Optimal Database Marketing Drozdenko & Drake,

2 Chapter 3 Defining Customer Data Requirements

Optimal Database Marketing Drozdenko & Drake, 2002 Chapter Objectives Examine the types of data needed to achieve marketing objectives. Review internal and external data sources. Examine the characteristics of various external databases. Review case examples

Optimal Database Marketing Drozdenko & Drake, Database Development Steps Determine the data requirements needed to meet the marketing objective Establish guidelines for database maintenance and program coding Evaluate the database structure, including hardware/software requirements Determine whether the database will be built and maintained inside the organization or outsourced

Optimal Database Marketing Drozdenko & Drake, Data Needs Determination Database development begins by determining the types of data attributes (fields) required to support the marketing objectives. The amount of data residing on a database can vary greatly from company to company depending on needs and how the database will be used to meet the marketing objectives.

Optimal Database Marketing Drozdenko & Drake, Types of Databases Fulfillment – for ordering, shipping and billing. Marketing – history of customer transactions and customer characteristics. Prospecting – contains non-customers, sometimes used for ‘cloning,’ once orders are placed name moves to marketing and fulfillment databases.

Optimal Database Marketing Drozdenko & Drake, Fulfillment Data Any direct marketer currently taking and fulfilling orders of any kind must have, at the very least, a fulfillment database or file. In all likelihood, this file is being managed and maintained by an outside vendor. The sole purpose of this file is to maintain information on customers regarding their order, product shipment and billing information and status. Fulfillment files do not maintain historical data and therefore cannot be used to conduct analyses of past customer purchase behavior.

Optimal Database Marketing Drozdenko & Drake, Marketing Databases Marketing databases are structured for efficiency and does maintain a history of all customer transactions over time. These databases are derived from the customer information sitting on a fulfillment database. How often the fulfillment data feeds the marketing database depends on the enterprise’s needs. Marketing databases allow direct marketers to more easily obtain quick counts on active customers, select names for future promotions across the various divisional product lines and track customer performance over time. In this course, we will focus solely on the use of a marketing database.

Optimal Database Marketing Drozdenko & Drake, Prospecting Databases Prospecting databases - are a type of marketing database but comprised solely of non-customers. They are usually kept as a separate file because they carry limited information on the names residing on this file. Once a prospect orders and becomes a customer, their information will be transferred from the prospecting database to the marketing database.

Optimal Database Marketing Drozdenko & Drake, Sources of Information For Marketing Databases MARKETING DATABASE INTERNAL DATA EXTERNAL DATA

Optimal Database Marketing Drozdenko & Drake, After an organization has determined the need to establish a database, the challenge often focuses on the varied and unorganized sources of customer information that currently exist. This information must be organized and structured in a meaningful way in order to achieve the objective of tracking customers. Internal Data Sources

Optimal Database Marketing Drozdenko & Drake, Internal data can originate from different departments in the organization such as accounting, marketing, customer service, operations, research, etc. Even within those departments, sometimes several different databases will exist. Internal data is also called house data and referred to as the house file. Internal Data Sources Data collected by the organization

Optimal Database Marketing Drozdenko & Drake, Internal Data Sources Data collected by the organization Previous Contact Information Purchase Records Product Returns Data Bad Debt Information Customer Service Data Surveys Voluntary Customer Registration Data

Optimal Database Marketing Drozdenko & Drake, In-house customer data is classified as one of three types, based on how it is used: Fulfillment Data Marketing Data Customer Contact Data House Data

Optimal Database Marketing Drozdenko & Drake, Fulfillment Data Fulfillment data are basically raw or transactional-level data and are primarily used for billing and fulfilling orders. However, a marketer also wants to use such data. For example, the data field “Last Bill Effort Sent” is used by a marketer as an indicator of how quickly a customer pays.

Optimal Database Marketing Drozdenko & Drake, Marketing Data Marketing data are any piece of customer information used by marketers for the purpose of increasing the effectiveness or efficiencies of marketing activities. This includes data that can help marketers promote customers, develop relationships with customers, and establish marketing strategies and programs.

Optimal Database Marketing Drozdenko & Drake, Marketing Data Marketing Data can be classified into three type related to the recency, frequency and monetary value of customer transactions. Recency data are related to the recency of a customer’s last promotion, order, payment, and so on. Frequency data are related to a customer’s total number of promotions, orders, payments, etc. Monetary data are related to a customer’s total dollar value of orders placed, payments made, etc.

Optimal Database Marketing Drozdenko & Drake, Customer Contact Data Customer contact data are the foundation of the database. The marketer must have a means to reach customers. Basic contact information includes name, address, zip code, phone and fax numbers, and address. Marketing efficiency and effectiveness is greatly affected by the quality of the contact information.

Optimal Database Marketing Drozdenko & Drake, External Data External data can help supplement in-house customer data and allow marketers to develop more effective marketing programs. Several sources of external data allow marketers to supplement and enhance their databases.

Optimal Database Marketing Drozdenko & Drake, External Data Types Compiled List Data Census Data Modeled Data Based on their characteristics, external data can be classified into four categories.

Optimal Database Marketing Drozdenko & Drake, Compiled Data Compiled Data are lists of people or organization gathered from telephone directories, voter registration files, birth records, housing purchase records, membership rosters, etc. Companies such as Edith Roman, Polk, USAinfo, Experian/Metromail compile lists.

