Understanding Consumer Database Marketing

Consumer database marketing is a powerful subset of traditional marketing practices combined with computer based analysis technologies. Essentially, consumer database marketing allows us to analyse and then use information about individual customers and prospects to enhance marketing campaigns.

Consumer database marketing helps us target prospects more accurately and deliver more pertinent offers to them. Thus, a database led marketing campaign, promises a greater chance of success and a higher return on investment.


Carrying out consumer database marketing

Types of analysis in common usage for consumer database marketing include:

1. 
   Regression Analysis
   This technique can deliver a highly targeted prospect list for a particular offer. This is done by scoring consumers according to relevant characteristics. For example, here are a set of scoring rules for the likelihood of consumers responding to the offer of a deluxe German motor car:
   
   Add 50 points if they have bought a deluxe car before
   Add 50 points if the previous car was German
   Add 30 points if they earn more than £50,000
   Deduct 10 points if they earn more than £300,000
   Deduct 20 points if they are aged less than 35
   
   Once all the rules have been applied, each prospect has a total score and the higher that score, the better chance of them responding to the offer. The scoring system is derived from study of previous behaviour and can prove a very effective method when correctly implemented.
   
   


2. 
   CHAID analysis
   CHAID (Chi-squared Automatic Interaction Detector) is a computer based system that produces a tree like structure of potentially valuable leads by analysing a consumer database according to predefined segments and past responses. Once it knows which sector is most likely to respond, that group is then subdivided according to all the given variables. This process is then repeated again and again to give small groups of customers, each with a probability score assigned to it. By marketing to the resulting list in order of probability, return on investment can be maximised.
   



3. 
   Cluster analysis
   Cluster analysis breaks down customers into different types. It processes the raw database information and classifies consumers into clusters according to characteristics. Hence in cluster analysis we see consumers listed on the database with classifications such as ‘nest builders’ or ‘liberal new-agers’.
   
   

With the power of modern computers it is now possible to run these analysis tools at home using a home PC. However, the main skill in consumer database marketing is not running the analysis software but actually understanding the data. A combination of statistical understanding and excellent marketing knowledge are required to get the most out of database marketing.

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