Geoff Fripp

Great Article on CLV for Mobil Apps

 profitability  Comments Off on Great Article on CLV for Mobil Apps
Feb 202017

evus TECHNOLOGIES has a great article on various ways of measuring and tracking the performance of a mobile app. They review 50 different KPIs (key performance indicators) that are relevant to mobile app metrics, including a look at customer lifetime value, retention rate, and customer acquisition cost.

So if you have a special interest in CLV for your mobile app – then check out their article Top 50 KPIs for Mobile Apps.

Here is a short excerpt from the opening of their article, to give you a sense of why it’s an important read…

Understanding the various mobile KPIs (key performance indicators) and how they apply to your business should be the first steps you take when developing a plan for marketing, promoting, and ensuring the success of your app.

Regular reporting and analysis of mobile app marketing KPIs and how your app is progressing helps you improve upon its performance and therefore generate more revenue.

It helps you place a valuation on your app and therefore attract the attention and resources of buyers, investors, and shareholders.

Defining unique KPIs means determining what a good performance looks like and how to capture and measure the various indicators along the journey.

But of course, there are nearly as many mobile app metrics as there are apps, so understanding what it all means is perhaps the first step in the process.

Customer retention rate should increase over time

 formula, retention  Comments Off on Customer retention rate should increase over time
Jul 232016

One of the major impacts on overall customer lifetime value (CLV) is the firm’s ability to retain customers. An increased loyalty rate can substantially increase the average lifetime period of the customer, resulting in a significant increase in customer lifetime value.

However, it is unlikely that any cohort of customers will have a static retention rate. It is likely that retention will increase over time. You should note that the free template provided on this website to calculate customer lifetime value, allows you to modify the retention rate each year.

Obviously, for most firms/brands there is a natural goal to increase retention rate – but this will happen automatically in most cohorts of customers.

Example of increasing retention rate

Let’s assume we have acquired 100 customers in a particular year. Upon their first/early experiences with the firm/brand, they will go through some “customer satisfaction” (post purchase) evaluation. As you probably know, this is aligned to their expectations prior to purchase.

natural customer retention rate over timeLet’s assume that 25% of these new 100 customers are relatively dissatisfied with their purchase, with the remaining 75% relatively satisfied with their purchase.

You would probably guess that many of the 25% dissatisfied customers are unlikely to continue as customers into the second year – and you can probably also guess that a significant proportion of the 75% satisfied customers will remain loyal to the firm/brand.

If we enter the second year, say with a 60% retention rate – with all of these retained customers being part of the original satisfied group – therefore we held 60/75 of these satisfied customers and we lost all 25 dissatisfied customers.

Therefore, as we enter year three, we only have generally satisfied customers. While we had a 40% churn/loss rate in the first year – due to a proportion of new acquired customers being dissatisfied – they have left the firm/brand – and will not impact the retention rate of this customer cohort into year three.

This will mean that we are likely to see a significant jump in retention rate for this customer cohort – perhaps up to 80%. This process likely to continue, with the quite satisfied customers continuing and the less satisfied customers being more likely to drop off. Over time, the firm/brand should be left with a small, but loyal and quite satisfied, customer base – where retention keeps increasing.

Customer lifetime value – does the average lifetime period make sense?

 formula  Comments Off on Customer lifetime value – does the average lifetime period make sense?
Jul 232016

Perhaps one of the confusing aspects of calculating customer lifetime value (CLV) is working out the average period that a customer purchases from the firm/brand. Sometimes it seems inconsistent with the percentage of customers retained.

In this article, we will work through why this sometimes seems to be an inconsistency. For this example we will use an 80% retention rate. As we know, as this equates to a 20% churn rate, which is 1/5 as a fraction, making the average lifetime period for customers five years.

However, if we keep decreasing our customer base by 20% (the churn rate) each year, then at the end of the five years we only have around a third of the starting customers – so how can five years be the average period?

Let’s assume we start with 100 customers that are acquired in a particular year and our goal is to track this cohort’s customer lifetime value. With an 80% retention:

  • 80 of them will continue into year two,
  • 64 into year three,
  • 51 into year four,
  • 41 into year five, and
  • by year six there are only 33 of the original 100 customers.

