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For many companies, their entire business revolves around trying to figure out which customers are worth retaining and which are not. This has resulted in managers from the most various areas Businesses are looking for increasingly sophisticated ways to measure CLV (Customer Lifetime Value) to highlight the most promising customers in terms of future purchases.

Comment V-RATIO: CLV is a concept that has gained popularity due to its apparent obviousness and simplicity. Indeed, if we know that, having received less this client profit now, we get it "for life", why not let it "earn" a little for us? Unfortunately, not everything is so simple. If only because if we are not able to get “full profit” from a client today, who said that the value of our service (without discounts for supposedly “loyalty”) is so great that we will take the “lost received” tomorrow? As they say, "it was smooth on paper." About some ravines - this article. If we look at the idea of ​​collecting and analyzing data about our customers from the point of view of new marketing, then we can see its real benefits. You just need to think not about who and for what to give additional discount, but about how, knowing your customers deeper than your competitors, you can improve your product so that you don’t have to give any discounts at all.

Roy Cardiff's business is mail order sales, and he keeps track of sales for each client. Recently, he decided to cut costs and no longer send catalogs to customers who are unlikely to buy in the future.

His customers fall into three categories: those who made several small purchases in the past year; those who made one purchase, but for a significant amount; and those with whom relations are of a long-term nature, but on a non-permanent basis.

Which segment should be removed from the mailing list?

According to several Wharton professors who have studied the question in detail, there is no easy answer, despite new and increasingly sophisticated methods of measuring the so-called " lifetime value client", " Customer Lifetime Value” (hereinafter - CLV) - the current value of the probable future income received from a particular buyer.

"For many companies, their entire business revolves around trying to figure out which customers are worth retaining and which aren't," says Wharton marketing professor Peter Fader, author of the book. . “This has led managers across a wide range of businesses to look for ever more sophisticated ways to measure CLV in order to highlight the top prospects in terms of future purchases.”

The goal is not only to identify these customers, but also to "reach" them through cross-selling, multi-channel marketing and other tactics, all of which are tied to acquisition, retention and statistical measures known as RFM - time of last purchase, frequency and monetary value. value.

“CLV is popular today,” notes Wharton marketing professor Xavier Dries, co-author of “ ". Although CLV is not a new concept at all (it has been used in banks for a long time when working with accounts), the concept has acquired new life with the widespread use of the Internet, "which allows companies to connect directly with people at low cost." CLV, according to Dries, "views customers as a resource from which companies seek to extract the maximum possible amount of profit."

However, many companies are suddenly realizing that CLV, which is one of the components of CRM, is a rather elusive indicator. Firstly, it is difficult to calculate it with a certain degree of accuracy, and secondly, it is difficult to use.

"The only number a manager can be sure of is the client's ongoing profitability," says Wharton marketing professor George Day. “And then the main question becomes: now that we have all the information, what to do with it? Some companies use it to develop special programs for different value segments. In the financial industry, for example, customers receive different levels of service depending on the size of their account. But there is always a risk that by doing so, you can piss off other customers.”

What's more, it's very difficult to predict how long a company's customer will stay or assess its "growth potential," says Day. "Companies don't know how profitable their customers are."

Throwing the dice

CLV is an attractive concept, but for a number of reasons it is often difficult to apply in practice, notes Wharton marketing professor David Bell in his paper. Seven Barriers to Customer Equity Management.

CLV, according to Bell and others, works best in industries where customer acquisition and retention costs are high, such as financial services, airlines and hotels. "It's also useful in situations where the entire business is run by a small number of people, and where firms can offer bonuses and discounts to influence customer behavior," says Bell. As an example, he cites airlines, which can give a “value” customer a free seat in first class, which is very important and pleasant for the passenger, but costs the company almost nothing.

Gathering information for CLV can provide certain companies with a number of benefits. For example, individual data collected by a hotel will help determine best clients and offer them to cross-sell other products. They allow a company's marketers to reach out to a specific group for information. Using feedback, the company can make more informed decisions about the more efficient allocation of marketing resources. Suppose the information collected shows that a significant number of hotel guests come from New York, and their average age about 50 years old. The hotel can use this data to more accurately reach the target audience.

