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Case studies

Multichannel customer measurement

Consolidation of customer satisfaction information received from different data collection channels, automation of database construction. Instead of ad-hoc solutions, the development of a process provides a solution to manage the data assets, directly extracting the information needed for improvements.

The company has been present in Hungary for several years as a broker of insurance products and as a dealer. The company's main strategic objective is to increase its retail customer base, penetrate the retail insurance market and to maximise market share. To this end, it has launched an intensive development programme to expand and improve the quality of its network of advisors and brokers.


The number of advisors and dealers who have direct contact with retail customers has multiplied as part of the network expansion, but this alone has not achieved the desired goal. The managers of the network of brokers felt the need to have a transparent and detailed picture of the satisfaction of retail clients and the work of brokers to be able to make further improvements and training in an efficient and targeted way. Valuable feedback from customers was received through several channels. Following a face-to-face meeting with the advisor, customers were asked to fill in a paper satisfaction questionnaire. In addition, clients with an email address were also contacted with a web-based questionnaire to capture details of the client experience. Further information was obtained from the traditional quality assurance feedback survey, which included a random call-back of some clients by the broker's supervisor.

Although information was available to support the quality improvement of the network, the large amount of data received through different channels, with different structures, was not presented coherently, was difficult to understand and was not suitable for making conclusions.


Consolidating data collected on customer satisfaction across different channels, and automatically incorporating new data into the data warehouse, has enabled the discovery of decision-support information.


SPSS Statistics provides complex solutions for managing and consolidating different databases. The standardisation of the coding of variables from different questionnaires can be automated and integrated into a process. To extract the information that underpins decision-making, the program requires a wide range of analysis options, which can be accessed through an easy-to-use visual interface without programming skills.

  1. Preparation
    The first step in the consultancy process was to understand the questionnaires, to learn about the databases coming from different channels and to map them. Subsequently, instead of using very large databases, a sample of 2 percent from each of the three databases was requested to develop the solution.

  2. Implementation
    To consolidate the data from different channels, we have created SPSS Statistics syntaxes that can be used to create a harmonised, manageable, unified structure from the databases originally available. All this is automated, "closed system", requiring no intervention to run the program. But the flexibility of the development offers further advantages: if the user wants to modify or add to the code written in the syntax as an ad hoc implementation, SPSS Statistics allows our partner to do this easily without any programming background, using the visual interface provided by the program.

In addition to the creation of a standardised ready-for-analysis database, our consultancy work also included the exploration of analytics options and the development of reporting processes.