Sources and Uses of Marketing Data

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Sources and Uses of Marketing Data
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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.

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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.

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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.

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Response Data

• Recording a purchase in response to a coded
  promotion.
• Example Multistep lead generation process.

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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.

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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?

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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

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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.

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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?

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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.

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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.

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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
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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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
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Profiling Assigning Customers to Segments

• Classification by product affinity
• - Affinity starts from customers perspective
• - Use Cross-Buying rates.
• -This is done by cross-tabulating purchasers of
  one product against purchasers of another product

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ProfilingCross-Buying rates between A and B

• 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

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ProfilingAffinity Matrix showing likelihoods of
purchase

• Prod A Prod B Prod C ProdD
• 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

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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.

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Third Party Sources

• Zip code used when number of customers or
  prospects is large (gt 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).

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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.

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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)

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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.

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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.

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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.