Global Best-in-Class Lessons The Overlooked Relationship Between Data Quality, CRM, Marketing Automation and BI

Amazing Lessons from the Global Fortune 200 – The Powerful Link between Data Quality, CRM, Marketing Automation, Business Intelligence and Profit Optimization

Results for All Enterprises in ALL Industries!

By

Robert S. Orf CEO, DataMentors, Inc. [email protected]

Van Mayros Global Knowledge Management Author, Speaker and Consultant [email protected] [email protected]

Global Lesson Series Data Management White Papers Lesson 1.1 White Paper Briefing

Three Important Caveats

Data Quality Plays an Extremely Important Role In

1. The Future of Knowledge Creation and Utilization. 2. Helping any Enterprise Leverage Data into Information. 3. Optimizing Revenue and Profitability.

Two Important Baselines

1. Enterprises in 2004-2007 will prioritize Knowledge Management and Customer Relationship Management (CRM) solutions that include marketing automation based technologies to dramatically improve performance, opportunity and predictive metrics. 2. Enterprises are just beginning to understand the many benefits of diagnosing bad data, cleaning the entire enterprise data model and creating synchronization between clean data and metadata.

Table of Contents PAGE

The Role of Data Quality And Management in Creating World-Class Marketing, Sales And Planning Solutions That Dramatically Improve Enterprise Profitability ------4

Introduction – Clean Data And Revenue Success ------4

Origins of Profit Reengineering ------4

The Link between Quality Data, CRM and Profitability ------4

Who Is Eugene Foster? ------5

Page 2 Creating Negative and Positive Goodwill ------5

MGM Mirage and Mandalay Bay Impact of Clean Data ------6

Clean Data and Decision Support Success ------7

Clean Data Models in CRM ------8

The Future of CRM and Knowledge Management Deliverables ------8

Transforming Data into Information Into Knowledge into Profits ------9

Data Quality/Data Management And the CRM Profitability Model ------10

Business Intelligence and Knowledge Applications ------11

Final Remarks – The Link Between Data Quality, Data Management and Customer Relationship Management ------12

Summary ------12

The Enterprise Knowledge and Business Intelligence acronyms we will use:

KM Knowledge Management CRM Customer Relationship Management SFA Sales Force Automation BI Business Intelligence

Page 3 THE ROLE OF DATA QUALITY AND KNOWLEDGE MANAGEMENT IN CREATING WORLD CLASS MARKETING, SALES AND CUSTOMER SOLUTIONS

INTRODUCTION

Can a simple White Paper help your organization improve revenues and profits? Is it possible for a White Paper to replace a consultancy hired to improve revenue or customer relationship management? Does the secret to profit optimization lie in the careful management of DATA? Or is the processes involved in transitioning DATA TO INFORMATION TO KNOWLEDGE TO MANAGER UTILIZATION, the MOST IMPORTANT business reengineering process of the 2004-2010 timeframe?

DataMentors will soon be releasing a series of “LESSONS” in the coming months outlining the best in class results from the Marketing Information Technology Forum and numerous other well respected knowledge research groups. The Forum was a prestigious Consortium of high level knowledge executives from most of the Fortune 200. These executives met three times per year, for over a ten year period, to examine and study best practices as they pertain to such knowledge based solutions and processes commonly referred to as Customer Relationship Management (CRM), Marketing Information Systems (MKIS), Sales Force Automation (SFA), and Business Intelligence (BI.) If you think you have heard all you can about these important technologies, stay tuned. The best is yet to come!

