Building Marketing Databases In-House or Outside Bureau? • Outside Bureau: • Outside agency that specializes in designing and developing customized databases. • Three factors.

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Transcript Building Marketing Databases In-House or Outside Bureau? • Outside Bureau: • Outside agency that specializes in designing and developing customized databases. • Three factors.

Building Marketing Databases
In-House or Outside Bureau?
• Outside Bureau:
• Outside agency that specializes in designing and
developing customized databases.
• Three factors to consider
• Cost
• Control
• Customization
Cost
• Cost of developing a database in-house
depends on
– Existing workload of the in-house staff
– If additional help is needed from contract programmers
– Other system development initiatives that will be
forgone
– Whether an outside resource is quicker and better
Control
• Customer list is the lifeblood of most customer centric
companies.
• External facilities create additional risk of exposure.
• Companies need to manage risk through procedural and
contractual measures.
• External bureaus should have familiarity with
• The company policies
• Initiatives
• Processing systems, and
• Data
Customization
• In house systems are more customized to the
marketing departments needs.
• However, end-user departments may be charged
by the IT department on a cost plus basis.
• Sometimes the cost plus charge is costlier than an
outside bureau.
• Service bureaus have very flexible approaches to
working with several clients.
Customization
• However, internal IT staff are always
available to make last minute changes.
• Internal IT staff may be trained to work
only on standardized systems.
• However, a dynamic system such as
marketing requires special skills to design.
External Vendors
• What if the platforms/software of marketing
department and IT department do not match?
• Time is spent in making the marketing and IT staff
speak the same language.
• Until then the marketing department uses the same
archaic information to make decisions.
• External vendors alleviate these problems because
they have previous experience helping previous
clients.
Combined Approach
• Approach #1:
– Use external bureaus and internal staff for tasks
they are specialized in respectively.
– For example, Internal staff may be good at
design while the external supplier may be
skilled in implementation.
• Approach #2:
– Use an external supplier initially, and then
migrate the system to internal resources later.
What Data is Needed?
• Three step process:
– Identify business and promotional files that
should be included.
– Review data elements in each contributing file.
– Select from each file the data elements required
in the marketing database.
What Data is Needed?
Identify files to be included:
• Not practical to have all the information that ever existed
about a customer.
• Issue to consider:
– Is the file too hard to get?
– Will the database contain data on customers or prospects?
– How much promotion history is available?
– What levels of transaction data is available?
– Is the desired data actionable?
– Data element coverage.
Review of Data Elements
Review Data Elements:
• Detailed reviews of each data element with the data
processing or end-user personnel.
• May take anywhere from one day to a few weeks.
Select Data Elements:
• Include all the data elements identified in the review
process– even somewhat critical elements.
• Review the selections once a year after experience is
gained with the system.
How will data get into a marketing database?
• Data extraction by data providers
– Standardized programs written to extract data.
– Automated when updates are required.
– Is not flexible when new data elements are added.
• Data extraction including creation of summary calculated data
• Un extracted copies of data to data loader
– Provide whole data files to the loader.
– Loader decides on what records to include or exclude.
– More work for data loaders.
– Simpler, and cost-effective when data elements change during review
In house Vs Service Bureau
Implications
• Data availability on a regular basis depends on
– In-house
• Workload of IT department (less number of data sources)
• Co ordination between departments (large number of data
sources)
– Service Bureau:
• Billing structure of the service bureau
• Cost of not having to co ordinate with other departments may
be steep sometimes.
Consolidating Records
• Customer data is captured in transaction
oriented systems resulting in duplicate
records.
• Data has to be cleaned before it is loaded
into a database.
• Example: Financial service firms
– using Unique customer ID or unique account
number.
Data Cleaning
• Duplicate Identification
– Software used to identify duplicates in mailings
– Based on names and addresses
• Address Standardization
– Representative software: Finalist, Code-1 Plus
– Verifies if 123 oak street, or 132 oak street, or 123 oat
street is correct.
– Uses national zip code databases for this purpose.
Data Cleaning
• Logic of address standardization software
- The ZIP code matches the city and state portions of
the address
- The corrected ZIP code contains an Oak Street
or Oak Street or both
- The street numbers along the street in question lies
within bounds of the ZIP code
- The street number is a valid address
- Whether the address is a business or a residence
Data Cleaning
• Matching Issues
- Variations of spelling of an individual’s name
- Companies with multiple business files store
name and address in different formats
- Use matching software in first case and parsing
in second case
- Duplicate identification may be very important
for prospects too
Data Cleaning
• Scrubbing
- For financial services companies, registration info
my be imbedded in customer record
- Use specialized application of parsing and
dictionary use
- Software would recognize that some terms are not
part of names or addresses
- Scrubbing software also retains meaning of
registration data
Data Cleaning
• Householding
- How certain are you (with the data available)
that Anthony Smith and Julia Smith are
married?
- Householding based on names and addresses
-Constitute a confidence indicator.
- Mail material that promote a happy
married life only if you are 100%
confident.
Data Cleaning
• More complex households
– Type I: Same last name, same address, and joint
account.
– Type II: Different last name, same address, and
joint account.
– Type III: Common account, different addresses,
may or may not have same last name.
– Type IV: Same address, different last names,
and different accounts.
Frequency of Update or Replacement
• Frequency of updating determines how well
the database represents the actual customer
master file.
• Updates need not be more frequent than the
decision making interval.
• Intervening month’s files need to be
accessible to make the update processing.
Avoid Access Conflict
• There is a always a priority conflict between
– Analytic users of data: Marketers
– Operational users of data: Customer Service
• Solution is to maintain separate databases with
each.
• But it is too costly, marketers may not have up-todate information on some transactions.
• To calculate trends, distribution by list source etc.
however, real time data may not be necessary.
Other Issues
• Level of Detail
• Transactional Vs Summary
• Update Vs Replacement
• Determines analysis that can be performed
• Determines variable cost
• Conduct periodic reviews to determine
changes in business needs and the resultant
changes in the databases.