Optimal Database Marketing Drozdenko & Drake, Compiled Data The information in compiled list data can be categorized in two ways: Demographic Psychographic

Optimal Database Marketing Drozdenko & Drake, Demographics Income Age Gender Marital Status Education level National Origin, Ethnicity Family Size Occupation Religion

Optimal Database Marketing Drozdenko & Drake, Psychographics Hobbies Reading interests Exercising habits Music preferences (rock, country, etc.) Movie preferences (action, drama, etc.) Political Orientation Social (opinions on the environment, education, family, health care, etc.) Donor characteristics

Optimal Database Marketing Drozdenko & Drake, Census Data Demographic and other data collected by the US government on a periodic basis. The census is updated every 10 years, updates on specific data, such as population growth, are done more frequently. Data can be broken down to specific geographic areas in the country.

Optimal Database Marketing Drozdenko & Drake, Census Data Obtained from the U.S. Census Bureau at a geo- demographic level (zip code, block group, census track, etc.) It is not available at an individual level as compiled list data. “Census tracts” are 50,000 subdivisions of counties. “Block groups” are 225,000 subdivisions of census tracts formed by grouping blocks (streets). Being too fine of a split, some sensitive economic and personal data is not reported at the block group level; however, it is reported at a census tract or zip code level.

Optimal Database Marketing Drozdenko & Drake, 2002 Examples of Census Data Average household size Average home value Average monthly mortgage Percent ethnic breakdown Percent married Percent college educated And even such measures as average daily commuting time

Optimal Database Marketing Drozdenko & Drake, 2002 Census information for three very demographically distinct census tracts are shown below. If you were to promote an expensive children’s book series and could only market to the names within one of the three census tracts below, which would you choose and why?

Optimal Database Marketing Drozdenko & Drake,

Optimal Database Marketing Drozdenko & Drake, 2002 Data Residing on the Marketing Database (Cont.) When lacking an abundant amount of individual level data pertaining to customers, a direct marketer often relies on census level data. The premise in using this type of data for determining a product’s target market, when no other data is available, is that all individuals living within a geo- demographic region are similar to one another. While this may be true in some cases, it certainly is not in others. Head-to-head, census level data will never be as powerful as individual level data in predicting customer behavior. However, as previously mentioned, when no other information is available, it will and can play a fairly strong role depending on your applications.

Optimal Database Marketing Drozdenko & Drake, Modeled Data Modeled Data are generated from statistical analysis such as customer clustering. These data are often used to classify customers based on purchase patterns, demographics and psychographics. For example, based on certain geographic data, income or educational levels can be predicted.

Optimal Database Marketing Drozdenko & Drake, Lists Versus Data Names residing on lists can also be rented for promotions or purchased and added to a direct marketer’s prospecting database. Typically, contracts are set for a one-time use or a one-year agreement with unlimited use. Outside intermediaries such as list brokers or managers often handle list rentals and maintenance for an organization.

Optimal Database Marketing Drozdenko & Drake, INSOURCE A Database Enhancement Service Delivers Data On … a broad range of demographics consumer interest and lifestyle telephone numbers mail order responsiveness automotive ownership real estate holding census geodemographics

Optimal Database Marketing Drozdenko & Drake, Response Lists Response lists are lists of people or organizations that responded to offers such as mail order catalogs or subscriptions. Organizations rent lists of people who responded to their offers.

Optimal Database Marketing Drozdenko & Drake, Examples of Response List Data Subscription to a magazine Purchase from a catalog Donation to a charity Request for information about a product Some of these lists are further specified as to most recent purchasers. These are called “hot-line” lists.

Optimal Database Marketing Drozdenko & Drake, House data can be enhanced with response list data to determine if any of an organization’s customers responded to offers of other direct marketers. Some companies establish joint agreements whereby they exchange certain pieces of customer data. Examples include: Sharing of non-payer information Catalog buyers Response List Data

Optimal Database Marketing Drozdenko & Drake, Compiled vs. Response Lists As mentioned, most compiled lists are relatively simplistic lists of names and addresses from sources such as public real- estate records, and organization rosters. In contrast, response lists are people or organizations who have previously responded to some type of offer. Response lists can be further defined by media, such as direct mail or telemarketing responders.

Optimal Database Marketing Drozdenko & Drake, Compiled vs. Response Lists Response lists have a higher potential response rate than compiled lists because past behavior is a good predictor of future behavior. Therefore, marketers seek response lists composed of purchasers (or donors) in the same or a similar category to their own.

Optimal Database Marketing Drozdenko & Drake, Purposes of Data Enhancement (Data Overlays or Supplements) In addition to acquiring lists of potential new customers, marketers overlay information on an existing database… To learn more about individual customers To increase the effectiveness of customers programs To predict responsiveness for prospective marketing programs

Optimal Database Marketing Drozdenko & Drake, Applying and Using Enhancement Data If direct marketers wish to have enhancement data (census, compiled, or modeled) overlaid on their customer file, they often follow these steps: 1. The direct marketing company makes a copy of their customer file (or whatever portion they wish to enhance) and sends it to the to the enhancement service. 2. The service bureau matches their file to the direct marketing company’s file using a name and address- matching algorithm (Chapter 4). 3. Once matched, the service bureau appends the desired information (e.g., age, income, lifestyle indicators) to the copy of the file given to them. 4. The direct marketing company matches the file back to their database (via a unique customer number) and appends the enhancement data to their file for future use.

Optimal Database Marketing Drozdenko & Drake, Three case studies illustrating the use of enhancement data.

Optimal Database Marketing Drozdenko & Drake,

Optimal Database Marketing Drozdenko & Drake,

Optimal Database Marketing Drozdenko & Drake,

Optimal Database Marketing Drozdenko & Drake, Review Questions 1. What are some of the sources of data that can be included in the database? 2. Give some examples of demographic and psychographic data elements. 3. How are compiled lists different from response lists? 4. Why are house files (internal databases) enhanced with supplemental data? 5. Describe how marketers can use U.S. Census Bureau data. 6. What steps are involved in using an outside service to enhance a house file?