ORIGINS OF PROFIT REENGINEERING

Recently, several well respected industry research organizations including The Meta Group and The Gartner Group, presented important conclusions regarding the future determinants of CRM and Knowledge Based Technology Vendors success and failure. In brief, this research stated Knowledge Based Solutions (CRM, SFA, BI) growth in the next several years will be based on those vendors who successfully incorporate Data Quality, Data Management and Marketing Automation/Intelligence into their overall Delivery Solution/Package. For example, CRM Sales successes in 2004-2010 will be based on the ability of vendors to link their existing products and services into a broader delivery perspective which will include “clean” and “accurate” customer, prospect and market operations data. CRM customers today, and especially tomorrow, want CRM to include a detailed look at Customers/Prospects from a TOTAL Market/Product/Channel Potential perspective. This means looking at a cleansed customer database across ALL lines of business, markets, channels, products, geographical segments, competitors and technology. Sounds logical doesn’t it? The link between Data Quality, Data Management and Profitability is far more important than previously thought.

THE LINK BETWEEN QUALITY DATA, CRM AND PROFITABILITY

The absolute value of accurate and refreshed data is currently being studied by several dozen organizations, including DataMentors. WHAT WE KNOW… Inaccurate and low-quality data costs U.S. businesses $611 BILLION dollars each year according to the Data Warehousing Institute. Examples of these costs will be offered shortly. Let’s begin with some rather obvious illustrations. Loss results vary but often these losses result from activities/programs such as low quality marketing or sales campaigns, direct mailings, associated staff overhead, etc. Loss is usually associated with targeted prospects who no longer reside at a particular address, or customer campaigns that end up sending the same customer 2-10 of the same promotional

Page 4 packages. Indeed, more injurious than the unnecessary printing, postage and staffing costs is the slow but steady erosion of the enterprise’s creditability among customers and prospects. This is easy to understand. Now let’s look at some examples that are less obvious.

Lower Return on Investment (ROI) values are often caused by poor decisions due to inaccurate information, or low quality Data. “Isn’t it interesting,” says Tim Waggoner, CTO of Group 1 Software, “that a company will spend $10 Million on CRM, but totally ignore the data quality behind it?” As data quality and management is the cornerstone of any CRM or KM success, ignoring it is simply not an option. Want or need proof? Experts suggest that over 2% of an enterprise’s customer master file contains records that become obsolete every month as their customers move, die, divorce, marry, etc. Given this fact, it easy to see how the all important Customer Master File, which is the cornerstone of CRM, quickly degenerates over time.

WHO IS EUGENE FOSTER? IS HE OUR CUSTOMER? IS HE A GOOD CUSTOMER?

For example, are Eugene W. Foster and Gene Foster the same person? How many other records in the Customer Master contain similar disparities? The answer is approximately 25-27%. Imagine creating a direct mail campaign with a built in error rate of 27%? Imagine the goodwill you would lose sending the same Mr. Foster two or more of the same promotional materials? Imagine the impact of sending Mr. Foster one offer at 5% and another at 7.5%?

Here is the LINK: According to the Gartner Group, in 2004, businesses are expected to manage 30 times more data than in 2000. Also, through 2006, greater than 50% of Business Intelligence (BI), CRM and Enterprise Resource Planning investments will suffer limited user acceptance despite the cost and effort necessary to implement them. Finally, these same companies will continue to invest heavily in Customer Relationship Management (CRM) spending a staggering $206 billion on direct marketing media alone. Are we to assume that 25% of the $206B is destined to failure due to BAD DATA? Is this part of the $611B? Yes.

CREATING NEGATIVE GOODWILL

Similar to the previous example, sending duplicate mailings can be both expensive and embarrassing. For example, let’s assume a typical Bank maintains a customer database of 934,000 records. After removing the “dirty data” their number of records dropped to 905,000. In this instance, this reduction of 29,000 records yields a short-term savings of $43,500 per mailing, assuming the campaign costs were $1.50/pc. As this local bank had four quarterly mailings per year, they saved $174,000! What would this bank do with an extra $174,000 in their marketing budget?

