August 25, 2015 at 12:16Lifetime customer value - consider LTV
“I saved my hottest hugs, kisses, smiles, respect and deepest admiration for the marketers and analysts who calculate LTV,” exclaims web analytics guru Avinash Koshik. These are not simple emotions - this is the real state of things.
In our country, the first to consider the indicator of LTV (Lifetime Value - lifetime customer value) were mobile operators. Their need was not accidental - against the background of a high level of cellular penetration, the cost of attracting one client became more and more - it was time to get rid of unprofitable sales channels and change the distribution model.
Today, e-commerce is becoming more and more like a cellular operator: mass customer acquisition, serious outflow, numerous channels of lead generation and sales. This look of online commerce has created a new paradigm for calculating work efficiency - from the standpoint of LTV, the total value of the client. There are still few followers of this paradigm, but in vain.
Most internet marketers and analysts use a set of indicators in their work to evaluate the effectiveness of advertising campaigns: failure rate, CTR, number and share of conversions, churn (outflow), cost of attracting a client. These indicators can give a general idea of the effect of marketing activities and the level of customer loyalty, however, from a financial point of view, they make almost no sense if LTV is not considered together with them.
There are a lot of formulas for calculating LifeTime Value and they depend on the purpose of using this indicator.
In order to easily determine the importance of a customer for an online store, it’s enough to use elementary summation over
You can also use the classic calculation formula:
LTV = (Monthly Revenue per Customer * GrossMargin per Customer) / Monthly ChurnRate
ChurnRate = Q / Nt , where
Q is the number of users left at the end of the period
Nt is the total number remaining at the end of the period
To simplify this formula and some comparison of sources can be used
GrossMargin per Customer = (TotalRevenue - Costs) / Nt
In general, you can find many formulas on the Internet and adapt them to a specific customer relationship management structure. Here, for example, is a fairly universal formula that can be found:
LTV = AC × N × P × t ,
where AC is the average check, N is the average number of purchases per month, P is the proportion of profit to the average amount of the check, t is the average life time of the user (how many allocated periods of time he is your buyer - in months, days, years).
There are also formulas tailored to customer churn. An interesting LTV calculation case can be found, for example, in a translated article in a blog .
The manager calculates the average cost of attraction, and then the average value of the client, the remaining groups are distributed on the basis of "below average" and "above average". This method is not the best solution, because It does not give exact values and does not take into account additional factors associated with a specific promotion channel.
which are provided by advertising agencies. You can see, for example, a calculator from Netpeak , which calculates LTV based on the data you entered. In principle, a good option, but it has general restrictions on the values, and also does not take into account industry specifics.
For example, we in RealWeb calculate LTV for each of our clients and, based on the totality of this and other indicators, we build a further advertising strategy.
As you can already see, the simple means of web analytics when solving the problem of assessing the lifetime value of a client is indispensable. Unfortunately, in the general case, Google Analytics does not know how to calculate the LTV indicator, but we will talk about a particular one below. Accordingly, for the calculation of the indicator you will need to carry out some preparation.
Value segmentation is desirable.to understand which channels bring the most valuable customers from each segment. For example, take two buyers of a hardware store. Let each person spend 1,000 rubles each. (let's say AdWords). Client A came and bought a TV for 27,000 rubles. Six months later, he bought speakers for 3,000 rubles. Client B is the head of a software company. Once a week he comes to the store and buys a flash drive, then a cable, then a surge protector, then a cool mouse as a gift to a partner. On average, he spends about 1,200 rubles a week. A year passes. Client A brought 30,000 rubles. He will not return, because he no longer needs new household appliances. Client B brought 1,200 * 52 = 62,400 rubles. And will bring forth. And what do you think, who received the loyalty card immediately, and who - after accumulating a certain amount? Meanwhile
It is necessary to analyze the channels and campaigns that brought average and above average customers in order to allocate funds for incentives.
It is necessary to determine the client’s life time on the basis of experience or available statistics, to establish a unit of measurement for periods (for example, for a restaurant or a grocery store it is both a month and years, and for an online store - days and weeks, although this is not so simple) . In addition, it is necessary to measure the periods of repeated actions (purchases, payments) - so you can split the lifetime into intervals and predict profit or plan advertising activities.
