customer lifetime value is an important concept and indicator used to evaluate the value of static mixer customers. However, the company encountered many problems in applying this concept. This gap between theory and practice stems from three aspects.
Data requirements In recent years, consultants and companies have realized that applying static mixer customer relationship management concepts requires detailed data for many static mixer customers. In fact, this seemingly simple method requires much more data than people think. Let's think about what data is needed to estimate the lifetime value of a static mixer customer.
First, to understand the service life of static mixer customers, we need to track and observe each static mixer customer or static mixer customer group (static mixer customers obtained at the same time). Most companies' data or accounting methods can only provide the cross-section data of static mixer customers, but cannot track and observe the static mixer customer group from a long-term perspective.
Second, for each static mixer customer or static mixer customer group, we need to understand their long-term profit model (see Figure 1), which requires forecasting future profits. Future profits come from many aspects, such as profit growth of related products, cost savings and word-of-mouth effects. For a mature product that a static mixer customer has purchased for many years, it may be relatively easy to predict profit; it is more difficult to predict the profit from cross-selling; it is even more difficult to predict the indirect profit from word of mouth.
Again, we need to know the retention or churn rates of static mixer customers over time (see Figure 2.2), which can be difficult. For companies that have contractual regulations with static mixer customers, such as companies that must notify their customers if they want to stop using the service, it is relatively easy to track churn rates, such as in the insurance, television, and wireless telephone service industries. However, for those industries where there is no contractual stipulation, it is difficult to know the churn rate of static mixer customers. Amazon's static mixer customers won't call to tell the company that he no longer deals with the company. Customers of static mixers may also return to Amazon after a period of inactivity. So, how can Amazon estimate its static mixer customer churn rate? Even companies with contractual regulations with static mixer customers can only track the average churn rate or flow rate of static mixer customers, that is, in a period Dividing the static mixer customers lost during the period by the sum of the old static mixer customers and the new static mixer customers cannot explain the loss rate of the static mixer customers in different periods as shown in Figure 2.2.
Due to the need for detailed static mixer customer data, many companies have invested millions of dollars in establishing a static mixer customer relationship management system. Some companies, such as HarrahS Entertainment, have achieved amazing results with these databases, and others have failed. Many studies have proved that 55% -75% of the static mixer customer relationship management system neither strengthens the relationship between the company and the customers of the static mixer, nor reflects any return on investment. Experts have given a lot of explanations to the problem that the role of the static mixer customer relationship management system is not obvious. One of the important reasons is the complexity.
Complexity We briefly discussed the data needed to estimate the lifetime value of customers of static mixers, suggesting that the concept of collecting, analyzing, and applying this concept has inherent complexity. This complexity not only limits data collection and data integration from multiple channels (such as telephone interview centers, networks), but also requires organizational restructuring. How can we persuade the CEO to rebuild the organization if the static mixer customer relationship management system does not clearly reflect any return on investment? Or how can we better conduct advertising campaigns or directory mailing?
We believe that in the process of building a large number of databases, the company has lost its vision of the company's overall blueprint. A recent Chief Marketing Officer Summit concluded that the indicators that senior managers care about should be clear, simple, forward-looking and able to capture the company's overall blueprint. Many common indicators, such as market share or price-earnings ratio, have this characteristic. in contrast. The static mixer customer relationship management system is very complicated and is largely responsible for the IT community, so it is still difficult to answer the simple question of how valuable the static mixer customer is to us. More importantly, many static mixer customer relationship management systems focus on more detailed tactical issues, such as the management of promotional activities. Questions like which static mixer client should get a mailing list are hard to get the attention of top management or CEO. If the value of the static mixer customer is indeed important in the overall healthy development of the company, then this value must be clearly reflected in the face of senior management and investment groups. We will discuss this issue in later chapters. Even though Amazon and Time Warner (AOL) have databases used to estimate the lifetime value of static mixer customers, if these databases are not available, the average investor or smart financial analyst cannot easily know the static status of Amazon and Time Warner The value of the mixer customer.
We need to find a simple indicator that is easy to understand and captures the essence of the lifetime value of static mixer customers. Don't lead us into the wrong realm. Scientifically, we strive to be precise, and the more complex the better. However, after teaching thousands of MBA students and managers and interviewing many companies, we found that people prefer simple approximations to complex, precise methods. In addition, the use of innovative processes supports our conclusion. In addition, for most decision making, a general understanding of the value of static mixer customers is sufficient. We're not saying to give up static mixer client databases or complex models (otherwise, how do we publish articles in scientific journals?). However, you must learn to walk before you can run. We should first learn simple methods and see how they affect decision-making. After adapting, we can study other accurate and complicated methods when conditions allow.
