To conduct direct marketing, marketers must know their customers.16 And to do that, they must collect information and store it in a database from which to conduct database marketing. A customer database is an organized collection of comprehensive information about individual customers or prospects that is current, accessible, and actionable for lead generation, lead qualification, sale of a product or service, or maintenance of customer relationships. Database marketing is the process of building, maintaining, and using customer databases and other databases (of products, suppliers, or resellers) to contact, transact, and build customer relationships.
Chapter 3 reviewed “Big Data” and the analysis of massive data sets. Here we consider some additional issues in building customer databases and conducting database marketing.
1. CUSTOMER DATABASES
Many companies confuse a customer mailing list with a customer database. A customer mailing list is simply a set of names, addresses, and telephone numbers. A customer electronic mailing or e-mail list may literally be just names and e-mail addresses. A customer database, however, contains much more information, accumulated through customer transactions, registration information, telephone queries, cookies, and every customer contact. Ideally, a customer database also contains the consumer’s past purchases, demographics (age, income, family members, birthdays), psychographics (activities, interests, and opinions), mediagraphics (preferred media), and other useful information.
A typical business database contains business customers’ past purchases; past volumes, prices, and profits; buyer team members’ names (and ages, birthdays, hobbies, and favorite foods); status of current contracts; the supplier’s estimated share of the customer’s business; competitive suppliers; assessment of competitive strengths and weaknesses in selling and servicing the account; and relevant customer buying practices, patterns, and policies. A Latin American unit of the Swiss pharmaceutical firm Novartis keeps data on 100,000 of Argentina’s farmers, knows their crop protection chemical purchases, groups them by value, and treats each group differently.
2. DATA WAREHOUSES AND DATA MINING
Savvy companies capture information every time a customer contacts any of their departments, whether via purchase, a service call, an online query, or a mail-in rebate card.17 Banks and credit card companies, telephone companies, catalog marketers, and many other companies have a great deal of information about their customers, including transaction history and enhanced data on age, family size, income, and other demographics.
These data are collected by the company’s contact center and organized into a data warehouse where marketers can capture, query, and analyze them to draw inferences about an individual customer’s needs and responses. Customer service reps inside the company can respond to customer inquiries based on a complete picture of the customer relationship, and customized marketing activities can be directed to individual customers. Some firms provide specialized help to support database marketing.18
DUNNHUMBY British research firm Dunnhumby has increased the profitability of retailers and other firms by gleaning insights from their loyalty program data and credit card transactions. The firm has helped British supermarket giant Tesco manage every aspect of its business: creating new shop formats, arranging store layouts, developing private label products, and tailoring coupons and special discounts to its loyalty card shoppers. Tesco decided against dropping a poor-selling type of bread after Dunnhumby’s analysis revealed it was a “destination product” for a loyal cohort that would shop elsewhere if it disappeared. U.S. clients of Dunnhumby have included Coca-Cola, Kroger, Macy’s, and Home Depot. Based on data from 350 million people in 28 countries, Dunnhumby’s insights have aided decisions about product range, availability, space planning, and new-product innovations. For a major European catalog company, Dunnhumby found that not only did shoppers with different body types prefer different clothing styles, they also shopped at different times of the year: Slimmer consumers tended to buy early in a new season, whereas larger folks tended to take fewer risks and wait until later in the season to see which styles proved popular.
Through data mining, marketing statisticians can extract from the mass of data useful information about individuals, trends, and segments. Data mining uses sophisticated statistical and mathematical techniques such as cluster analysis, automatic interaction detection, predictive modeling, and neural networking.
Some observers believe a proprietary database can provide a company with a significant competitive advantage.19 In general, companies can use their databases in five ways:
- To identify prospects—Many companies generate sales leads by advertising their product or service and including a response feature, such as a link to a home page, a business reply card, or a toll-free phone number, and building a database from customer responses. The company sorts through the database to identify the best prospects, then contacts them by mail, e-mail, or phone to try to convert them into customers.