Simply stated, the typical consumer of today wants to receive RELEVANT content from companies he/she is familiar and has agreed to receive such information. From the business perspective, the company wants to demonstrate to the executive team where the organization’s best market, customer, product and competitor opportunities will be found and how to optimize these opportunities with the least resources. More importantly, he/she wants to focus marketing resources on current customers who are “underperforming” relative to their potential in a rising economy. The focus of most businesses today is simple -- Increase sales with the least amount of expense. To accomplish this, give the sales force the best tools available to get to the right customer, with the right product, at the right time.

Page 5 MGM MIRAGE AND MANDALAY BAY’S $37,462,500 SAVINGS PLAN

Recently, MGM Mirage and Mandalay Bay agreed in principle to a $7.9bn merger. This merger will essentially create an ownership of approximately half the hotel rooms on the Las Vegas Strip. MGM Mirage and Mandalay Bay will collectively operate 23 casinos. The stated goal of the merger is to create a world class convention and exhibition business spanning all market segments from high end to modest. Their stated objective is to aggressively drive business conventions to each property depending on each customer’s specific market segment. Let’s assume this merger is successful and suddenly this new hotel giant is faced with a rather daunting task – combine IT resources, including the customer and prospect master databases!

Here is their task. MGM Mirage/Mandalay will target over half of the 90 million households and most of the approximately 5 million large to mid sized businesses in the US alone. In addition to this collection of “external data,” the new company must integrate their collective customer and related market databases.

This scenario is interesting for many reasons. First, the new company must successfully integrate several sets of disparate data. Second, they must integrate external information into these different sets of disparate data. Third, they must create a common platform from which to build new marketing and sales programs to achieve their stated goal of convention and exhibition business optimization. Fourth, they must create a point and click portal for users to easily access this information. Finally, they must create custom analytics and applications to help users evolve the “common data” into “actionable knowledge.”

Now just imagine, with all that must be done, the new combined company forgets to clean their existing data! Here is a quick compilation of the impact of such an oversight:

Base Data Profile

90 million households Approximately 50% gamble This represents approximately 45 million households Many of these households include business managers and executives who will make or influence decisions on conventions attendance or exhibitions.

14,000,000 businesses Approximately 70% are small businesses, while 30% represent larger and mid size businesses Therefore, 4,200,000 businesses represent viable conference and exhibiting prospects

If we examine the total market and incorporate our 25% rule that all households/businesses will have changes in their record due to moving/relocating, growing, dieing, divorcing, marrying, etc., the impact will begin to evolve. This error rate rule results in 11,250,000 households who will have different mailing addresses each year. If MGM/Mandalay mailed or marketed to just a third of the available households/businesses each year, their error rate will include over 3,746,250 records, or households. If each record costs $10 in actual marketing costs, MGM/Mandalay would save over $37,462,500 in total marketing costs each year.

Even more significant is the fact that each of these individuals represents lost opportunity revenue. Assuming each of the 11,250,000 households would send one member to Las Vegas once during the year, the impact would be in the billions of dollars. However, if only 5% of the

Page 6 11,250,000 would actually come to Las Vegas, this still represents over a half million visitors each year and if each gambled and lost $150 each, Las Vegas just lost $84,375,000 in lost gambling revenue. Statistically, MGM/Mandalay would own half of this loss, or $42,187,500! This does not even factor in the revenues from their hotel, meals and entertainment. Yes, clean data is important!

CLEAN DATA AND DECISION SUPPORT SUCCESS

Isn’t it interesting how most businesses perceive their current knowledge gap? Many, if not most CRM decision makers, call on CRM vendors because although they collect “all the data they will ever need,” they still find it difficult to grow their markets and businesses. These same executives also understand their organization lacks real knowledge about markets, customers, prospects, products, geo area trends, socioeconomic impacts, competitors, etc. Compounding the issues for most managers is the general belief there is plenty of industry/market data available from external sources to supplement what data they may not have. Still, to date, the typical IT group has been unsuccessful in delivering to management, the information (especially knowledge) necessary for “optimizing” marketing and sales investments.