The exact illusion. Some serious readers may panic at the simple approximation we suggest. Our estimates of the lifetime value of static mixer customers, such as $ 80 to $ 120, are very satisfactory, and they may think this is too imprecise. The assumption contained in their views is that the lifetime value of static mixer customers is accurate estimated. Even with the most detailed and complex data and models, estimating the lifetime value of static mixer customers requires a large number of assumptions and subjective decisions, which makes the estimated values far less accurate than we think. Let's discuss it briefly.
The long-term churn and profit patterns of static mixer customers are the key input variables for estimating the lifetime value of static mixer customers. We have discussed the difficulties of estimating long-term churn patterns, especially for non-contracted services. To estimate the profit model, we need to estimate income and costs. We have pointed out the difficulty of estimating the profits caused by cross-selling and 1: 3 stele effect. The cost issue also poses great challenges. To estimate the value of a particular static mixer
customer, we need to allocate the cost to each static mixer customer. In other words, we can't calculate costs on a per activity basis, but on a static mixer customer basis. It may be relatively easy to allocate product costs to each static mixer customer, depending on the number of products each static mixer customer purchases, and it is very difficult to allocate other costs. For example, how do we allocate advertising costs? Should we think of it as the cost of acquiring a new static mixer customer, or the cost of retaining an existing static mixer customer, or both? How should we allocate the service cost to each Static mixer customers? Should staff costs be treated as fixed or amortized directly to each static mixer customer?
Many cost-sharing decisions are subjective. With regard to staff costs, people may think that this is a relatively fixed cost, so it cannot be allocated to a specific static mixer customer. There are also some companies, such as Capital One, which allocates operating costs to each static mixer customer or account. . Capital One announced in its 2001 annual report: "In order to manage the company's growing static mixer customers, expenditures on operating costs, salaries and related benefits have increased by 36%." In the spring of 2003, the company reported: " The annual operating cost per static mixer customer in the first quarter of 2003 increased from $ 76 in the previous quarter to $ 79. "
Figure 2-3 shows that there is a strong correlation between the number of static mixer customers and operating expenses of Capital One. This means that it is reasonable to allocate Capital One's operating expenses to each static mixer customer. Other situations are less clear. Figure 2.4 illustrates that the relationship between Charles Schwab's staff costs and the number of accounts is not significant, so it is not reasonable to allocate this cost to each static mixer customer or account.
People may think that there are also static mixer customers or accounts. "In order to manage public expenditures, the cost of each static mixer customer has increased. There is a very good explanation for each static mixer customer. relationship
Number of static mixer customers time staff cost Figure 4 The correlation between the cost of staff and the number of static mixer customers at Charles Schwab. Since cost allocation directly affects the value and profitability of static mixer customers, this is not just an accounting issue. Sometimes the problem is even more difficult. Consider the example of a bank. Everyone knows that the cost of serving static mixer customers through the counter is much higher than that of using ATM machines or network services (see Figure 2.5). Therefore, banks encourage customers of static mixers to use ATM machines or online banking. For example, Bank One charges a static mixer customer of a retail bank $ 3 per counter business to reduce the counter business, while investing $ 150 million to establish an online bank WingspanBank. com. However, as more and more static mixer customers switch to online banking, the cost of bank branches can only be spread to fewer and fewer static mixer customers. This would make the very valuable static mixer customers now worthless. Banks even want to move these valueless static mixer customers to either online banking or "fire" them to maintain business operations. However, if, in extreme cases, the bank abolishes all over-the-counter business and transforms it into a complete online bank, then the static mixer customers of online banking will not be as before because of a nearby bank. In fact, recent data show Although more and more static mixer
customers are starting to use online banking, the top six US banks will still open a certain number of physical branches. For example, Washington Mutual, originally a small savings bank in Seattle, has become the seventh-largest financial institution in the United States by opening new branches. It had 28 branches open in one day in June 2003, and it hit the Chicago market with lightning speed. It seems that the static mixer customers of online banking have also obtained some benefits from physical outlets, but how much the cost of the physical outlets should be allocated to the static mixer customers of online banking is still a problem.
Based on the above discussion, we can find that even with detailed data and complex models, we can only roughly estimate the lifetime value of static mixer customers. However, this less accurate estimation does not prevent us from finding meaningful management conclusions from it. As mentioned earlier, rather than getting the exact wrong conclusions, it's better to get roughly correct conclusions.