Bell cites the story of Harrah's Casino as a success for CLV. Based on the information collected through the loyalty program, Harrah’s can now accurately tell “who arrives at the casino, where they go when they go inside, how long they sit at different tables, etc. This allows us to optimize both the configuration of the tables in the gaming hall and the entire activity.”

Others cite health care and credit cards, direct marketing and online mailing lists as destinations that can directly benefit from CLV, in part because they interact directly with consumers and can easily track their feedback. For example, salespeople in the pharmaceutical industry can use the information they collect to decide how often to see doctors to promote their company's drugs.

Basically, says Day, CLV is most applicable “when you have a database of customer and transaction information. But if you work, for example, through retail chains and you don’t have direct contact with customers, then it becomes much more difficult to apply this indicator.”

Now that marketers can gather better information to determine customer lifetime value, how can this information be used?

The answer, according to the researchers, is “carefully.”

“People are all different,” says Bell. “On an individual level, it is very difficult to predict the behavior of an individual client. It is easier to predict the behavior of market segments. We can say, for example, that on average business people will spend “x” nights at the Hilton. But if we try to predict how many nights Mr. Jones will spend in the hotel, the problem becomes much more complicated.”

One difficulty in implementing CLV, adds Bell, is that forecast models are too sensitive to assumptions. For example, models often assume how long a customer will maintain a relationship with a company and how much they will spend. However, some of the assumptions may be wrong. "Just because I spent $100 last year doesn't mean I'll spend $100 this year," says Bell. “Or, if the client does not show himself in any way, does this mean that he temporarily stopped using the product or went to competitors?”

In particular, the problem with estimating the capitalization of Internet companies was that "many companies made unreasonable assumptions about how much their customers cost, how much it cost to acquire them, and how long they will remain customers in the future," notes Bell. “Customer dollar value calculations are very sensitive to these critical assumptions. Any mistake you make can be fatal. In other words, your estimates will drastically diverge from reality if at least one of the assumptions was wrong.

“However, many companies are already using one or another tool for determining your value in order to understand how to treat you. If I am a regular customer, my call will be queued. If not - two beeps, and picks up the phone real manager. But this approach assumes low mobility of people. You sort them into different baskets and they stay there. However, maybe if you had treated me better in the beginning, I would have become a more valuable customer.”

In addition, when firms evaluate their clients, they draw conclusions based on what they know. “Information is always lacking here. I don't know what you do in other places. Maybe you spend $100 a year with us and $500 with our competitors,” says Bell. “This is a lack of methodology. You are trying to determine the value of people based on the information that has accumulated in the course of his communication only with you and with no one else.

Whichever model a company uses can only provide a starting point in its decision-making process, adds Bell. "Intuition and managerial experience has not been canceled."

Day cites the case of a large equipment manufacturer who found that serving one of their customers was not profitable. "What to do? The client may not be profitable, but in such markets, one client can account for up to 15% of all sales. It takes a certain amount of courage to announce that you can no longer serve him... And it's even harder to predict the future value, because you don't know how the customer will behave in the future. The biggest risk for a company is to inadvertently turn away a client that could be profitable in the future.”

Fader suggests that individual CLV models ignore "inherent human unpredictability". “These models look at past customer behavior… But past transactions are not the best or only indicator for predicting the future.”

Water skis and goggles

Although tactics such as cross-selling and add. Sales have been around for years, and today they are being used even more frequently and aggressively in an attempt to artificially increase the lifetime value of customers, Fader says. However, this practice has two sides.

In cross-selling, the company that sold you water skis, for example, will try to sell water goggles as well. For marketers, the reason is obvious. "It's easier to sell to someone you already know," Dries says. "It's an attempt to maximize the value of the relationship you already have." Fader, however, is skeptical of such tactics. “If someone's behavior within a category is random, then that means you're taking the ambiguity in one category and adding it to the ambiguity in another category. It is very difficult to establish a stable connection between them.”

Additional sales can also cause problems. Take, for example, Amazon, which provides free shipping if the customer has spent "x" dollars, or after buying the first book, offers a second book at a discount. “In the Amazon example, the customer would probably have paid full price for the second book as well, and wouldn't have needed to give a discount,” says Fader. “Some companies put too much effort into upselling. It is difficult to assess the actual effect of them. Just looking at sales volumes does not show the exact amount of potential profit that can be directly related to marketing efforts.”