So why does this Data-To-Knowledge-ROI Gap still exist? The fault does NOT lie with just the IT side of the enterprise. Marketing executives and managers have historically been poor in articulating their specific needs to both the IT group and the vendor. Even more significant is the lack of attention IT and Marketing Executives pay to Data Quality. Thus, if we combine the lack of communication between Marketing, Sales and IT, AND, the fact that each organization’s customer database contains a roughly 25% error rate, we have the recipe for failure. The trend of enterprises creating knowledge based solutions where a user seems unwilling, or unable, to utilize existing “bad data” is fundamentally sabotaging the majority of CRM or BI efforts around the world!

THEREFORE, THE SOLUTION is finding the CRM or Knowledge Vendor who will link “prioritized” Marketing Operations Data/Information/Knowledge into/from a comprehensive and robust “Clean Data Model.” This presumes the CRM vendor(s) understands ALL the components of a world class marketing and sales data model. To date, THIS IS NOT AN ACCURATE ASSESSMENT OF THE KNOWLEDGE MANAGEMENT MARKET! For example, a robust data model would offer each user the ability to link CRM to such marketing automation areas as:

1. Market Potential, Penetration and Projection (tools and applications) 2. Customer Potential, Penetration and Projection (tools and applications) 3. Prospect Potential and Projection (tools and intelligence applications) 4. Revenue Opportunities Identification (matrices, models and optimization tools) 5. Competitor SWOT (Strengths/Weaknesses/Opportunities/Threats) analysis, applications and early warning systems 6. Market trends and forecasts’ (business, socioeconomic, demographic, psychographic and lifestyle) impact on current and future products and product portfolios 7. Profit and market optimization front office suites and portals

It is clear from our research, and related research from other qualified institutions, the vast majority of CRM vendors will continue to receive calls from global customers and prospects asking for Marketing and Sales Automation linkages to CRM and a CLEAN DATA MODEL. Though their IT managers have been trying to put together “executive information portals” (the latest IT vendor-inspired buzz) for their managers, they have little understanding of what data

Page 7 should be in the CRM-BI-KM Data Model or Portal, and in what format this data should be displayed so as to provide “actionable information.”

CLEAN DATA MODELS (DATAMENTORS ROLE) IN CRM AND MARKETING AUTOMATION SUCCESS

This paper introduces how the enterprise of today, and tomorrow, will construct the CRM, and supporting cleansed Data Model, of the future. We offer examples of how to assess data both internally and externally in conjunction with the construction of a short-term roadmap to synthesize this new data architecture/model consistent with CRM and Knowledge Management best practices. We also introduce benchmarks for supporting marketing’s requirements linkages with CRM without causing any undue stress on the main mission of the IT department. In addition, we outline why clean data is so important to CRM and/or KM success. Finally, we recommend utilization of some exciting new event processing ‘middleware’ technology that has been developed to pull data from existing internal and external sources to create clean and synchronized data structures that will dramatically improve current IT operations and CREATE A BENCHMARK FOR REDUCING COSTS AND INCREASING CRM ROI.

The reader should be aware that indeed by most software/CRM metrics today, there is now a ‘magic new box’ where the Enterprise Marketing-Sales-CRM Operations Portfolio Management Solution is upon us leveraging cleansed data, new software technologies and adding extraordinary business intelligence and applications on the front end. Our perspectives are derived in part from our association with the Marketing Information Technology Forum. The Forum was a Fortune 200 Think Tank, or “Experts Consortium,” of the top marketing and information executives from around the world. Each Forum addressed a wide range of issues including future software issues and expectations. A list of participants is available upon request. Many of the insights in this report originate from this extraordinary group of companies and top executives best practice.

THE FUTURE OF CRM AND KNOWLEDGE MANAGEMENT DELIVERABLES

Although every client is unique, we find many similarities in how ALL enterprises manage markets, customers, products, etc. If we understand the complex issues of a particular client, along with benchmarks for how others have solved these same issues, we can custom design an intellectual property transfer that will significantly impact the profitability of our client. Inherent in each of the issues presented below, is a set of solutions that have been successfully utilized by companies across industry, country and/or time period. It is our role to continue to research and review best in breed so that we can always present to our clients, the optimum set of solutions for each issue.