Therefore, the question is given we have only around one third of customers continuing past year five, how can the average lifetime period of this customer cohort be five years?

clv customer contributionIf we use the chart provided here – please note that the lines are mapped onto two different axes – you can see that the red line maps our 100 original customers on a progressively decreasing basis. And by year six there are around one third of the original customers still active with the firm/brand.

The blue line needs some slight explanation. The blue line represents the number of customers who leave in a particular year, multiplied by the number of years that they are a customer. For example, in year one we lose 20% of the 100 customers – and therefore 20 customers – they were only customers for one year.

However, in the second year we lose 20% of the remaining 80 customers – which is 16 customers. But as they were customers for two years, they were equivalent to 32 “single year only” customers. In year three, we lose a further 20% of the remaining 64 customers – which is about 13 customers – as they were customers for three years, they are equivalent to 39 “single year only” customers.

Therefore, the blue line maps the contribution – in terms of customer years – of the customers that are lost in that particular time period. As you can see, the blue line peaks around years four and five, indicating that the average of customers will be dragged towards  four or five years’ worth of value (as opposed to a single year only customer).

The other factor to consider is the long tail of the red line. As you can see, it is somewhat flattening out, meaning that they customers remaining are relatively loyal, and are likely to be long-term customers. For example, in year seven, we only lose 5% of our original 100 customers. These five customers, have been dealing with the firm/brand for seven years. As you can see, we still have 15 to 20% of customers dealing with us up until you 10 – and beyond – which has the impact of extending the average lifetime period (essentially as a weighted average) to five years.

Related topics

Main customer lifetime value formula

Using the retention rate to calculate average lifetime period

 formula  Comments Off on Using the retention rate to calculate average lifetime period
Jul 232016

When calculating customer lifetime value (CLV), one of the key inputs is the number of years that the average customer will purchase from the firm. This is surprisingly easy to calculate if you know the loyalty/retention rate of customers.

The formula for average lifetime period of customers is simply 1/(1-retention rate).

You should know that the opposite to the retention (or loyalty) rate is called the churn rate – which is the percentage of customers that are lost in the time period.

For example, an 80% loyalty/retention rate means that 20% of customers are lost (churned). And a 60% loyalty/retention rate means that 40% of customers are lost/churned. In all cases, the retention and the churn rate should add up to 100% to account for all the customers.

If we relook at the above formula for average lifetime period, then it could be further simplified as 1/churn rate. And if we convert the churn rate to a simple fraction, then we can quickly work out the average lifetime period as follows:

20% churn rate = 1/5 = average lifetime period = 5 years

33% churn rate = 1/3 = average lifetime period = 3 years

50% churn rate = ½ = average lifetime period = 2 years

Hopefully what you should notice, is when we convert the churn rate to a simple fraction – where we have 1 as the numerator (top number), we can simply take the bottom number (the denominator) as the number of years.

This occurs because, as we divide the fraction into one, the calculation has the impact of inverting the fraction.

Therefore, if you remember your approach to dividing fractions, you should be able to work out the average lifetime period for any fraction – by inverting the fraction. And you may recall from mathematics, that to divide a fraction you turn it over and multiply it. Because we are dividing into one, we end up multiplying by one – so all we have to do is invert the fraction.

For example, if we have a 30% churn rate, as a fraction that is 3/10. When we invert that we get 10/3 – which is equivalent to 3.33 years.

Likewise, if we have a 40% churn rate, that is equivalent to 2/5 – we then invert it and get 5/2, which is equal to 2.5 years.

Existing Customer CLV Formula

 formula  Comments Off on Existing Customer CLV Formula
Jun 182016

A fairly standard CLV formula that you will find for measuring the lifetime value of existing customers is:

CLV = m.r/1+d-r

  • Where m = customer margin (or profit contribution) per year
  • Where d = discount rate
  • And r = retention/loyalty rate per year

Important note: This formula is designed to measure the customer lifetime value of EXISTING customers only. You should also note that there is NO use of an acquisition cost, as existing customers have already been acquired and that expense is now historical (or a sunken cost).

How this CLV formula for existing customers works

To make sense of what this formula is doing, let’s first look at the bottom line of 1+d-r, but remove the discount rate (d) and we are now left with 1-r.