A sales tactic similar to cross-selling is multi-channel marketing. “Before, companies had only one point of contact with the customer,” says Fader. “But today there are many different types of stores, plus the Internet, direct mail, call centers, etc. And the question of resource allocation arises. If one customer used the internet and another customer used the call center, should we treat them differently? Clearly you can encourage people to use the internet because it's cheaper than running a call center, but who exactly? What behavioral characteristics distinguish people who can be pushed to this? Should you risk the loyalty of people who are used to making phone calls and redirect them to the Internet, or is it better to focus on less loyal customers from whom you still cannot get the full benefit?

It all boils down to one thing, says Fader – “Some tactics work, others don't, but in general it's very difficult to estimate the return on marketing investment and tie it to CLV measurement/management. As companies try different tactics on their customers, they are inadvertently polluting CLV data, making it even more difficult to choose who to focus on in the future and who to ignore.”

Research

In a recent work entitled Investigating Recency and Frequency Effects in Customer Base Analysis, Fader, along with Bruce Hardy, Chun-Yao Huang, and Ka Lok Lee, examines how database marketers assessed the value of different groups of customers based on their past behavior prior to the widespread adoption of CLV. “The most popular was to categorize customers by RFM: time of last purchase, frequency of purchases, and monetary value of past transactions,” says Fader.

RFM has its roots in direct marketing, one of the most progressive industries in terms of using the CLV concept. Fader and colleagues wanted to understand how a simple RFM measurement relates to more complex CLV estimates. Can it act as a "main indicator" of future purchases. “If you have a customer who bought a lot of product, but a long time ago, and a customer who bought a little, but recently, which one of them is better in terms of CLV, which means who should you focus on?” Fader asks. going back to the first example. “And what is the relationship between the time of the last purchase and the frequency of purchases?”

In their paper, Fader and his colleagues suggest that simple statistics such as the frequency and time of the last purchase can provide a fairly accurate estimate of future value, i.e. “Based on the limited amount of information collected, when used correctly, it is possible to construct a CLV forecast that is almost as accurate as one based on a complete and detailed customer relationship history. The main thing is what kind of information to use, and how to use it correctly.

AT Biases in Managerial Inferences about Customer Value from Purchase Histories: Intuitive Solutions to the Mailing-List Problem, Fader acknowledges that "in the real world, identifying key customers is still largely a matter of intuition." In other words, despite complex models and extensive information, "managers make subjective decisions about which customers to consider as a future source of company revenue."

The paper points out that almost no work has been done to assess the ability of managers themselves to "draw correct conclusions about the potential of customers based on their purchase history." The researchers set up a learning situation in which participants were shown several purchase histories of a number of customers and asked to evaluate them.

We've found, Fader says, that managers are highly inconsistent in their use of information such as the timing, frequency, and monetary value of purchases. They use the data depending on what task they are facing now (for example, which of the clients to include in the mailing list and which to exclude).

AT A Renewable-Resource Approach to Database Valuation, Dries and André Bonfret suggest " A New Look on clients." Traditional CLV looks at net profit received from one client. When assessing the lifetime value of a client, the assumption is always taken into account that at some point he will leave, ”Dries says.

But if you make that assumption, he adds, “you seriously undermine the value of the entire database. If you try to optimize your marketing activities based on this formula, you will come to the wrong conclusions. Yes, every year you lose a certain percentage of customers, but you get new ones. You should take this into account when evaluating a database." In other words, "it is necessary to maximize the value of the database, not the customers."

In another study by Noah Gans, Wharton professor of information management looks at CLV from an optimization perspective: if a company has limited resources, which customers should you focus on?

Hans built theoretical models considering how the time a customer spends with an average service provider is affected by the quality of that service. “You can achieve a significant time drag by improving the quality of the service,” he says. But the model also takes into account other factors: What is your competitor doing? How much does it cost for a customer to change providers? How does the development of technology affect transactions?

At some point, a company deduces what type of customer it is facing. “Then comes the action—the customer is offered a certain level of product or service. For example, when calling a call center, it is given priority. This is the operational control used by the company in determining what this customer receives and how much it costs to serve him.

Hans says he wants to use marketing models to improve operational decisions. "I'm waiting for someone to give me a model of customer behavior, how they respond to different levels of service, then I can estimate the cost of providing a certain quality of service."

