| CRM enthusiasts typically howl when I say that CRM is, in effect, a vertical within BI. Again, let us refer to the BI loop: BI extracts data from the operational environment and stores the data in some structure that is distinct from the operational system. The extraction process transforms and cleanses the data to be consistent with the data in this other structure. The Decision Support System (DSS) delivers this data to the decision maker, who uses it to formulate some plan of action. BI is a necessary component for any business process. In processes where the consumer is the target of the analysis, BI can create significant differentiation. Most other BI endeavors create internal efficiencies that indirectly enhance value to the customer. CRM performs this same process. CRM takes the data from the operational environment and stores it in the CRM system. It then provides this data to the decision maker, who uses it for managing the relationship with the customer. Figure 12.2 presents this flow of information. Figure 12.2. BI-enabled e-commerce = CRM.  The loop shown in Figure 12.2 is similar to the BI loop presented in Chapters 1 and 3. In this loop, the operational systems from which we extract data are the systems that record the interactions with the customer. These customer- facing systems can include Point-Of-Sale (POS) systems that record purchases made by customers, customer support systems that record post sales activities, and especially Web sites that record Internet-based communication with customers. All of these systems are possible source systems for our IEBI/CRM solution. As we can see in this figure, the IEBI system aggregates the data from the customer-facing system to provide customer intelligence. The customer intelligence provides a complete picture of the customer, a 360-degree view. This complete picture is in terms of the individual as well as in the context of his or her demographic groups. It shows the individual customer and, where appropriate, the household to which the customer belongs. This complete view also presents an analysis of past behaviors to predict future actions. The decision maker uses this data to guide future interactions with the customer. These interactions may be both reactive and proactive. We discuss each type of interaction later in this chapter. For now, we need to understand that CRM is not a separate system that sits outside of IEBI. CRM is as essential an ingredient in the IEBI solution as the Balanced Scorecard (BSC) and Activity Based Management (ABM). The balanced scorecard applies IEBI to the management and formulation of strategy. ABM applies IEBI to the management of cost. CRM applies IEBI to the management of customer relationships. While IEBI/CRM is an IEBI solution, it is a solution with an additional ingredient, a solution with its own unique flavor. It is the difference between marinara and Bolognese. In the next few sections, we look at how this additional ingredient transforms the other elements of our solution. We look at how adding meatCRMto our sauce has changed its flavor. 12.3.1 THE VALUE OF THE CUSTOMER RELATIONSHIP The first ingredient of the IEBI/CRM solution is the meat itself, the customer. It is, in effect, the base of our sauce. One of the major benefits to being a customer-driven organization is that as the market changes, so does the organization. Think of this in terms of our solution. If we use beef as the base of our sauce, we have a sauce that is different from one with a pork base. The market, or customer, is the base of the solution. As its flavor changes, so too does the flavor of our solution. This change in perspective focuses on the nature of the relationship we have with our customer. CRM is about relationships . The engineering-driven organization sees them as users, those pesky people who never truly appreciate our genius. They tolerate them because they perform a service. The sales-driven organization sees them as a one-night stand . They buy them dinner, hold their hand, and tell them they love them. Then, once they close the deal, it is on to the next sucker with money. To describe the quality of the relationship in both these situations as poor is an understatement. In the customer-driven organization, the thing that is of real value to the organization is not its technology or the individual sale. The greatest asset to the customer-driven organization is the relationship established with the customer. In this type of relationship, we are concerned with providing for the needs and wants of the customers. We exist to serve them, to make their plight better. Through the continued delivery of quality service, we create customers who remain loyal to our company. It has long been maintained that it is 10 times more expensive to find a new customer than it is to keep an old one. About 2 years ago, I was returning from Chicago from a speaking engagement. I arrived at the airport very early and spent about 2 hours waiting for my flight. Then, 15 minutes after our scheduled boarding time, we were told our flight had been cancelled. This made me angry , since this just happened to be 20 minutes after the departure of a competing airline's flight to the same destination. I was not in the most pleasant of moods . After a heated exchange with the airline representative, I turned to walk away. Then, just barely loud enough for me to hear, he said "If you don't like it fly another airline." As I waited for my next flight, I used my cell phone to call his CEO. I informed the CEO's office that I planned to take the employee's advice and that they would not see me on another flight. In a sense, we broke up. I terminated the relationship. Consider what this one statement by the employee cost the airline. On average, I make one