Chapter 4Chapter 4

Marketing Intelligence and Marketing Intelligence and

Database ResearchDatabase Research

Chapter 4Chapter 4

Marketing Intelligence and Marketing Intelligence and

Database ResearchDatabase Research

1. What kind of relationships will add value to customers (e.g., loyalty programs, preferred customer status, etc.)?

2. What is the value perception of the customer segment, and how can the value be enhanced (e.g., direct communication to customers, new services, etc.)?

3. What products and services and mode of delivery have value to the customer segment (e.g., stock market alerts via Web-enabled mobile phones)?

4. What are customers’ responses to marketing and sales campaigns?

Market Intelligence Questions

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1. Develop meaningful communication with customers.

1. Develop meaningful communication with customers.

2. Improve efficiency of market segmentation.

2. Improve efficiency of market segmentation.

3. Increase probability of repeat purchase behavior.

3. Increase probability of repeat purchase behavior.

4. Enhance sales and media effectiveness.

4. Enhance sales and media effectiveness.

Customer Database – Purposes

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How products compare with the competition?

Relationship between perceived value and price of the product?

How satisfied customers are with the service level and support for the product?

What are the comparisons among lifestyles, demographics, attitudes, and media habits among heavy, medium, and light users of the product?

Other Questions Answered from Databases

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Database Information

ProfitabilityProfitability

RecencyRecency

FrequencyFrequency

Affinity (Liking)Affinity (Liking)

Customer Characteristics

Customer Characteristics

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View the total process of database development as a commitment to a long-term data acquisition plan.

View the total process of database development as a commitment to a long-term data acquisition plan.

View the data acquisition process in terms of the depth and width of the database.

View the data acquisition process in terms of the depth and width of the database.

Avoid jumping onto the database bandwagon and then failing to commit the necessary resources.

Avoid jumping onto the database bandwagon and then failing to commit the necessary resources.

Database Development

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Geodemographic(Geographic, residential)

Geodemographic(Geographic, residential)

Attribute(attitudinal)Attribute

(attitudinal)

Target Market(demographics, usage)

Target Market(demographics, usage)

Three Types of Database Units

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o Central repository of data.o Two Purposes:

•Collect and store data•Operational Data

•Online Transactional Processing (PLTP)

•Collect, organize and make data available

•Informational Data

•Online Analytical Processing (OLAP)

o Comparable to a library.

o Central repository of data.o Two Purposes:

•Collect and store data•Operational Data

•Online Transactional Processing (PLTP)

•Collect, organize and make data available

•Informational Data

•Online Analytical Processing (OLAP)

o Comparable to a library.

Data Warehouse

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Data Warehouses

Types of Data to be

Stored

Secondary data

Primary data

Real-time transactional data

Customer-volunteered data

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Data Mining

Analysis procedure – identifies significant

patterns of data relationship for

specific customers or customer groups.

Analysis procedure – identifies significant

patterns of data relationship for

specific customers or customer groups.

Data Mining – process of finding

hidden relationships among variables contained in data stored in the data

warehouse.

Data Mining – process of finding

hidden relationships among variables contained in data stored in the data

warehouse.Transforming Data Into

Knowledge

Transforming Data Into

Knowledge

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•Enable researchers to determine which factors separate customers into purchase groups . . .

•Use weights to multiply assigned values

•Use actual purchase behavior data

•Key variables Assign weights or scores depending

on ability to predict purchase behavior

•Enable researchers to determine which factors separate customers into purchase groups . . .

•Use weights to multiply assigned values

•Use actual purchase behavior data

•Key variables Assign weights or scores depending

on ability to predict purchase behavior

Scoring Models

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Lifetime Value Model

Premise – need to determine value of customers to your company

Lifetime value models – examples of variables . . .• Price variables• Sales promotional variables• Advertising expenditures• Product costs• Relationship-building efforts

Database Information• Used to identify most profitable customers

over the span of their relationship with the company

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