Technology as the Great Enabler of CRM Analytics
With CRM becoming the paramount philosophy of marketing in the 21st century, organizations are striving to develop processes which are compliant with this philosophy. Specifically within the area of CRM analytics, one of the constants is the need for information. In looking at information within CRM analytics, one could use the analogy of the human body . The human body requires food for the effective functioning of all its processes which is similar to the need for information amongst CRM analytics practitioners. Yet, food by itself is not sufficient as exercise and eating the right foods are the real keys to successful health. It is no different with CRM analytics as the successful practices require not just information(food) but the ability to use this information in a meaningful manner(exercise).
The use of technology is the great enabler for CRM analytics by allowing organizations to more effectively derive meaningful information and knowledge from raw data. What does this mean? For the more advanced user, we now have more robust tools. Advanced statistical techniques can be more easily applied alongside tools that more effectively process the data.. A more advanced user can examine more complex techniques while examining them with much larger volumes of data. For these type of users, they can continue to look at their traditional ways of analyzing data which required a high level of technical expertise usually involving some type of programming as well as exploring other tools which may offer additional statistical techniques or increased data processing capabilities.
Yet, the real win for technology within the CRM analytics arena is the ability to empower more people beyond just the advanced users as discussed above. An empowered environment permits a much broader perspective of a given problem since more people are able to analyze the data. Certainly, this broader and indeed more collective perspective may produce better solutions. But what is the caveat? Yes, indeed more people can analyze data but how deep is the understanding of the information. At the heart of any analysis resides the source data. Most of these new empowering technologies deal with the source data in canned programming modules where the analyst does not need to have a solid understanding of the data environment and all its nuances. More importantly, the analyst does not need to have an understanding of how to manipulate the data into a form where it can be analyzed. This limitation represents a loss of potential knowledge and information because in many cases it is this detailed knowledge of the data environment that can truly lead to a superior data solution. As in many business scenarios, the devil is in the details.
These new user empowerment technologies are certainly here to stay. But organizations also need to understand that the role of advanced analytics and the need for more technical human resources is equally important. In fact, in being able to juggle these two priorities of user empowerment and advanced analytics, one must be able to evaluate projects by the degree of data intensity that is required. For example, certain exercises and projects such as simple cross-tab reports require a less data intensive discipline while projects such as predictive models require a much more rigorous discipline with the data. Both cases involve analytics and both are equally important to the organization , yet it is the successful organization that can both increase user empowerment while providing a more focused approach towards its advanced analytics. The key to this success, though, is effective use of technology.