Before continuing, we realize our brief introduction into real life success must in some way compel you. In our view, the future of CRM successes, marketing automation successes and/or BI successes, all rest with the delivery of value. Our vision of the CRM future will be based on the following:

1. Expanding the User’s Knowledge Base. The Knowledge (CRM, BI, KM or SFA) Vendor must understand the issues/problems in far greater depth than the user, or organization. If presented five areas of issues, the Knowledge Vendor should be able to make you think about five additional ways of thinking about the same issue. Vendors must help each user get “out of the box” and ask the right questions or help them articulate their needs in a more precise manner.

Page 8 2. Creating the Optimal Data Architecture. The future of successful intellectual property transfer includes attacking the very core of the knowledge foundation of an enterprise – the Data Model. Most data models or architecture’s, contain much of the same data mix – customer history, sales history, product history, ship to information, etc. Unfortunately, this is a restrictive look at “where the enterprise has been.” The Knowledge Enterprise is demanding the vendor help them assess where the enterprise should be going. Therefore, today’s data models will include far greater external information such as customer (B2B) firmgraphics/demographics, business growth formulations, household demographics (B2C), lifestyles, socio-economics, industry trends and statistics, macro economic trends, industry growth statistics, customer’s key account data, etc. This external based data is critical in predicting future opportunities and threats. 3. Evolving Data into Information and then to Knowledge. Every company has data. If you ask the head of most Fortune 500 marketing departments if the company has sufficient data, they will say YES! Only until you begin comparing the enterprise’s data model to best in class, will this same executive begin to question if they really have the “right kind and levels of data”. It gets worse. Next, ask if his/her group in sales or marketing is receiving sufficient information/decision support to execute short and long range commitments, plans and strategic objectives. Many executives would say -- knowing who the customers is, where they live/work and how much they purchase is sufficient. To fully understand where the enterprise should be investing their resources to optimize markets, most executives want to know why and why not, when, how often, what else, potential, etc. Knowing when they purchased a product, where and how much is information. Knowing why they purchased a specific product, why they will purchase more, when, where, how much and what related products/services they would also be interested in is knowledge.

TRANSFORMING DATA INTO INFORMATION INTO KNOWLEDGE INTO PROFIT

Most enterprises primary objective is to offer products and services that are perceived to be highly differentiated. In pursuit of this objective, enterprises often identify the profit model that will carry them for years -- Data to Knowledge to Profits will become the cornerstone of successful branding, company imaging, marketing plan execution and profitability. The pages to follow outline the basic foundation of this transformation.

DATA. Data is merely a record of the moment. For example, a customer name, phone, age and address are data.

INFORMATION. Information is evolved from data when the collection of data begins to offer multiple views that tell a story of markets, customers or industries.

KNOWLEDGE. Knowledge results when information becomes so compelling that the user begins to see current or future trends/projections that correlate to specific profit opportunities at the speed of thought.

For example, P&G sells among other items – diapers.

Data Example: The fact that they sold $15MM diaper product items in the greater Atlanta region to the Walgreen’s account in quarter 4 (01) is data.

Page 9 Information Example: The fact that the Atlanta Walgreen’s sales were down 28% over the previous quarter is information.

Knowledge Example: Results when we can see in a quick composite view, or “dashboard,” that in the same period Walgreen’s had:

A minor labor disagreement in the same quarter, The overall retail sales in the region were also down 22%, The 9.11 tragedy in NY took place in the last part of Q3, Raw material production declined, Transportation of product declined 30%, P&G reported a 25% diaper production slowdown during the same period.