We should know that 1 minus the retention rate is churn (or customer loss) rate. When we use the churn rate at the bottom (denominator) of the fraction/equation, we are actually calculating the lifetime period of a customer in years.

  • For example, a 60% loyalty rate = 40% churn/loss = 1/0.4 = 2.5 years, and
  • An 80% loyalty rate = 20% churn/loss = 1/0.2 = 5 years

Now let’s look at the impact of the retention rate at the top of the equation. At the top of this CLV formula (numerator) there is m times r. This has the immediate impact of reducing the margin (profit) to the likely margin be be achieved in the FOLLOWING year.

This occurs because the formula is looking at an existing customer (already acquired) and estimating their FUTURE value – not their total value over the course of their customer relationship.

comparing clv formulas

Click CLV table to enlarge

To make sense of this difference, let’s compare a new customer’s CLV to an existing customer.

The new customer is shown on the left hand side. As you can see, their acquisition cost was $500 in Year 0, their margin was $300 in Year 1, which then reduces by 60% each year in line with estimated retention rates.

After the 10% discount rate, their CLV (shown as DCF = discounted cash flow) is $160.

On the right hand side of the table, the CLV figures are shown for an existing customer using the above formula.

As you can see, there is NO acquisition cost (as they are already a customer), and we essentially start the customer in Year 2 with a annual margin of $180 (which is 60% of Year One’s $300 – note the two highlighted yellow cells).

In this case, the customer value (after discounting) is $360. This is also what the above formula tells us:

  • CLV = m.r/1+d-r = (300 X 60%)/(1+.1-.6) = 180/0.5 = $360

Limitations of this CLV formula

The main concern with this approach to calculating customer lifetime value is its use of static values. Firstly, it assumes a stable margin (annual customer profit), which is generally unlikely (please see article on increasing customer revenues). And secondly, it also assumes a stable loyalty rate over time, which again is generally unlikely.

That’s why the free CLV Excel template available on this website allows for flexible revenues, costs and margins over time.

So why use this CLV formula?

CLV = m.r/1+d-r is appropriate as a simple estimation of future customer value. It can be easily applied to a customer database (say in a spreadsheet format) where the customer’s profit/margin for the year is listed, along with an estimated loyalty/retention rate.

This CLV value becomes a forward-looking metric that a marketer can use to determine the financial viability of various cross-selling and loyalty focused marketing tactics.

Related Topics

CLV: New versus existing customers

Customer Lifetime Value: Existing versus new customers

 formula  Comments Off on Customer Lifetime Value: Existing versus new customers
Jun 182016

Are you measuring the CLV of existing or new customers?

Customer lifetime value calculations, and the most suitable CLV formula to use, will vary depending upon what type of customer that you are attempting to measure. To make this point quite simply, there are two main types of customers that we are seeking to measure for customer lifetime value purposes, which are:

  1. Existing (current) customers, or
  2. Potential (new) customers (which will also include reacquiring lost or lapsed customers).

Key CLV formula differences between existing and potential customers

There is a significant different in the CLV calculation for these two categories of customers. The most significant difference is in regards to the treatment of the acquisition cost. Obviously, existing customers have already been acquired – hence their acquisition cost is essentially a sunken cost that we would not take into account. Whereas new/potential customers still need to be acquired and will incur an acquisition cost.

The second difference is that the loyalty (retention) rate of existing customers is likely to differ between existing and new customers. To make sense of this retention rate difference, let’s consider this graph of customer loyalty over time.

loyalty rate over timeThe first arrow on the left shows the loyalty rate for (new) customers after the first year of just 60%, whereas the arrow on the right shows the loyalty rate of existing customer (in years 7-8) approaching 80%.

So why does this happen? When you think about it, the loyalty rate pattern makes logical sense.

At the start (year 1), new customers are essentially trialing the brand’s/firm’s offering. If they are dissatisfied (or a consumer more prone to switching), then they are more likely to churn (switch or lapse) early in their brand relationship. However, if they are satisfied with their initial purchase and remain loyal after the first year, it is likely that the loyalty rate of the remaining customers will increase over time (as the less satisfied customers decide to discontinue or switch brands).