round trip a week. With that one statement, the employee shifted all of that revenue from his employee-owned airline to his biggest competitor. What will it take to move that many customers from the competitor to their own airline? How much of a discount will it have to give? What promotions will it have to run? The airline lost not just one but 50 flights annually. Let's explore the difference between these two. We can view the customer relationship as an annuity. When properly maintained, that relationship provides an ongoing revenue stream to the organization. This is known as the customer's LifeTime Value (LTV). Just as we can determine the present value of an annuity, we can determine the present value of a relationship with a particular customer. The current LTV of a customer is a summation of the profit for each year times the Present Value Interest Factor (PVIF). Before we look at a specific example, let's take a moment to understand what we mean by PVIF. The present value of something in future is how much we would need to invest today to have that value at a given point in time in the future. For example, if I have an account that gives a 6 percent annual return on my investment, and in 5 years I want to have $200 in that account, I would have to put $149.46 in that account today. The PVIF is the factor we apply to that future amount to put it in today's terms. The PVIF for 5 years at 6 percent is .7473. Figure 12.3 illustrates how to apply this calculation to LTV. In the figure, we see that a particular customer is expected to initially generate $100 profit in the first year. The present value of this profit at a 6 percent interest rate is $94.34. We apply this same procedure for the expected profits from this customer for the remaining years of the expected life of the customer relationship. Summing these values gives us an expected LTV of $1,413.24. Figure 12.3. Calculating customer LTV.  As we can see, the customer's LTV is calculated for the entire length of the relationship. What determines the length of the relationship is the strength of that customer's loyalty. In our futuristic story, customer loyalty was built through understanding customer needs and wants. The better we are able to meet these desires, the more loyal they are to us. There are two important points concerning customer LTV. First, a customer's LTV is a summation discounted value. Since LTV is a discounted value, the duration of that lifetime is not relevant to the comparison. All LTVs are comparable. If customer A has an LTV of $10,000 and customer B has an LTV of $8,000, customer A is the more valuable , even if customer A's relationship spans 20 years and customer B's spans 10. The LTV is the present value of the relationship. The second point is that an LTV is a prediction. In the examples we have used in this section, our level of precision is down to the penny. This risks giving a false impression concerning how well we can predict LTV. While it may be correct to use this precision when calculating an annuity where all future cash flows are known, this is not the case with customer LTV. Customer LTV is a prediction based on statistical analysis. The level of accuracy of any statistical analysis is a function of the deviation about the mean. In short, we may be able to be close in our predictions , but very rarely, if ever, will we be able to predict with 100 percent accuracy. In addition, the prediction of an event becomes less accurate the further out in time the event occurs. Therefore, as time increases , so does the risk of our prediction being incorrect. To compensate for an increased risk over time, we make the following change to our PVIF equation: 
In this revision of the equation, we have added a risk value, R, to the denominator of the PVIF. As time, N, increases, so does the effect of the risk factor reducing the present value of the profit. We have demonstrated how this affects customer LTV in Table 12.1. Compare the present value of customers with no risk to those whose risk is 5 percent and 7 percent. Although the cash flows over the same period of time are the same, as risk increases the present value of those cash flows decrease. Table 12.1. Customer LTV with Risk Compensation | Period | Future Value | 0% Risk PVIF | 5% Risk PVIF | 7% Risk PVIF | Present Value with 0% Risk | Present Value with 5% Risk | Present Value with 7% Risk | | 1 | 100.00 | 0.9434 | 0.9009 | 0.8850 | $ | 94.34 | $ | 90.09 | $ | 88.50 | | 2 | 100.00 | 0.8900 | 0.8116 | 0.7831 | $ | 89.00 | $ | 81.16 | $ | 78.31 | | 3 | 100.00 | 0.8396 | 0.7312 | 0.6931 | $ | 83.96 | $ | 73.12 | $ | 69.31 | | 4 | 100.00 | 0.7921 | 0.6587 | 0.6133 | $ | 79.21 | $ | 65.87 | $ | 61.33 | | 5 | 100.00 | 0.7473 | 0.5935 | 0.5428 | $ | 74.73 | $ | 59.35 | $ | 54.28 | | 6 | 100.00 | 0.7050 | 0.5346 | 0.4803 | $ | 70.50 | $ | 53.46 | $ | 48.03 | | 7 | 100.00 | 0.6651 | 0.4817 | 0.4251 | $ | 66.51 | $ | 48.17 | $ | 42.51 | | | | | | Totals = | $ | 558.24 | $ | 471.22 | $ | 442.26 | Ultimately, the greater we are at risk of losing a customer, the less valuable that customer is to our organizations. Compare the LTV of the three customers described in the table. A customer with a 7 percent chance of terminating the relationship is much less valuable than a customer from whom the organization can depend on a steady revenue stream. 