As you already understood, the data for calculating LTV are taken from the outside, so it will be necessaryget data from CRM / ERP / 1C or from the financial (economic) department for further calculation. Here is a sample list of data you might need:
The higher the client’s received value over the period of his life, the more room you have for further actions: developing loyalty programs, opening new channels of attraction, marketing activities and research activities. That is, in fact, you can freely spend money on such customers. If LTV detects a downward trend - this is a dangerous sign, you need to take measures and study the accumulated customer base and focus on sales and complementary sales. It's simple: retaining a customer is cheaper than attracting a new one.
Indeed, the platform provides for the LTV section (in English and in Russian). The report, available only for application representations, calculates the LTV value in the context of attraction channels, based on the life cycle and revenue volume. A comparison of the LTVs of different user groups is also available. The maximum evaluation period is 90 days. This is a fairly small interval, however, it is quite suitable for mobile applications and their dynamics. It cannot be said that this report is ideal, but it gives some idea for further analysis.
In principle, by its logic, it is close to the cohorts that we have already considered in our blog. It is hoped that the tool will evolve and web analytics will have at their disposal a report to count LTV clients coming from various online channels. In combination with attribution models, this will give a strong impetus to the development of analytics in the field of e-commerce.
Calculation of LTV cannot be replaced by a pool of other indicators - this is a valuable value that has economic and marketing meaning. Of course, it requires data collection to substitute in a fairly simple formula, but the efforts are worth it - it’s not without reason that some companies enthusiastically say that they saved tens of thousands of dollars after introducing LTV into the system of tracked business intelligence indicators. Awareness of customer value allows you to competently and reasonably develop loyalty programs, highlight truly "right" customers. And, as you remember, only the right bees carry the right honey.
Today, e-commerce is becoming more and more like a cellular operator: mass customer acquisition, serious outflow, numerous channels of lead generation and sales. This look of online commerce has created a new paradigm for calculating work efficiency - from the standpoint of LTV, the total value of the client. There are still few followers of this paradigm, but in vain.
Most internet marketers and analysts use a set of indicators in their work to evaluate the effectiveness of advertising campaigns: failure rate, CTR, number and share of conversions, churn (outflow), cost of attracting a client. These indicators can give a general idea of the effect of marketing activities and the level of customer loyalty, however, from a financial point of view, they make almost no sense if LTV is not considered together with them.
Why and how to read LTV?
- His calculation focuses on success - you will definitely know which channels bring you the best customers.
- You will know exactly the effectiveness of each channel to attract customers and will be able to redistribute costs based on the needs of your business.
- You will see the value of each customer group in the long run.
- You will be able to evaluate the points of savings, as well as to understand how much additional money you can spend on attracting and retaining a client (for example, through remarketing, mailing lists or advertising campaigns on social networks).
There are a lot of formulas for calculating LifeTime Value and they depend on the purpose of using this indicator.
Ready-made formulas
In order to easily determine the importance of a customer for an online store, it’s enough to use elementary summation over
- the volume of repeated orders, which was in the period under review compared to the previous one:
- we receive data on orders for the reporting period
- we receive data on orders for a longer period (for example, six months)
- we aggregate user data with the inclusion of all records from (1) and only matching from (2)
- summarize the data on orders for each user and find the average value.
You can also use the classic calculation formula:
LTV = (Monthly Revenue per Customer * GrossMargin per Customer) / Monthly ChurnRate
ChurnRate = Q / Nt , where
Q is the number of users left at the end of the period
Nt is the total number remaining at the end of the period
To simplify this formula and some comparison of sources can be used
GrossMargin per Customer = (TotalRevenue - Costs) / Nt
In general, you can find many formulas on the Internet and adapt them to a specific customer relationship management structure. Here, for example, is a fairly universal formula that can be found:
LTV = AC × N × P × t ,
where AC is the average check, N is the average number of purchases per month, P is the proportion of profit to the average amount of the check, t is the average life time of the user (how many allocated periods of time he is your buyer - in months, days, years).
There are also formulas tailored to customer churn. An interesting LTV calculation case can be found, for example, in a translated article in a blog .