Example of different CLV calculations: New versus existing customers

To make the customer lifetime value calculation as simple as possible, let’s assume:

  • The acquisition cost of new customers is $1,000
  • The customer profit (revenues less appropriate costs) is $500 per year
  • The loyalty rate of new customers is 60% (as per the above table, which = 2.5 years)
  • And the retention rate of existing customers is 80% (say for year 9 in the table above, which = 5 years)

Therefore, the customer lifetime value of NEW customers would be:

  • $500 X 2.5 years, less $1,000 = $250

And the CLV of EXISTING customers would be:

  • $500 X 5 years = $2,500
What do these CLV results mean?

As you can see, the customer lifetime value for existing customers is 10 times the value for new customers. However, this is to be expected. Due to the loyalty rate pattern for this example (60% increasing to 80%+ retention), there is only a small number of existing customers after ten years.

percentage of customers over timeLet’s now look at the percentage of customers that actually remain loyal for ten years (even with a retention rate of 60-80%). As you can see in the graph, only around 5% of customers are still with the firm/brand at the ten year mark.

These customers are highly loyal (most probably due to choice, rather than habit at this stage) and therefore should be quite profitable ongoing.

And compared to the less loyal newer customer, their CLV figure will be naturally higher. But keep in mind that within every cohort of new customers there will be very short-term low value customers, as well as a small number of long-term high value customers.

Impact on new versus existing customer acquisition strategy

Based on the differing CLV’s of new versus existing customers, there is possibly a suggestion that the best strategy would be to focus on existing customer only. But you are probably aware of the leaky bucket theory – which suggests that even with high retention rates there will always be a drain on customer numbers (as illustrated in the previous chart).

Therefore, the clear strategy should be to continue with new customer acquisition, with the intent of identifying (or creating) the long-term, high value customer than underpins the ongoing profitability of the firm or brand.

Reconciling Customer Lifetime Value with Total Profits

 profitability  Comments Off on Reconciling Customer Lifetime Value with Total Profits
Feb 112016

The accounting challenge of customer lifetime value

One of the key challenges with communicating the benefits of customer lifetime value (CLV) as a key marketing metric is its alignment (or perceived lack of) with the firm’s overall profitability.

Take for example, a marketer who has determined that the firm’s CLV is $300 (before taking into account the initial $200 acquisition cost) and the marketer has also worked out that the average customer retention rate is 75% (or four years on average). The marketer could then argue that an acquisition cost of $200 per new customer (leaving a net CLV of $100) would be quite acceptable and would actually deliver a good marketing ROI of 50% ($100 profit/$200 acquisition cost – not including a discount rate).

Enter the accountant: who then points out that the firm made $2 million last year and that the firm has a customer base of around 40,000 customers – which clearly shows that each customer only makes $50 per year for the firm ($2m/40,000). Therefore, according to the accountant it doesn’t make sense to acquire customers at a $200 each – when they only make $50 per year and last only four years – “the firm would be lucky to break-even doing that“.

This would not be an uncommon situation for a marketer – so how do we reconcile the $100 customer lifetime value with the average $50 profitability quoted by the finance expert? Let’s have a look in the next section.

Aligning CLV to Overall Profitability

The problem with the above discussion is that the position is confused by the firm’s fixed costs and the overall acquisition (marketing/promotion) budget. So let’s reconcile customer lifetime value and the accounts.

  • The firm made a profit of $2 million last year
  • The firm had fixed costs of $800,000
  • And they had a marketing/acquisition budget of $200,000
  • Therefore, their profit BEFORE fixed costs and new customer acquisition costs was $3 million

So what does this $3 million profit represent? This is the profit generated by the current/existing customer base for the year. We have removed the fixed cost component and we have removed the investment in new customers. Therefore, this is the key financial number to get to = which is profit contribution of the existing customer base. So now we can continue our accounting and CLV connection.

  • The profit contribution of the existing customer base was $3 million
  • The firm has a 40,000 customer base
  • This means that each customer contributed $75 in profits (on average)
  • The average customer lifetime is 4 years
  • $75 (per customer profit) X 4 years = $300

Yes, we are back to the $300 customer lifetime value amount quoted by the marketer initially. So the marketer is right, the firm can spend $200 on customer acquisition, as they will make $300 back – every new customer is worth a net $100 to the firm.

