# Innovation – LTV Metrics

## Many times when you are browsing startup literature you will see the term LTV (Lifetime Value), reflecting the long-term value a customer brings in relation to the cost to acquire that user. But LTV is a difficult metric to both understand and calculate, which is why we wanted to dive into the details of LTV as a means to structure a proper customer acquisition strategy.

*The below post is a very simplistic, illustrative example of how the topic works conceptually.* *It is meant for educational purposes and is not specific to any business or brand in-particular*.

Do a quick Google search of ‘LTV Lifetime Value’ and you will see several different results coming up. Why?

LTV is highly dependent on the type of business. In the last decade, we have seen the rise of many SAAS (Software-as-a-Service) and Subscription-based businesses, for whom the calculation would be distinct from those of businesses that don’t have a recurring revenue model.

In this post we will look at data from Farfetch based on Theta Equity Partner’s proprietary modelling of non-contractual based businesses:

# Farfetch Example – LTV in Action

Before looking at the mathematical dimension of LTV, we will talk about the philosophical and strategic dimensions of why it is so important to understand LTV for any type of business. Using an example from the Farfetch Business Model Canvas, we can see that this innovative, publicly-listed (Ticker: FTCH) fashion company uses LTV as its core metric, rather than bottom-line profitability.

Theta puts LTV and related calculations at the heart of their corporate valuations. Their model of ‘**Customer-Based Corporate Valuation**‘ gets to the heart of this concept, where a business’s valuation goes beyond basic P&L (Profit and Loss) calculations for a certain period of time (ie. one quarter). Instead, you need to look a layer deeper at metrics such as retention, margin, and any metrics that reflect behaviors.

Keeping in mind that Farfetch is a public company (creating many more data points for analysis), Theta’s analysis of the Farfetch IPO zones in on the LTV calculations.

In the above quote, you can see the logic they apply in relation to the graph. Looking at 2017 data, you can see that **more than half of Farfetch’s customers (55.6%) were Existing Customers**. This fact becomes extremely important when looking at the* Customer Acquisition Cost *(**CAC**) because without this long-term context surrounding customer behavior you would be unable to assess the strength of the business model. Whereas* Average Revenue per User* (**ARPU**) is generally reflective of revenue over a quarter (or year), LTV captures behavior over the ‘lifetime’ of a customer. Defining *lifetime *itself is another calculation, but let’s look at Theta’s conclusions from Farfetch data:

Now you can see, as the pieces come together, how the LTV* can be used to inform strategy. The $100 CAC can be expected to deliver a 400-900% return, net, because of their retention metrics. From purely a strategy standpoint (not an investment standpoint), one could support the use of funds to **expand their marketing efforts** and continue trying to acquire customers. On the contrary, if you didn’t have a significant expectation of ROI on marketing spend for new customers and strong retention metrics, then it would be better to focus on how to make the customers you currently have become more profitable.

**Customer Lifetime Value (CLV) is interchangeable with LTV*

# The Mathematics – LTV Equation

If you Google ‘LTV Formula’ you will see many different statistical formulas that are mostly adapted to **subscription-based businesses. **In the case of Theta’s models, they use WACC (weighted average capital cost) and NPV (net present value) in their calculations to assess cashflow dynamics and other methods of financial performance. For the purposes of this post, we are going to try and simplify the math into a *basic formula *to illustrate the mechanics of how LTV is calculated. These basic calculations can produce metrics and data that are **useful in assessing strategy** but are not fully-verified for accounting or finance purposes.

If you look at the full post in the analysis of Farfetch’s valuation, you will notice a couple key elements:

They determine, through their own extensive analysis, that CLV net of CAC is $400 – $900 in NPV terms. *Net of CAC, *in this case, implies that they take LTV ($500 – $1,000) and subtract out CAC ($100). Their CLV calculation takes in very sophisticated data capture on Retention, something that would be impossible to represent *simplistically *in a formula; yet is still relevant for illustrative purposes in this post, so we will use 1/Churn (explained below).

Then we see how Farfetch themselves disclose their LTV/CAC over time. This visual representation of *why* LTV is so important speaks to the fact that loyalty, while difficult to calculate, pays tremendous dividends over the long term.

CLV, for the purposes of this post, is effectively LTV/CAC. Retention Period, as a metric of loyalty, *can be estimated *using the 1/Churn formula, even for non-subscription businesses. Let’s say you acquire 100 Customers in a year and lose 20. Applying this formula, an average customer could generate revenues for** 5 years*** (1/0.2 = 5).

**Note*: *this is a very simplistic, illustrative example of how this works conceptually. To do a proper estimate of Churn requires an advanced statistical model like we see with Theta Equity (or Farfetch’s own calculations) that factors in decay. Simply put, it is obvious that a certain % of the remaining 80 customers* *will themselves churn in Year 2, Year 3*, *and beyond. The relationship, will be non-linear, however (ie. the number will not be 20% per year), as we see in the bands for Farfetch’s Cohorts YoY (year over year). *

Both ARPU and CAC (as will be described below), can be pulled from financial data. When factoring in an accurately calculated Churn over time,** the benchmark of a good CLV (LTV/CAC) is 3X or 300%**.

Let’s break down some of the terms around CLV in order to be able to determine how to use the formula for any type of business:

**>ARPU (Average Revenue Per User): **how much revenue is generated per user over a period of time? *typically per quarter or per year depending on the business*

**>Retention Period: **what percentage of new customers are retained over X period of time? * When you divide the Churn Rate by 1 (ie. 1/Churn), you get the average # of periods you expect a customer to be retained, in aggregate. *

**>CAC (Customer Acquisition Cost): **how much is spent across all categories to acquire a customer? *This includes direct marketing spend, indirect marketing spend (ie. referrals), and staff marketing salaries. Can be captured under the moniker of ‘demand generation expenses.’*

# YOURBIZ Example and Strategy Implications

**This example is illustrative only in order to show conceptually how the concepts come together. To get accurate estimates of LTV/CLV requires more advanced statistical models. **

**>**The Average Customer will spend **$100 per year** at YOURBIZ. This number can be calculated using either **ARPU** or **APV** (Average Purchase Value), but it must be defined within a certain time range (ie. per year or quarter).

>YOURBIZ has a large referral funnel, which helps to keep a high retention rate of 60%. This means that the Churn is 40%. **(1/40%) = 2.5 years**

>YOURBIZ is in a competitive market, so even though it has a large referral funnel for *demand generation*, it still spends a lot on marketing. **CAC = $75**

>** [$100 **(ARPU)** * 2.5 years **(1/0.4 Churn)**] / $75 **(CAC) = **3.33 **(CLV)

The CLV comes out to **3.33X (or 333%)**. Using **3X (300%) as the benchmark (3X value returned in revenue on money spent on CAC)**, we would say that this a good ROI and shows positive unit economics for the business. The additional granularity versus simply calculating *the margin* becomes obvious and shows that the value being derived per customer is strong when both retention rates and demand-generation expenses are considered.

This formula is just a basic way to present the LTV/CLV concept. The Farfetch example above using Theta Equity’s calculation was designed to show how important it was to get deeper into an understanding of consumer behavior.

Theta’s analysis incorporated WACC and NPV to give further insights into the business from a finance perspective for potential investors. But for now, we will leave the LTV/CLV calculations there, as they are enough to begin forming basic strategic insights from. Naturally, different types of businesses have different factors that drive their success. But certain formulas like LTV/CLV help to structure customer data into models that can be used both internally and externally to assess strategy, marketing ROI and other important metrics.