He gives the example of cross-selling. “It's a very simple problem. After the service is delivered, you decide if it's worth trying to cross-sell. For example, in a call center, cross-selling lengthens the time of one call and makes other callers wait longer. You must determine how many cross-sells you would like to make, how much additional resources it took, and so on.

“When making any decision, there are four main marketing factors that must be taken into account: price, promotion, product and place of distribution, which are all related to marketing, but have a direct impact on the entire activity of the company.”

Hans touched on some of these questions in his latest work Customer Loyalty and Supplier Quality Competition. There are mathematical formulas for determining "customer share" as a function of determining the overall service level of our hypothetical service provider and its competitors.

It also shows that there is a "standard" level of service that all competitors have to adhere to. "AT real life, such things are often referred to as "world-class services," he says. “For example, in call centers, the generally accepted standard is to answer 80% of calls within 20 seconds.” And the more competitors in the market, the higher the industry standard.

Speaking in terms of CLV maximization, Hans believes it makes sense for companies to keep track of each customer's history and use that to decide which bucket to place them in. “Then, based on your findings about the characteristics of this basket, you can decide how best to treat these customers. But you should remember that every time a client comes to you, you don't really know what kind of client he is. So the best solution for you is always to take into account your incomplete awareness of the possible reaction of the client.

LTV is one of the most important analytical metrics in business. You can take into account the number of views, visitors, the time they spent on the site or average check- but the most balanced metric in the field ecommerce is LTV.

In this article, we present several simple ways, which will help increase the “lifetime value” of the client for the company.

What is LTV?

LTV (Lifetime Value) is the total profit of the company received from one client for the entire time of cooperation with him. There is also a simplified version of the Russian definition, which briefly characterizes this indicator - the lifetime value of the client. This metric is also called CLV (Customer Lifetime Value) or CLTV.

LTV outperforms other KPIs because it focuses on long-term customer value and does not account for seasonal fluctuations or positive/negative trends. An increase in LTV directly entails an increase in profit for a business, as it affects the entire buying cycle.

According to Marketing Metrics, the chance of selling a product to a new customer is 5-20%, while the chance of selling to an existing customer can be up to 60-70%. By focusing on returning customers, you are focusing on a long-term strategy that gives your business higher returns.

1. Effective email marketing

Secondly, you can segment customers based on their purchase history and thus increase the effectiveness of each email.

Try to create the right content:

2. Create as many customer touchpoints as possible

Create new touchpoints and invade your customer's information environment. Try to ensure a permanent presence on Facebook, Instagram, Vkontakte, forums and other communication channels. By interacting with your customers in a variety of places and methods, you add value to that customer's “lifetime”. The idea is simple, but putting it into practice can be a bit tricky.

• Make a list of places where your customers spend time, both online and offline;
• Develop an advertising or content marketing presence in these locations;
• Encourage customer engagement with your brand.

by the most simple example icons serve as such a touch social networks on your website:

3. Use a subscription model

By turning a product into a subscription service, you naturally increase your LTV. By changing the payment system from a one-time purchase to a multiple purchase, you form an audience of regular customers who create a stable income stream.

As an example, let's take an online cosmetics store that provides an opportunity to subscribe to monthly delivery probes:

Birchbox took the subscription format to their business and made the right decision: Not only does the company generate $110 in revenue per subscriber, but it also gets customers who stay with the brand for a long period of time and, as a result, have a higher life cycle value.

4. Upsell and cross-sell

It's easier to sell to an existing client than it is to acquire a new client. By upselling your product, the customer's lifetime value for the company increases. Offering accessories, expendable materials or a service to your product, you will not only add value to the customer, but more importantly, earn their loyalty.

Upselling and cross-selling generate far more profit than you can make from selling to new potential buyers. Remember that there is a 60-70% chance of making a purchase from existing customers. You only need to motivate users for subsequent purchases.

5. Quality customer service

They stop working with the company due to poor customer service. Quality customer service is powerful way LTV increase.

In a famous Harvard Business School report, researchers found that as little as a 5 percent increase in customer retention results in a 25-95% increase in profits! Thus, increasing the retention rate increases the value of the buyer's life cycle, since the longer the consumer remains a client of the business, the more profit it brings.

According to Help Scout, Disney Parks is revisited by 70% of visitors. Believe me, there is no magic here! All the efforts of the park staff are aimed at ensuring that a smile does not leave the visitor's face during the entire visit to Disney. It turns out a simple formula for success: satisfied customers = regular customers!