An approximate customer lifetime value metric

Given this reconciliation of profits and CLV above, we should be able to work backwards as well and construct a ball park estimate of customer lifetime value using the firm’s top level financials (although I would suggest that you use the Excel template on this site to ensure greater accuracy).

As an example of this approximate CLV metric:

  • A firm made $10 million in profits
  • Add back their fixed costs, say $4m = $14 million
  • Add back their marketing budget, say $1m = $15 million (profit from existing customers)
  • Divide by their customer base, say 100,000 = $150 (profit per customer)
  • Multiply by average customer lifetime, say 5 years = $750 (CLV before any acquisition costs)

This is possible metric that you could use to:

  1. Verify/ball park check your own CLV calculations
  2. Set targets for improving CLV – e.g. if profits are to increase by $1m, what does CLV need to get to?
  3. Estimate competitor customer lifetime values

Help in setting CLV targets for increasing profitability

If you look at the 2nd way you could use the CLV “appropriate” metric above, you can see it can be used for setting a customer lifetime value goal/target. Let’s continue with the above example and figures to see how that would work.

  • Firm’s profit of $10m, with a goal of increasing to $11m
  • Without any other major changes, this would mean that the profit contribution from the customer base would need to increase from $15m to $16m
  • If the customer base remains at 100,000 – then profit per customer per year needs to go from $150 to $160
  • With the 5 year average lifetime, total CLV (before acquisition costs) needs to increase from $750 to $800 (assuming acquisition costs per customer remain the same)

As you can see – the $10 increase in profit ($150 to $160) X 100,000 customers = $1 million profit increase. But that’s just a guide – our task, as the marketer, is to increase CLV from $750 to $800, and that increase could be achieved by:

  • Increased revenue per customer
  • Decreased costs of supplying/servicing the customer
  • Decreasing retention costs per customer
  • Increasing loyalty (lifetime) per customer
  • Decreasing the acquisition cost (more customers/same spend)

And, of course, we could grow the customer base instead – but the purpose of this article is to discuss CLV considerations.

Calculating Customer Lifetime Value for Banks

 banking  Comments Off on Calculating Customer Lifetime Value for Banks
Nov 192015

How to calculate customer lifetime value (CLV) for a bank

Having had a corporate background in banking, I found that customer lifetime value was a key marketing metric in the finance sector. This is because banks (and other financial institutions) will hold customers for a long period of time and the customers will go through phases of their relationship – ranging from highly profitable to minor (or even negative) profitability.

Banks tend to focus a considerable amount of their marketing efforts on trying to build more profitable relationships with existing customers. Essentially direct marketing and relationship marketing efforts are used to:

  1. Retain the loyalty of the customer (greater customer lifetime in years)
  2. Increase the value/profitability of the customer (through up-selling and migration to higher value products).

The ROI on the investment in the various direct and relationship marketing efforts can be measured quite effectively using a customer lifetime calculation. To assist in this CLV calculation for a bank, a free customer lifetime value Excel template has been provided on this site.

You can download the free CLV banking Excel template here… free-clv-template-download-for-banks

The customer lifetime value calculation for banking

Customer lifetime value is calculated primarily the same way for a bank as it is for the main CLV calculation. Please refer to additional information on this website as required – please navigate by the above menu.

The key inputs into the customer lifetime value (CLV) banking calculation include:

  • Average balances of loans and savings on a per customer basis
  • Average interest rate margin (as a percentage)
  • Average income/revenue per customer generated from non-interest income sources (e.g. fees, commissions, and other sales)
  • Costs of providing customer services and access (which would include transaction costs, statement costs, and potentially a provision for infrastructure costs, and so on)

These inputs are used together to determine average annual profit on a per customer basis. This information is then combined with customer retention rates, other costs of retention and up selling, as well as initial customer acquisition costs – to determine the customer lifetime value (CLV) for the bank.

This is all calculated automatically for you in the Excel template for customer lifetime value for banks – which is available above for free download.

How average interest margin is used in the calculation

The customer lifetime value formula has been discussed elsewhere on this website, and probably the most significant difference for the banking customer lifetime value calculation is the handling of the interest rate margin in the determination of CLV.

If you look closely at the free Excel template of the CLV banking calculation, you will note that the profit generated from the average balance multiplied by the interest rate margin is then divided by two. Why is this necessary?