- To decide which customers should receive a particular offer—Companies interested in selling, up-selling, and cross-selling set up criteria describing the ideal target customer for a particular offer. Then they search their customer databases for those who most closely resemble the ideal. By noting response rates, a company can improve its targeting precision. Following a sale, it can set up an automatic sequence of activities: One week later e-mail a thank-you note; five weeks later e-mail a new offer; 10 weeks later (if the customer has not responded) e-mail an offer of a special discount.
- To deepen customer loyalty—Companies can build interest and enthusiasm by remembering customer preferences and sending appropriate gifts, discount coupons, and interesting reading material.
- To reactivate customer purchases—Automatic mailing programs (automatic marketing) can send out birthday or anniversary cards, holiday shopping reminders, or off-season promotions. The database can help the company make attractive or timely offers.
- To avoid serious customer mistakes—A major bank confessed to a number of mistakes it had made by not using its customer database well. In one case, the bank charged a customer a penalty for late payment on his mortgage, failing to note he headed a company that was a major depositor in this bank. The customer quit the bank. In a second case, two different staff members of the bank phoned the same mortgage customer offering a home equity loan at different prices. Neither knew the other had made the call. In a third case, the bank gave a premium customer only standard service in another country.
Tesco uses insights gained from a massive customer data base to help make all kinds of business and marketing decisions.
3. THE DOWNSIDE OF DATABASE MARKETING
Database marketing is most frequently used by business marketers and service providers that routinely collect masses of customer data, like hotels, banks, airlines, and insurance, credit card, and phone companies. Other types of companies that invest in database marketing are those that favor cross-selling and up-selling (such as GE and Amazon.com) or whose customers have highly differentiated needs and are of highly differentiated value to the company. Although packaged-goods retailers and consumer packaged-goods companies use database marketing less frequently, many (such as Kraft, Quaker Oats, Ralston Purina, and Nabisco) are building databases for certain brands.
Having covered the upside of database marketing, we also need to cover the downside. Five main problems can prevent a firm from effectively using database marketing.
- Some situations are just not conducive to database marketing. Building a customer database may not be worthwhile when: (1) the product is a once-in-a-lifetime purchase (a grand piano); (2) customers show little loyalty to a brand (there is a lot of customer churn); (3) the unit sale is very small (a candy bar) so customer lifetime value is low; (4) the cost of gathering information is too high; and (5) there is no direct contact between the seller and ultimate buyer.
- Building and maintaining a customer database require a large investment. Computer hardware, database software, analytical programs, communication links, and skilled staff can be costly. It’s difficult to collect the right data, especially to capture all the occasions of company interaction with individual customers. Deloitte Consulting found 70 percent of firms experienced little or no improvement from implementing customer relationship management (CRM) because the system was poorly designed, it became too expensive, users didn’t make much use of it or report much benefit, and collaborators ignored it. Sometimes companies mistakenly concentrate on customer contact processes without making corresponding changes in internal structures and systems.20
- Employees may resist becoming customer-oriented and using the available information. Employees find it far easier to carry on traditional transaction marketing than to practice CRM. Effective database marketing requires managing and training employees as well as dealers and suppliers.
- Not all customers want a relationship with the company. Some may resent knowing the company has collected that much personal information about them. Online companies should explain their privacy policies and give consumers the right not to have their information stored. European countries do not look favorably on database marketing and are protective of consumers’ private information. The European Union passed a law handicapping the growth of database marketing in its 28 member countries.
- The assumptions behind CRM may not always hold true.21 High-volume customers often know their value to a company and can leverage it to extract premium service and/or price discounts, so it may not cost the firm less to serve them. Loyal customers may also be jealous of attention lavished on other customers. When eBay began to chase big corporate customers such as IBM, Disney, and Sears, some mom-and-pop businesses that helped build the brand felt abandoned.22 Loyal customers also may not necessarily be the best ambassadors for the brand. One study found those who scored high on behavioral loyalty and bought a lot of a company’s products were less active word-of-mouth marketers than customers who scored high on attitudinal loyalty and expressed greater commitment to the firm.23
When it works, a data warehouse yields more than it costs, but the data must be in good condition, and the discovered relationships must be valid and acceptable to consumers.
Source: Kotler Philip T., Keller Kevin Lane (2015), Marketing Management, Pearson; 15th Edition.