12.3.2 CHANGING THE ORGANIZATION'S PERSPECTIVE This brings us to the second ingredient in the IEBI/CRM solution, the organization. If we are to truly be a customer-centric organization, we must pay more than lip service to making the customer relationship the thing that drives the organization. In a very tangible way, we must change the way we do things. The question of course is how. How do we structure our organization so that the customer relationship drives what we do? How do we take all these nice platitudes and turn them into real business processes? To understand customer loyalty, we need to look at the relationship from the customer's point of view, not ours. Several years ago, I was in a meeting in which a new marketing campaign was being developed for yet another company. They came up with the brilliant idea of not trying to sell to customers any longer, but to switch to a total self-service model. The customers would simply go to the company's Web site for all their needs. Dissenters in the organization pointed out that its competitors would continue to try selling its customers products. The party line was that our vastly superior technology would drive the customers to our Web site. It was like saying "I am so attractive, everyone will simply have to date me." Well, you can guess what happened. The campaign failed miserably. Customers left in droves and the company lost market share. The obvious, and might I add extraordinarily stupid, mistake was that the company was approaching the market based on its internal needs, not on those of the customers. It wanted the world to work in a particular manner so desperately that it sat in the corner with furrowed brow, attempting to recreate the world with sheer mental force. In the end, all it got out of it was a headache and a reduced stock price. A purely Web-based service model did not meet the needs of the customers. As we said earlier in this chapter, not all products and services are adaptable to the Web. We need to understand the needs of the customers in those markets. Part of the mistake this organization made was that it believed it had a lock on the market, which it didn't. Even if it had, this would have been a poor strategy. We mustn't confuse the lack of choice with loyalty. Customers with a choice will remain loyal as long as the organization meets their needs. Customers with no choice will remain loyal only until another choice is available. When another choice is available, the exodus will be even greater from the resentment that has accumulated while there was no alternative. We have seen this happen many times in our own industry. After building control over a particular market, the hardware or software company grows fat and happy. They become less competitive and start to produce inferior products. Eventually, their complacency causes them to miss the inevitable shift in technology. While they may maintain a command over a particular market, that market becomes less and less relevant. This has happened in the shift from mainframes to minicomputers, from minicomputers to workstations, from workstations to Internet enablement. Organizations are faced with a significant challenge. If markets were monolithic, if there were little diversity between customers, meeting market demand would be simple. The unfortunate truth is that markets aren't that simple. Different customers have different needs at different times. In the auto industry, a customer's transportation needs and wants are highly dependent on many demographic characteristics working in unison . There is the obvious difference between the 30-something soccer mom and the 20-year-old mountain biking MBA student. Even within these demographics , there is a difference in transportation wants. The soccer mom from south Texas whose household income is above $100,000 may be more interested in the big, burly SUV than the mom from a New York suburb with an annual household income in the $80,000 range. Each additional demographic variable can greatly vary the predicted results. So, how does the organization meet these many different needs in an ever-changing market place? How is the organization transformed by the IEBI/CRM solution? Figure 12.4 presents the information infrastructure of a customer-driven organization. The structure reflects the organization's strategy. The strategy of the organization centers on the development and maintenance of customer relationships; the center of the information infrastructure is the IEBI/CRM system. It acts as the hub, driving and directing the other parts of the company. We can see how this figure is a more detailed view of Figure 12.3. In the earlier figure, the information flows from the customer-facing system to the IEBI/CRM system. Customer intelligence then flows to the decision maker. Figure 12.4 shows some of the many paths that the customer intelligence travels to reach the decision maker. Figure 12.4. A market-driven information architecture.  The entire process begins with the customer-facing system. The IEBI/CRM system aggregates and integrates data from the customer-facing system along with financial and external data. This data is used as the basis for our customer intelligence, which in turn drives the IEBI/CRM system. To quote John Donne, "No man is an island entire of itself; every man is a piece of the continent ." The same is true of IEBI/CRM: It is not an island entire of itself. It is part of an integrated system of applications, each of which exchanges information. In the previous section, we discussed how a customer's lifetime value to the organization is a function of profit. The values used to calculate profit and customer LTV come from two different systems: Activity-Based Costing (ABC) and financial intelligence. ABC gives us a more accurate understanding of our costs. We need to understand the advantages of ABC over the traditional GAAP (Generally Accepted Accounting Principles) method of cost accounting. As shown in Figure 12.5, GAAP reports costs along organizational structures. It is well suited to financial reporting, understanding what departments and divisions are spending. We can see specifically what we spent on marketing or procurement. Unfortunately, this type of reporting doesn't tell us too much about the cost of manufacturing or servicing an individual product. What we can't see with GAAP is what we spent on marketing and procurement for a specific product. Figure 12.5. GAAP versus ABC cost accounting.  