Sources and Uses of Marketing Data

Customer Data

• All sales, promotion, and service activity relating to a customer.

• Best bets for use in predictive statistical models.

• Not available in equal measure for every customer

• More data available for old customers.• Appropriate measures that use time a

customer has been on file hence required.

Cohort or Enrollment Group

• Groups that contain customers that have

been on file for similar lengths of time.

• Basis for all forecasting systems.

• Used to alert management on changes in

lifespan, and lifetime value.

Other Sources

• Billing status, service interactions, back orders, product shipment, claims history etc.

• Marketing department internal operations• Customer classifications

• Response scoring models

• Expected sales

• Marketing Objectives

• Projected customer value

• Expected promotion costs.

Response Data

• Recording a purchase in response to a coded promotion.

• Example: Multistep lead generation process.

Problems in coding response data– Transactions occur across multiple channels– Matching promotions and responses to

appropriate customers.– For example, in the case of retail promotions

point of sale scanners cannot capture customer identification.

– Cost minimization in call centers may not allow promotion and customer codes to be recorded.

– Responses may not be matched at the individual customer level but at the zip code level.

Response Attribution

• What if the customer is sent multiple

promotions and he/she responds to one of

them?

• What if the customer passes along the

promotion to someone he knows?

Prospect Data

• People who have been promoted in the past but

have not made a purchase yet.

• Prospect Databases

– Used when there is relatively large variation in

potential customer values.

– Primary applications

• Track promotion history

• Calculate number and type of lists that contain information on

a prospect

• Combine descriptive statistics from internal sources

Prospect Data

• Two-Way Customer Dialogues

– Focus on developing and managing a relationship with

each customer.

– Manage communication across all channels

• Example: Financial Services

– A customer may not be ready to invest currently.

– Keep the communication channel open with the customer

in order to convert the customer at the appropriate time.

Prospect Data

• All information is potentially important.

• Data gathering is an ongoing process.

– Begins before the first purchase is made.

– Pay careful attention to

• How the customer is contacted?

• When the customer is contacted?, and

• What data can be captured at each stage?

Nontransactional Data Sources

• Data provided directly by individuals about themselves.

• Third Party vendors.

• Directly supplied data:– Obtained from lead generation questionnaires,

warranty cards etc.– Very critical for relationship marketing.

Nontransactional Data Sources

• Directly supplied data consists of three major types• Behavioral Data• Attitudinal Data• Demographic Data

• Primarily a forte of marketing researchers until recently.

• Marketing research studies have information on only a sample of the customers.

• This information is not enough to create customized, individual level campaigns.

Macro vs Micro level data• Consider two companies and two customers

• Firms have same shares in both figures but their customers have different purchase patterns

Firm 1 Firm 2

Customer A 1 2

Customer B 1 2

Firm 1 Firm 2

Customer A 0 4

Customer B 2 0

Nontransactional Data Sources• Relationship Marketing

– Third party data is so commonly available that it does not

provide a competitive advantage.

– Leverage investments in customer service to collect

individual information during regular business interactions.

– Advantages:

• Better coverage

• Data directly relevant to marketing objectives, and

• Faster acquisition cycles.

Nontransactional Data Sources• Relationship Marketing-The Advent of internet

– Lead generation

– Automated brochures provide wealth of product information and enable collection of e-mail, address etc.

– Surveys can be posted on the web

• Questions in the survey can be tailored to each customer.

• Growing evidence that customers are less reluctant to provide information on web sites.

– Privacy issues need to accounted for.

– If relationships are developed customers are ready to provide sufficient information.

Example: Insurance Marketers

• Age is the most critical information needed.

• Third Party sources provide unreliable information and have poor coverage.

• Insert a small survey in initial promotion packets.– Inquire in the surveys about

• Date of birth,

• Other insurance products customer currently owns, and

• Level of Satisfaction.

Example: Insurance Marketers

• Primary benefits– Better targeting

– Better mailing efficiency

– Reduced dependence on less accurate data

• Auxiliary benefits– Eliminate or reduce promotions to those who are not

responding.

– Use survey information to offer additional products.

Using Questionnaires

• Internal customer data does not include information on willingness to purchase.