Here are some easy ways to improve your customer experience:

• Prioritize quality over quantity;
• Be responsive. Do not leave phone calls unanswered emails. Reduce response time to the minimum possible;
• Publish expert content;
• Do a little more than what is expected of you;
• Take care of the client;
• Smile! Smile on the phone. Smile in your letters. Just smile)
• Provide discounts to loyal customers;
• Be patient with dissatisfied customers. Sometimes a small step on your part is enough to turn a negative customer into a permanent one;
• Always communicate in a positive way;
• Never interrupt a conversation with an annoyed client.

Working with clients is about building a system of relationships. Loyal customer The one you get on well with will, in turn, treat you well.

conclusions

There are many articles and tutorials out there that describe how to deal with abandoned carts, organize your content strategy, and create added value for your customers. But very little is said about methods of influencing LTV.

We have formulated some simple ways by which you can turn ordinary customers into loyal business partners.

1. Stay always in touch, create a regular interesting and useful newsletter;
2. Find new points of contact with your customers and be present wherever they are;
3. Turn your customers into loyal customers by implementing a subscription model;
4. Don't forget about upsells!
5. Make quality customer service a priority for your business.

Based on materials

Nobody disputes the importance of customer loyalty, but the question often arises, how to measure it? Is loyalty measurable or is it an ideal to strive for? If an organization has not run a loyalty program, can anything be measured? How not to drown in the flow of information on customer loyalty and start measuring the results of your work?
The article below summarizes the key loyalty metrics that can be measured in every organization.

Customer Lifetime Value (CLV) - customer lifetime value

CLV is one of the fundamental indicators applicable to any business. First of all, it makes us understand whether it is worth doing loyalty management in an organization at all. The client came, paid for the purchase and left. Is it valuable to us? If we count CLV, then we can answer this question, because it may turn out that such a customer makes purchases three times a year and stays with us for three to five years. Considering the profit that we receive from such customers throughout the entire time of interaction with them, and not for one purchase, the answer to the need for loyalty management will be “YES!”
CLV is well suited for measuring loyalty, as it takes into account the real indicators of interaction with the client - how much he buys and how long the cooperation with him lasts. Nothing superfluous, just a measurable financial result.
While CLV won't tell you how loyal your company's customer is right now, it will measure the success of your long-term loyalty efforts. If you calculate CLV not for the entire customer base, but for customer segments, you can achieve even more noticeable results by varying the costs of the loyalty program for different customer segments, because knowing the lifetime value of customers from different segments, you can make decisions about how to manage customer loyalty based on clear, measurable data, don't spend too much on rewarding low-yielding customers and invest more in building long-term customer loyalty with high lifetime value!
Several formulas can be used to calculate CLV, we recommend using the simplest one:

CLV = t × c × ƒ,

where t- duration of interaction with the client, c - average cost of purchases of the client during the interaction, ƒ - the frequency of purchases per unit of time.

Repeat Customer Rate - share of repeat customers

While customer lifetime value is an excellent metric for tracking how loyalty has changed over time, repeat buyers provide a measure of the current value of the state of affairs. Repeat Buyer Share is the percentage of buyers who make repeat purchases from you.
A repeat purchase is not yet a measure of loyalty per se, but studies show that if a customer makes three purchases from you, the likelihood of subsequent purchases increases by 54%!
The share of repeat customers is calculated quite simply:

RCR reflects the current state of customer loyalty to your business, but unlike Customer Lifetime Value, it does not measure financial results your work with loyalty. Measuring and analyzing both CLV and RCR will allow you to have more accurate data on your customer loyalty.

While the previous two indicators were objective data collected from accounting systems, the Net Promoter Score (NPS) is measured based on customer surveys and shows the subjective assessment of customers of their experience with the company. NPS is one of the best-known loyalty scores and can be measured even if your accounting system does not provide for fixing other indicators of work with clients, for this it is enough to introduce the practice of conducting customer surveys in the company.
The NPS scoring involves a customer survey with one simple question, "How likely are you to recommend us to your friends and family?" in which customers are asked to select one of the ratings on a scale of 1 to 10, where 0 is the least likely, 9 the most confident.