Evaluation Method
The manager calculates the average cost of attraction, and then the average value of the client, the remaining groups are distributed on the basis of "below average" and "above average". This method is not the best solution, because It does not give exact values and does not take into account additional factors associated with a specific promotion channel.
Ready-made calculators,
which are provided by advertising agencies. You can see, for example, a calculator from Netpeak , which calculates LTV based on the data you entered. In principle, a good option, but it has general restrictions on the values, and also does not take into account industry specifics.
Custom-made calculators
For example, we in RealWeb calculate LTV for each of our clients and, based on the totality of this and other indicators, we build a further advertising strategy.
LTV calculation conditions
As you can already see, the simple means of web analytics when solving the problem of assessing the lifetime value of a client is indispensable. Unfortunately, in the general case, Google Analytics does not know how to calculate the LTV indicator, but we will talk about a particular one below. Accordingly, for the calculation of the indicator you will need to carry out some preparation.
Value segmentation is desirable.to understand which channels bring the most valuable customers from each segment. For example, take two buyers of a hardware store. Let each person spend 1,000 rubles each. (let's say AdWords). Client A came and bought a TV for 27,000 rubles. Six months later, he bought speakers for 3,000 rubles. Client B is the head of a software company. Once a week he comes to the store and buys a flash drive, then a cable, then a surge protector, then a cool mouse as a gift to a partner. On average, he spends about 1,200 rubles a week. A year passes. Client A brought 30,000 rubles. He will not return, because he no longer needs new household appliances. Client B brought 1,200 * 52 = 62,400 rubles. And will bring forth. And what do you think, who received the loyalty card immediately, and who - after accumulating a certain amount? Meanwhile
It is necessary to analyze the channels and campaigns that brought average and above average customers in order to allocate funds for incentives.
It is necessary to determine the client’s life time on the basis of experience or available statistics, to establish a unit of measurement for periods (for example, for a restaurant or a grocery store it is both a month and years, and for an online store - days and weeks, although this is not so simple) . In addition, it is necessary to measure the periods of repeated actions (purchases, payments) - so you can split the lifetime into intervals and predict profit or plan advertising activities.
As you already understood, the data for calculating LTV are taken from the outside, so it will be necessaryget data from CRM / ERP / 1C or from the financial (economic) department for further calculation. Here is a sample list of data you might need:
- average check per customer
- average number of purchases per client for the reporting period
- advertising costs per month and per period
- the number of new customers per month and for the period
- outflow of customers per month and for the period
- return rate
- percent discounts and margins for client groups.
The higher the client’s received value over the period of his life, the more room you have for further actions: developing loyalty programs, opening new channels of attraction, marketing activities and research activities. That is, in fact, you can freely spend money on such customers. If LTV detects a downward trend - this is a dangerous sign, you need to take measures and study the accumulated customer base and focus on sales and complementary sales. It's simple: retaining a customer is cheaper than attracting a new one.
Google Analytics has LTV for mobile apps
Indeed, the platform provides for the LTV section (in English and in Russian). The report, available only for application representations, calculates the LTV value in the context of attraction channels, based on the life cycle and revenue volume. A comparison of the LTVs of different user groups is also available. The maximum evaluation period is 90 days. This is a fairly small interval, however, it is quite suitable for mobile applications and their dynamics. It cannot be said that this report is ideal, but it gives some idea for further analysis.
In principle, by its logic, it is close to the cohorts that we have already considered in our blog. It is hoped that the tool will evolve and web analytics will have at their disposal a report to count LTV clients coming from various online channels. In combination with attribution models, this will give a strong impetus to the development of analytics in the field of e-commerce.
Calculation of LTV cannot be replaced by a pool of other indicators - this is a valuable value that has economic and marketing meaning. Of course, it requires data collection to substitute in a fairly simple formula, but the efforts are worth it - it’s not without reason that some companies enthusiastically say that they saved tens of thousands of dollars after introducing LTV into the system of tracked business intelligence indicators. Awareness of customer value allows you to competently and reasonably develop loyalty programs, highlight truly "right" customers. And, as you remember, only the right bees carry the right honey.