• Use a two-step communication strategy.• First Step:

– Simple, inexpensive attitude and behavior survey

• Second Step:– Expensive brochures that contain product information and

special offers.

• People who respond in the first step but not the second provide information for relationship marketing.

Survey Data: Assigning Customers to Segments

• Segments: Small relatively similar pockets of customers.

• Customers within a segment are similar to each other and

differ from customers in other segments.

• Issues:

– Confirm that segments exist

– Determine attitudes and characteristics of each segment.

– Design cost-effective ways to assign individuals to appropriate

segments.

Survey Data: Assigning Customers to Segments

• Use survey responses to identify characteristics of segments.

• Characteristics useful in designing customized campaigns.

• Responses may be available only from a sample of customers.

• Very expensive to send surveys to all the customers in the database.

Survey Data: Assigning Customers to Segments

• Relate survey data to internal customer data.

• Use statistical models to infer segments membership based on – Internal data, and– Relation between internal data and survey

responses.

• Response rate depends on the relation between an organization and its customers.

Profiling: Assigning Customers to Segments

• Ways to create customer profiles

- RFM

-Product affinity

- Demographics

- Cluster or lifestyle coding

Based on behavior

Based on attitudes, demographics, lifestyle

Profiling: Assigning Customers to Segments

• Classification by product affinity

- Affinity starts from customer’s perspective

- Use Cross-Buying rates.

-This is done by cross-tabulating purchasers of one product against purchasers of another product

A B-No B-Yes Total

No row 268431 8328 276759

96.99% 3.01% 100%

Yes row 27023 12444 39467

68.47% 31.53% 100%

Total row 295456 20772 316228

93.43% 6.57% 100%

Profiling:Cross-Buying rates between A and B

Profiling:Affinity Matrix showing likelihoods of purchase

Prod A Prod B Prod CProdD

Prod A eq 10.5 2.4 4.5

Prod B 10.5 eq 9 1.1

Prod C 2.4 9 eq 3

Prod D 4.5 1.1 3 eq

Third Party Sources

• Primarily demographic, attitudinal, lifestyle and financial data.

• Available at the zip code and census tract level.

• Census tract (or block) level is a finer classification but is more expensive and requires additional statistical techniques.

Third Party Sources

• Zip code used when number of customers or prospects is large (> 100,000).

• Zip code data can be overlaid with purchase data for profiling purposes.

• Major Products:• ClusterPlus (First Data Solutions)• PRIZM (Claritas)• MicroVision (National Decision Systems)• Mosaic (Experian).

Third Party Sources

• Data is primarily averaged at the zip code level.• Based on the premise that

– “ Birds of the same feather….”

• Issues:– Possibility of outdated information.

– Results in promoting to the wrong people.

– Useful only when any form of prospect or customer information is unavailable.

National Databases: File Enhancement

• Nearly total coverage of US households.• Attitudinal Data

– Contains information on general opinions, and perceptions of the people.

– Useful when launching new products/services.

• Lifestyle Data– Provides information on personal interests, and leisure time

activities.– Result of combining geo-demographic and market research data.– Example: Claritas (geo demographic) + Simmons (Market Research)

National Databases: File Enhancement

• Lifestyle Data (Continued)– Improves the reach of print and electronic

media.– Representative strategies for use:

• List profiling.• Use the lifestyle characteristics for only customers

with the highest priority.• Apply profiles to prospect files.• Used as a guideline for obtaining other lists.

National Databases: File Enhancement

• Financial Data– Largest providers – Experian, and Transunion.

– Data on credit card purchases, installment loans, applications for

credit, and payment history.

– Marketers can send their house lists to financial data providers.

– The financial data providers then provide a profile of their best

customers.

– Information at segment level not individual level.

– Then prospect list can be used to send promotions to prospects that

match profiles of best customers.

National Databases: File Enhancement

• Demographic Data– Available at the household or individual level.– When certain data (e.g., age) is unavailable

– A reasonable inference can be made for a majority of the individuals.

– Multiple sources:• Motor Vehicle Registrations (Polk)• Telephone and City Directory (First Data Solutions and

Metromail)

– Values that are available are accurate and are not summaries at the Zip Code Level.