Customers who answered 8-9, we refer to " promoters", who chose ratings 0-5 - to " detractors", and between them remain" passive" - Satisfied, but devoid of enthusiasm, customers who can either become "promoters" or "ill-wishers" or go to competitors.
The NPS indicator reflects the actual state of loyalty of your company's customers, because. the previous two measures fail to separate true loyalty from forced loyalty or low price loyalty.

The NPS study should be included in the overall communication system with the client, because. a study with only one NPS question can be skewed.
Ideal scores of 100% are almost impossible to achieve. For example, Apple in 2013 had NPS = 76% - and this good result strong brand.

Redemption Rate (RR) - redemption rate of the reward

This metric measures how engaged your customers are in your loyalty program, understand its terms and enjoy the benefits you provide. The Redemption Rate is measured if your company has already launched a loyalty program. In essence, the Redemption Rate is the percentage of accrued bonuses that were used to pay for subsequent purchases.

If members earn bonuses but never spend them, then they cannot be classified as loyal and our loyalty program does not reach the goal of such customers. A Redemption Rate below 20% indicates that the loyalty program is not working the way you would like.

Customer Lifetime Value (LTV) is the amount of total income that the buyer brings during the period of cooperation with the company.

Its correct calculation will help determine how much money your customers spend, how often they spend it, as well as what programs and bonuses they are interested in and can make regular customers.

Why is LTV so important? In Internet business, the term Return On Investment (ROI) is often used. ROI is the percentage of profit received in relation to the investment made. Incorporating customer lifetime value into your ROI calculation will help you see the full picture of your business' profitability and how it can be managed. We will definitely tell you more about ROI, but for now let's get back to the customer's lifetime value.

How to calculate customer lifetime value?

There are several ways we can use to count LTV. Let's start with the basic formula:

Average order value X Number of sales X Loyalty period

For example, take the Birchbox hot subscription service, a monthly subscription for which costs $10 for women and $12 for men.

$10 X 12 months X 3 years = $360

Using Birchbox as an example, a female subscriber brings in $120 a year for the company. If a customer stays with them for 3 years, then the lifetime value will be $360.

FormulaLTV no recurring subscriptions

So our calculations so far have been simple. Consider an example where we need to calculate the LTV of buyers who do not make the same payment every month.

Take, for example, an online store selling home medicines. Let's choose three separate buyers to calculate the average sales:

• Client A takes care of her diabetic grandmother. Every month he buys syringes and test strips, sometimes a blood glucose meter. His monthly purchases are $60.
• Client B buys diabetes tests every month and her average order is $25.
• Client C buys medicines for several members of his family. Every month she buys test strips, syringes, insulin pumps, special containers and socks for diabetics. Her monthly spending on purchases averages $150.

Let's calculate the monthly sales for these three buyers:

We add up the monthly check of each customer and divide the resulting amount of $ 235 by their number. Average monthly revenue is $78

$78 x 12 months x 5 years = $4680

According to this formula, the customer lifetime value is $4680 for the entire period, or $936 for the year.

Why you need to knowLTV

Realizing the importance of the information received for your business, devoting a few hours to all the calculations, you will be able to determine which customers are the most valuable to you, how to distinguish them, what affects the loyalty of your customers and what methods you can use to increase LTV.

customer lifetime value(customer lifetime value, CLV or often CLTV), lifetime value(life-time value, LTV) is a prediction of net income associated with all future relationships with a client. The prediction model may have different levels sophistication and accuracy, ranging from approximate, heuristic, to complex, using predictive analysis techniques.

Customer lifetime value can also be described as the monetary value of a relationship with a customer based on the current size of the visible future. cash flows from the relationship with the client. Customer lifetime value is an important concept in that it encourages companies to shift their focus from quarterly earnings to long-term healthy relationships with their customers. Customer lifetime value is an important number as it represents the upper limit of the cost of acquiring new customers.

One of the first mentions of this term was made in 1988, in the book Database Marketing, which contains detailed working examples.

Target

The purpose of the Customer Lifetime Value (LCV) measure is to gain access to the financial value of each customer. Don Peppers and Martha Rogers are credited with the following quote: "Some clients are more equal than others." The value of customer lifetime value (the difference between income and customer relationship costs over a given period) is that CCP looks into the future. In fact, the PCC is useful in the formation management decisions, but it is very difficult to determine. The calculation of the PCR implies the prediction of future activity.