More revenues through precise
target group approach
INNOFACT developed an innovative approach for the successful identification of customer segments. In a multi-level analytical process, attitudinal, behavioral and sociodemographic dimensions turn into real-life customer segments.
INNOFACT has its own panels for direct Access to over half a million consumers throughout Germany and delivers impressive indepth results even for small samples.
Clients from various industries have been using the cooperation with INNOFACT for years to research their target groups precisely, and thus secure decisive competitive advantages in highly competitive markets.
Successfully identify customer segments
INNOFACT has already successfully identified customer segments for a large number of companies: With straightforward questionnaire construction that merely supplements a “simple” questionnaire with a series of attitude and behavioral questions, action-relevant customer segments are compiled in an analytical process. In principle, two approaches for typologies and customer segmentation can be distinguished from each other.
In the first method, a priori types can be defined in order to segment the respondents, a questionnaire is formulated whose questions describe these types. The respondents are asked – to put it briefly – whether they would assign themselves to one of the types described. INNOFACT uses a second method, which is analytically more complex, but provides results that are more selective and closer to reality. The main difference to the simple segmentation method is that predefined types are omitted in favor of a large number of statements that may contribute to segmentation. By means of a staged cluster and factor analysis, patterns and correlations are identified within these statements. In this procedure, the segments and customer types are formed quasi “automatically”, and just as they occur in empirical reality. The result is the identification of customers or target groups that are very similar to each other, and at the same time differ as much as possible from the other types.
Step 1: Summarising the Information
The questionnaire consists of a number of statements. The first step is to search for correlations between these statements (factor analysis). At the end of this first step there are a number of scales. Each of these scales consists of statements with similar directions of the responses. The scales form the basic building blocks of the segments.
Step 2: Identification of the segments
All scale values – and thus also the information from the individual statements – are now considered together with the socio-demographic and other information. Again, patterns and similarities are searched for: In this step, however, we do not look for similarities between the statements, but for similarities between individual test persons.
In simplified terms, a cluster analysis looks at each respondent individually and compares them with all other respondents. If similarities are found, a group is formed. After a number of such comparison runs, groups are formed whose members are very similar to each other and at the same time differ from the other groups in as many characteristics as possible.