The problem is that the cost of a product doesn't flow up organizational structures. Its costs flow across the organization. A particular product incurs costs from development, marketing, sales, manufacturing, and logistics. For example, we may manufacture watches, hundreds of different types of watches. Marketing may announce a new idea for a watch that costs $100 to produce. We then sell 1,000 of them for $120. We also have a watch that costs $90 to produce and we sell it for $100. Which of the two watches is more profitable? Well, we can't really tell from the information we have here. We discussed what it cost to manufacture, but what about the marketing cost for each product? What about the cost of different distribution channels? Marketing may have spent $20,000 on research and development for the first watch. The distribution channel for the first watch may also be more expensive than the second. GAAP is not able to provide this detailed cost analysis, but ABC can. ABC can tell us specifically the cost of a product with variations in supplier, distribution channels, and manufacturing processes. ABC considers all of these factors when calculating product costs. Figure 12.4 shows the financial intelligence system receiving the cost information from the ABC system. It combines this information with other financial data, such as revenue, to determine the profitability for specific products, customers, and customer types. This financial data is then passed to the CRM system. We have several plates spinning on very thin sticks. We discussed customer LTV, ABC, financial intelligence, and IEBI. Let us now step back and look at how these elements together drive the customer-driven organization. Figure 12.6 presents this flow of information between. Figure 12.6. Calculating customer LTV.  The first step in being a customer-driven organization is to understand the LTV of our customers. From the financial system, we extract the cost data and calculate cost object-unit cost for our products and services. The financial intelligence system combines this information with revenue to determine the profitability of each item. The IEBI/CRM system then applies data mining techniques to determine the buying patterns of the different groups of customers. This is the analytical side of IEBI/CRM. Based on these patterns, the system can project the LTV of each customer group . Using these numbers , we can then plot the value of those relationships. Figure 12.7 is an example of such a graph. Figure 12.7. Customer LTV profitability.  The x-axis of the graph represents the profitability of the customer's LTV. The y-axis is the revenue dollars generated by the customer over the life of the relationship. Note that there is a difference in the volume of revenue dollars generated by a customer and the profitability of those dollars. We can divide this graph into four basic quadrants. Quadrants 1 (low-profit, low-volume) and 3 (high-profit, high-volume) reflect what we would expect to see in the graph. Some of our most profitable customers have the highest dollar volume, while our least profitable have the lowest volume. The graph, however, shows some other interesting customer groups. We see that in quadrant 3, there are customers who, based on their volume, should be highly profitable, but aren't. These customers may have special requirements that reduce their profitability or require a great deal of service. In quadrant 2, we see just the opposite effect: highly profitable customers who have a low volume. Perhaps these customers purchase products with large margins and require little service. As we discussed in Chapter 3, data mining is the process of finding patterns hidden in the data. Once we have plotted each different group, we can mine the customer data to understand the different characteristics of the customers in each quadrant. By answering customer- related questions, we can better manage our relationships with those customers. For example, what is the difference between our low-volume, high-profit customers and our high-volume, high-profit customers? With this understanding, we can develop strategies to move every customer to quadrant 4. Notice the benefit of the customer profitability and LTV perspective. A sales-driven organization would only look at one line on this graph, the revenue volume. It would have no insight into the costs. Customers that appear to be profitable because of a high revenue volume can in fact be very costly. All the sales-driven company would see is large sales. The engineering-driven organization would have no greater insight into customer profitability. It wouldn't even look at this graph. It may even see the customers in quadrant 1 as just marvelous. These customers may purchase one, possibly two, systems and develop software that did something that is technically astounding. The engineering company would be thrilled. The problem is that they wouldn't be very profitable. After purchasing that one system, the customer would disappear. 