4. The optimal Delivery of Knowledge. How the enterprise delivers knowledge to each user is the next key to success. Knowledge must be created and disseminated based on user needs and priorities. This created base of important business intelligence must be made available in such a way that requires no training, no guess work – just a point and click of the mouse! Thankfully, companies like DataMentors, IBM, Info USA and Seisint are working everyday to create easy to use enterprise portals, gateways, front office suites, market pattern recognition tools, customer triggers, etc., making this task of optimizing markets and customer relationships easier for the user.

DATA QUALITY/DATA MANAGEMENT AND THE CRM PROFITABILITY MODEL

For over 15 years, this White Paper author (Mayros) has traveled throughout the world introducing best practice results in CRM, KM and BI. One of the practices which numerous global enterprises utilize as part of their overall CRM Tool Chest is the CRM CUSTOMER PROFITABILITY MODEL. This is a 50-step checklist, or action plan, for creating the ultimate, or optimum, customer profitability model. Here is a sample using only 10 of the 50 Steps:

Step 1. Identify every customer and include EVERYTHING known about that customer in the record. The enterprise should know as much about this customer as if they were our best friend. Step 2. What is our TOTAL customer Universe for each customer and market segment? Step 3. What percentages of customers conduct business with more than one line of business? Which Lines of Business? Which Customers? Which Geographical Locations? Step 4. Who are BEST customers and why? Segment these Best Customers into a Top 20% Segment. A Top 21-40% Segment. A Top 41-60% Segment and so on. Step 5. Which of these customers in the Top 20% have purchased certain products or services in the past 1-3 years? (For example, a Bank would have the following segments – Auto Loans/Commercial, Loans/Real Estate, Loans/Home Equity, Loans/Home Improvement, Loans/Debt, Loans/Mortgage, Loans/Bus, Checking/Personal, Checking/Bus, Savings/Personal, Savings/CD, Money Market, Retirement Funds/ etc.) Step 6. Of the customers in the Top 40% Revenue Base, which of these customers work in high growth industry segments? Reside in High Growth Demographic Areas? Reside in High Growth Socio Economic Areas? Reside in High Income Areas? Reside in areas of Strong Business Establishment Growth? Are employed by companies with strong growth? Step 7. Which of the customers above fall into at least 3 categories above? 4 Categories? 5 Categories? Etc. Step 8. From above, which of these customers is doing business with one or more Business Units? Step 9. From above, which customers have purchased multiple products from us?

Page 10 Step 10. From above, which customers have the following classifications:

A. Reside in a Home valued at greater than $XXXX. B. Resides in Households with children between the ages of 10-17? Have Household Incomes of $XXXXX or more? C. Resides in Households where the following lifestyles are present ----- XXXX? D. Resides in Households who read the following magazines --- XXXXX? E. Resides in Households with the following auto types? F. Resides in Households with the following investment profiles – XXXXX? G. Resides in Households where the following catalogs were purchased in the past 36 months --- XXXXX? ETC

The key here is the Company (The Bank in this instance) would continue to build a customer Data Repository that would ADD important value to each customer record over the next several months until ALL 50 points where completed. When complete, the Bank would have a world class CUSTOMER DATABASE or Customer Metadata Model capable of supporting ANY CRM process requirement! This new data model would be capable of creating ANY type, or level, of customer assessment the bank would ever need. Here are a few samples of the types of analyses or applications we would recommend:

BUSINESS INTELLIGENCE AND KNOWLEDGE APPLICATIONS

Business Intelligence outsourcing success, whether it is a CRM project, a KM project, SFA project and/or BI project, is based in part on the following components of revenue/profit optimization and cost containment benchmarking. Here are a few samples of how global enterprises prioritize their business intelligence:

• Trends and Projects Customer Revenue and Profit Potential, Penetration and Projection • Trends and Projects Customer Lifetime Values across all lines of business, product, markets, geography and industry • Projects where marketing should allocate resources to optimize growth --by geography, markets, industries, products, channels and key accounts • Projects where company should allocate resources to offset or take advantage of general and/or specific geographical socioeconomic shifts and changes • Projects where marketing and sales should focus their collective resources and strategies to optimize key account opportunities across all lines of business, customers, channels, geography, products and markets • Offers geo and specific customer, and customer segment modeling, for isolating customer, prospect and market segment growth opportunities • Directs executive management to both quantitative and qualitative proactive market and customer opportunities • Identifies optimum price, profit and resource allocations for each product, customer segment, market segment and industry segment • Focus is generating revenues and profits and not just counting it!

