on purchases ceases at some point. For printers for example, this could be range 2-10 years depending on the hardware type. For mobile applications this could be a much shorter 90 days or less before a user is deemed to be non-active based on specific criteria (e.g., minutes of use, etc.).


In addition to costs of goods sold (if applicable), cost to serve and cost to acquire/install should be reflected as completely as possible. Some examples of the latter can include the following:

  1. Network/Data Costs – estimated cost to provide a service or solution, which can include data/bandwidth costs, storage costs, development costs, etc.
  2. Sales and Marketing Costs – estimated costs to obtain customers/users, such as advertising costs, sales team compensation, etc.
  3. Other Costs to Acquire – in razorblade or freemium business models, this can translate into the net loss of the initial component sold or free software provided to the customer that will generate consumables/add-ons in the future

Create Scenarios

Since there will always be variance in assumptions to estimates made, ranges of confidence should be created. At least 3 should be created at least modifying key drivers such as users, churn, and pricing such as:

  1. Conservative – considers a situation where there is a challenging macroeconomic environment and competitive landscape which impact sales volumes and pricing.
  2. Base – reflects the steady state that the business expects if economic and competitive environments are stable.
  3. Aggressive – should correspond to a beneficial situation where macroeconomic factors are very beneficial, and the competitive position of the business is strong such that sales volumes are strong and/or pricing is at the high end of the expected range.

Using CLV in Practice

Factors #1 – #3 can be used for a simple customer lifetime value such as:

CLV = Monthly ARPU / Churn Rate

For example, a business that generates $30 of monthly ARPU with a 5% churn rate would have a customer lifetime value of $600. As stated in #3, changing the churn rate would move the CLV a lot.

This could then be compared to the customer acquisition cost (CAC), which is calculated by:

CAC = (Sales & Marketing Costs + Other Indirect Customer Acquisition Expense) / Number of Customers Acquired

In a case where 1 million customers were acquired via sales & marketing costs of $500 million, the CAC is $500. This compares favorably to the CLV.

Incorporating more of factor #4 and #5 (scenarios), a long-term financial model can be built. In addition to the above 5 factors, other considerations such as time value, operational (retention) & overhead costs, seasonality, etc. may apply.

Again, CLV is not a GAAP measure, but it helps to add a longer-term perspective to short-term budgets/forecasts that have a near-term focus. The long-term estimations can also be used for a discounted free cash flow (DCF) business valuations.

Looking for More?

For more information on financial modeling best practices or improving your financial forecasting process, you can download our free resource below:

financial forecasting process guide

You can also contact 8020 Consulting to speak to us directly and explore how we can help your finance and accounting function.

About the Author

Marco has 17 years of Finance and Consulting experience. His work spans various industries including technology, entertainment, telecommunications, consumer products, financial services, and healthcare. Marco has expertise in Financial Planning & Analysis (budgeting, forecasting, and reporting), Strategic Planning, project management, financial modeling, merger integration, and valuation. Prior to joining 8020 Consulting, Marco held Finance and Strategy positions at Epson America and also worked for various firms including Deloitte Consulting, Paramount Pictures, Grupo Modelo, Cricket Communications, UBS, and Goldman Sachs. Marco holds a B.A. in Economics from Brandeis University, and an MBA from the UCLA Anderson School of Management.

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