12.3.3 PUTTING CUSTOMERS BEHIND THE WHEEL So far we have examined how we can use IEBI/CRM to better understand our customer relationships. What do we do once we have this understanding? Being customer-driven is having our customers drive the direction of the organization. In this section, we examine how we use CRM to drive the organization. Let's look at an example to see how this works. We may be a click-and-mortar company, interacting with our customers both over the Web and through local retail outlets. Our catalog contains memory cards for digital cameras and MP3 players. In doing a financial analysis, we discover that selling these products over the Internet is not as profitable as sales through our traditional outlets. Internet sales require additional packaging and handling, increasing their delivery cost. The problem is that these are very popular items. We need to decide how to reduce our cost while providing the customer with better service. Using IEBI/CRM, we can develop a 360-degree view of the customer and develop a better understanding of the dynamics of different groups of customers. Using the IEBI/CRM system, we could can look for common characteristics in customers. When we do this for the groups that purchase memory cards, we see no real distinction that is related to our problem. As we probe the data further, we see that the customers who purchase memory cards in rural areas typically do so in conjunction with other items. We see that the rural customer typically buys a memory card when he or she buys the camera or a photo-quality printer. We could speculate that rural customers, accustomed to purchasing products through mail-order or over the Internet, group their purchases for efficiency. In any event, the grouping of the items amortizes the shipping and handling cost over all the items and maintains the profitability of the memory card. On the other hand, urban customers, who typically purchase the memory card by itself, are within easy driving distance of a retail outlet. To remedy the situation, we could first suggest that urban customers who purchase the product over the Internet pick up the item at the store instead. We point out that they will receive the product much more quickly this way. If this does not reduce the number of individual memory card orders, we offer customers an incentive to either group the product with other orders or to pick up the memory card at the outlet. This example does more than address the issue of increasing the profitability of memory cards. It shows how, using profitability analysis, we can develop a more mutually beneficial relationship with our customers. The rural customers buy in volume and are more profitable. In addition to purchasing memory cards from our Web site, they typically buy multiple items at one time. We are doing well with these customers. Our strategy with our urban customers moves them from low-volume, low-profit to at least low-volume, high-profit or even possibly to high-volume, high-profit. Let us assume that for some urban customers, we succeed in getting them to pick up the memory card at the local outlet. We have increased their profitability, possibly moving them to a low-volume, high-profit customer. The campaign gives the customer a new option for interaction with our company. Their selection of this option indicates that we may be meeting some personal need. For those urban customers who choose to combine their purchases into one shipment, we have increased both their profitability and their volume. 12.3.4 THE INTERNET AND CRM The final ingredient in the IEBI/CRM solution is the Internet. If IEBI/CRM drives the entire customer-driven organization, it will obviously drive how we interact with our customers. In the Internet age, it will drive how we interact with those customers over the Internet. Earlier in the chapter, we described how we can increase customer loyalty by understanding our customers' needs. As we become more responsive to those needs, the customers become more confident in the relationship. Loyalty becomes mutually beneficial. One way to establish a sense that the company understands a customer is through personalization. For example, we may have a company that sells tools over the Internet. A customer primarily interested in home repair should have a different experience than a customer interested in woodworking. When we projected into the future and discussed a device that would deliver the perfect product for the customer, the device knew without being told what the customer wanted. A customer interested in woodworking would receive different direction than a customer interested in home repair. The device knew. Our Web sites need to get as close to this idealized environment as possible. The example with which most of us are probably familiar is Amazon.com. Amazon provides returning customers with a personalized home page. Of course, Amazon doesn't call it a home page, but refers to it as "Mary's Store" or "William's Store." This demonstrates how Amazon looks at the experience not from its point of view, but from the customer's. The customer goes to a store to make a purchase. In the case of Amazon.com, the customer's own personal store is tailored to his or her specific needs. At the very top of the page is a welcome message; this is the cyber equivalent of someone greeting you as you walk into your store. Just beneath the greeting is a link to a page of recommended reading. When recommending products, we should strive to go beyond the obvious. Whether we are recommending books or power tools, the recommendation engine should suggest to the customer things he or she may not normally expect. If we are suggesting books and the customer has rated a particular author highly, it is apparent that he or she would probably be interested in other books by the same author. In some cases, however, such a simple algorithm would get it wrong. Imagine an author such as Isaac Asimov, who has written extensively on areas ranging from science to the Bible to murder mysteries. Is the average reader really interested in that wide a variety of topics? The recommendation engine should be inventive in what it recommends to customers. Have you ever purchased a product, such as a digital camera or PDA, over the Internet only to have the