It is necessary to ensure that profits are not double counted in the calculation of customer lifetime value (CLV). As we know, banking involves the matching of depositors and borrowers – so let’s look at the following simple example.

Simple CLV Banking Example

Let’s assume we have just two banking customers (in order to make the calculation straightforward). The first customer has $10,000 in a savings account at 6% pa interest and the second customer has a loan for $10,000 at 10% pa interest.

In simple terms, our net interest margin is 4% (10% less 6%). Assuming interest only repayments, the bank would generate $1,000 in interest revenue from the borrower and then pay $600 in interest expense to the depositor. This is a $400 per annum profit for the bank, which is equivalent to our 4% net interest rate margin.

However, because there are two customers involved, this $400 profit amount needs to be divided by the two customers. This means that each customer helps generate $200 in profitability.

Therefore, this is why the interest income is divided by two in the customer lifetime value calculation.

Totaling Savings and Loan Balances

Because of the manner in which the spreadsheet handles the CLV calculation for a bank, it is then a simple manner to take the bank’s total loans and total deposits and add them together to determine the total combined portfolio. This total portfolio can then be divided by the total number of customers to calculate average balance, as shown in the following example.

  • Bank’s total loans = $400m
  • Banks’s total deposits = $600m
  • Added together = $1b total portfolio
  • Bank’s customer base = 50,000 customers
  • Can then calculate average balance $1b/50,000 (total portfolio/number of customers) = $20,000 average balance per customer

This simple approach ensures that all balances from all customers are included. For example, say a customer had $1,000 in savings and a $1,000 loan – then this approach would count $2,000 in their average balance – say at a 4% net interest margin (see above), then divided by two = $2,000 X 4% / 2 = $40 per year profit contribution.

Determining Net Interest Rate Margin

This is normally a key financial metric for a bank so it should be easy to find, but a simple way to calculate it is:

  • Net interest income/average total assets for the year


Mar 202015

Return on marketing investment: A Case Study of the Domestic Airline Industry in India (research paper)

This is an excellent research paper, ideal for anyone seeking a more detailed understanding of customer equity and customer lifetime value. The paper also provides good insight into the airline industry in India, as one of the co-authors is employed in the industry.

The paper constructs a framework for the integration of marketing strategy with customer lifetime value and customer equity within the airline industry. It has a significant return on marketing investment focus.

For a better understanding of the case study, here two paragraphs from the abstract of the research paper.

The authors present a practical model that can be of help to airline managers to trade off competing marketing initiatives and make them accountable. The model enables airlines to calculate ROI for any prospective marketing investment and to evaluate the realized ROI. The framework is based on the effect of marketing initiatives on firm’s customer equity, which is the sum of lifetime values of airline’s current and future customers. Each customer’s lifetime value results from the frequency of flying, average price of ticket, and brand switching pattern, combined with the firm’s contribution margin.

The drivers of customer equity include value (quality, price, convenience), brand (brand image, brand awareness) and relationship (loyalty program, CRM, knowledge of passenger). Airlines may analyze drivers that have the greatest impact, compare performance on those drivers with that of competitors, and project ROI from improvements in those drivers. The framework enables “what-if” evaluation of marketing ROI, which can include such criteria as return on service quality, return on advertising, return on loyalty programs, and even return on corporate citizenship, given a particular shift in customer perceptions. This enables the firm to focus marketing efforts on strategic improvements generating the greatest return.

Return on marketing investment: A Case Study of the Domestic Airline Industry in India by Dr. S C Bansal (Associate Professor at the Indian Institute of Management), Dr. Mohammed Naved Khan (Senior Lecturer Department of Business Administration Faculty of Management Studies & Research Aligarh Muslim University Aligarh) and Dr Vippan Raj Dutt (Manager, System/Maintenance, IT Department at Indian Airlines Limited.

You can download the paper here MROI_Paper_-_Domestic_Airline_Industry_in_India

And you can also download their supporting PowerPoint presentation here IIMA-ROMI_Presentation, which was presented at the “Return on Marketing Investments” conference jointly conducted by the Indian Institute of Management, Ahmedabad and Zyman Institute of Brand Science at Goizueta Business School, Emory University.