The first article on the online CRM series by artegic AG deals with the function of online CRM in companies, i.e. with the operative tasks – the operative CRM. For these tasks, e.g. the construction of a personal customer dialogue in email marketing, decisive information about customers is necessary. The efficient capturing, administration and analysis of data is therefore becoming an essential competitive factor. Information management or analytical CRM, is the basis for successful online CRM.

Capture and Administrate Data

In online CRM, all relevant customer data is captured in a data warehouse. The task of the data warehouse is the integration of data from different sources within the company, e.g. email marketing, inventory control system or online shop, in a central database. Data collected in the operative CRM is captured and analysed in the data warehouse and the findings are reused in the operative CRM. In this closed loop, the customer knowledge is increasingly refined and with each new piece of information, the CRM can adapt more precisely to customer requirements. A pre-condition is, that there are suitable interfaces between the data warehouse and the operative CRM.

Importance of Data Quality

The collection of data in online CRM must always be task-oriented, i.e. only data, which is relevant for decision making in the operative CRM, should be collected. However, data collected in the operative CRM is not necessarily usable in the analytical CRM. Example: The sales department collects data on the net income of customers in B2C in order to better evaluate their potential. It asks for absolute figures, e.g. €3,000, but for the analysis, only income groups are relevant, e.g. €2,500-€3,500. This requires a close synchronisation between the operative CRM and the analytical CRM. Furthermore, data must be captured correctly, e.g. names must not be misspelled.

Analyse Data

To analyse data, you can use a number of concepts. Data mining procedures, for example, analyse data multi-dimensionally while searching for patterns within the datasets. Connections between, e.g. socio-demography and buying behaviour can thus be identified. While data mining procedures can detect surprising connections, in the online analytical process (OLAP), you need to specify in advance, which connection or which query is to be researched, e.g. whether the click rate in email marketing is higher with men than women.

Automation of Processes

An important trend in online CRM is the automation of processes. It has become a central challenge of the online CRM to automatically analyse all data including the response to the communication and transfer the results in an integrated loop, which can respond with the correct communication in real-time. However, the relevant capacities for automated response and communication are often lacking. Static CRM systems and manual execution of processes are still the norm. Here, we can see email marketing as a role model. In modern email marketing systems, many of these required capacities already exist.

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