Web site recommend competing products during subsequent visits ? Recently, I purchased a PDA from a Web site, and then a number of competing PDAs were recommended. I wondered, Is there something wrong with the one you sold me that I don't know about? If I buy a sliding-compound-miter saw, don't recommend additional saws. I already have one. You're not helping. Instead, think of the things that someone with a sliding-compound-miter saw might want. Why not recommend a measuring tape with a digital readout, an air hammer for finishing nails , or a level? By making the recommendations helpful, things that might not normally be considered by the customer, we demonstrate an understanding of his or her needs. The consumer begins to think of the site as a place to go to receive advice and direction. Recommendation engines can be both subtle and overt. The previous example demonstrates how a recommendation engine can be used in an overt way. We can also provide recommendations in a more subtle manner. Figure 12.8 presents a Web page with more subtle recommendations. The Web page recommends lists and other books that were of interest to other readers with similar profiles. As we can see, the extraordinarily intelligent readers who rated this book highly also rated these other books highly. Along the right side of the page are lists of books similar to the one in the center of the page. Figure 12.8. Web page with recommendation.  Our goal is to establish in the mind of the consumer a sense of loyalty, to build a feeling that customers are somehow stakeholders in the organization. Another method is to create a sense of community around the store. When I was very young and actually had hair, I had dreams of being the next Eric Clapton. I had visions of myself up there on stage, jamming with Harrison, Clapton, and the other guys in front of throngs of screaming nubile female fans. It is not at all surprising to discover that there were many of us in my little hometown with the same dream. We all gathered at a little guitar shop on the east side of town. The owner encouraged this community atmosphere. After a few years, the little shop, while still little, had enormous influence. If you were any sort of guitarist in those days, you knew Art, the owner. It was there that you met other guitarists and got advice from Art and the other musicians on how to play as well as what instruments to play. This same sense of community needs to be developed on a company's Web site. As a site-based community develops, users come to see it as more than a simple store but as a gathering place for like-minded individuals. Again, we see that Amazon has developed this sense of community within its own site. Customers review products and recommend them to other customers; discussion groups are started; customers email one another to ask opinions . Customers are drawn to the site not just for products, but for virtually free information. In the information age, this is something for nothing. When we integrate the exchange of information into the purchase process, as we have done here, we are using the Internet specifically as designed, for the exchange of information. This community approach to sales is integral to a customer-driven strategy. The community becomes another aspect of our customer relationship. As is the goal with the entire relationship, the community aspect of this relationship is mutually beneficial. Not only does the consumer benefit from the relationship, but the supplier does as well. As we monitor the discussions that occur as part of this community, we gain a better understanding of our customers. Again, look to Amazon as an example of what works. Authors are suppliers; we create a productbooksthat is consumed by our customers. The reviews provided on Amazon benefit authors in two important ways. First, when we are researching a topic for a future title, we can examine the reviews of books that already exist. These reviews can tell us where certain books have succeeded and where they might have failed. We can use this research to help shape our own work. Second, these reviews are helpful once the book has been published. We can get a feeling for what our readers did and did not like about our book. When an email address is provided, we can contact that reader directly to probe their comments in more detail. This type of feedback is invaluable to an author. Most of what we have discussed at this point is reactive. The consumer takes the initial step in the process, and the organization in turn responds. We can also be more proactive in how we deal with our customers. When consumers purchase a product, whether through a traditional outlet or over the Internet, we can simply ask for their email address and permission to send them particular types of information. Consumer can be given the option of receiving news, promotional items, tips and techniques, or industry updates. For example, I finally go out and buy that sliding-compound-miter saw I have been eyeing for the past 6 months. When I purchase the item, I might be asked if I would like to receive a monthly newsletter on home repair or promotional items such as discount coupons on saw blades. Maybe I will receive copies of The Baseboard Journal every 6 weeks. Once I give permission, I have opened a dialog with the company. It can now provide information specific to the product I purchased or even general industry information. It is allowed to proactively communicate with me, the consumer. Through this communication, the company continues to establish a feeling that it is knowledgeable about my needs and there to meet them. The company builds in my mind not only trust, but an understanding that it is customer focused. It is there to support my needs to our mutual benefit. | 