• Measures efficiency indices – Performance Metrics or “actuals”, versus some measurement of actual potential • Identifies customer and key account lifetime value projections and offers contrasting trends to relative penetration levels to date

Page 11 • Offers sales rep and sales management executives, real time customer, prospect and market opportunity metrics, dashboards and easy access portals • Measures key accounts “customers” and/or markets growth expectations and correlates to company sales opportunities by actual market growth trends

• Over 50 additional ROI Benchmark Metrics Used!

Additional KM Tools to Consider:

• Pre built Analytics based on user priority, best practice standards and ROI value • Custom and packaged Best Practice User Analytics, Algorithms, Business Rules, Applications, Models, Data Mining – ALL corresponding to a precise best practice based Geneva Data Model and Support Architecture • Predictive proactive alerts and Market, Customer, Competitor, Industry and Geo Area “Triggers” -- Identifying significant events, trends, projections impacting company revenues, profits, products, customers, prospects, markets, etc. • Integrated CRM-KM-SFA analytics and front office suite and portal • Executive Boardroom Market Analyzer – Historical Impact Correlation and Projection Index – correlates hundreds of market trends and forecasts to specific product, customer, market segment, industry, geo area revenue and profit projection • Executive Marketing Analyzer – same as above but focuses on market and marketing impact trends, projections and detailed forecasts of business conditions impact on specific customers, markets, products, geo areas, territories, etc., performance

• Over 550 ADDITIONAL Analytic Metrics ARE available!

FINAL REMARKS ON THE LINK BETWEEN DATA QUALITY, DATA MANAGEMENT AND CUSTOMER RELATIONSHIP MANAGEMENT

This White Paper has introduced numerous examples of how the Enterprise (a Bank in this instance) creates and utilizes quality customer and market data. Imagine if 25% of the data detailing the top 20% of customers was “Bad Data?” The impact would be profound. Further imagine if the Customer Database contained errors in the linkages between Mr. Eugene Foster and his demographic, lifestyle and financial profile? This would imply that every single marketing or sales communication with Mr. Foster would likely offer products or services that would have little or no interest to this gentleman. No matter how adept this marketing or sales group, the results would never be positive from any metric or benchmark.

SUMMARY

The goal is simple. Find the ultimate customer DATA MANAGEMENT SOLUTION that supports all the knowledge needs of the enterprise presented earlier in this Brief. Your goal is to create a clean, comprehensive customer database with custom best practices analytics that will optimize profitability.

This White Paper briefing has illustrated several examples of how to present knowledge to every level of the entire marketing, sales, IT and/or business planning/operations groups. We also presented the importance of DATA QUALITY AND DATA MANAGEMENT in this scenario. The solution samples presented represent just a small sample of the total needs of the enterprise. Before the enterprise cleans data, they should understand the significance of the cleansing and how clean data will ultimately be used. The examples go on and on, but the point should be

Page 12 clear; having the ability to reach out to customers in a professional manner and to accurately identify their wants and needs isn’t just desirable, it is a requirement for all businesses. Targeting the right consumer or household or business at the right time, place, or channel with the right message or content, is critical to profit optimization. In fact, it is the basis of the profit optimization model. If customers have favorable experiences, they are likely to remain loyal customers. Loyal customers attract other customers for the enterprise. The cycle keeps repeating itself.

Page 13 DataMentors, Inc. Data solutions, clean and simple. www.datamentors.com

13153 N. Dale Mabry Suite 100 Tampa, FL 33618 813-960-7800

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