While researching event-based marketing recently, I happened upon the top 10 buzzwords of customer relationship management (CRM) for 2007 as identified by SearchCRM.com. Three of the top 10 are predictive analytics, customer valuation and personalization.1 I found this to be quite interesting because all three fit into the business intelligence (BI) folder in my mental filing cabinet. Predictive analytics is the use of data mining and analysis techniques to predict future behaviors and trends. Central to this concept is the ability to determine the variables that will reliably predict future customer behavior. Purchase propensity, default and credit risk, and attrition are all common predictive analytics focus points. Predictive analytics requires a robust data warehouse and perspicacious use of BI tools to deliver the desired insights.

 

Customer valuation is a similar concept - the scoring of customers based on past purchase recency, frequency and expenditure (monetary) in order to narrow the field of campaign recipients to those most likely to purchase again. This does not happen by magic - determining accurate and prophetic customer scores requires the BI environment to be in place. Personalization, while frequently constrained to the Web, is actually much more broadly applied by leading relationship managers. Personalization is a way to tailor communications so they conform to stated and inferred customer preferences and is a form of one-to-one marketing. Communications come in all forms and include promotional, service, regulatory, complaint responses and retention attempts. Event-based marketing (EBM) falls under the auspices of personalization. EBM is the generation of targeted and personalized communications that are triggered by significant events that indicate a specific customer need, eminent customer action, or strong propensity to purchase. Both EBM and personalization are difficult to do effectively without the data warehouse and associated BI tools.  

What I find most interesting is that while fully 30 percent of the CRM top 10 are closely aligned to what I think of as BI (requiring a data warehouse for robust results and scalability), it seems that many CRM vendors have only one category in their mental rolodex - CRM, with a subfolder labeled “analytics.” Rarely is the data warehouse given the marquee billing it deserves. Many times it is not mentioned at all. In fact, while poking around a few predominant CRM Web sites to test my hypothesis, I found the expected omission of this key component but also something far worse: a white paper titled “World Class Analytics - Without a Data Warehouse.” The paper called the data warehouse expensive, complex and unnecessary (more about this in an upcoming column).

That the data warehouse is viewed as an adjunct (sometimes an unnecessary one) to the main event in the CRM world should not surprise me, because in the not-so-distant past, CRM was synonymous with operational activities. Typing “CRM software” into your Internet search engine still brings back predominately operational applications - call center, help desk and sales automation.

 

While the vendors of these applications have included analytics capabilities in their product offerings, most are nothing more than simple prefabricated data marts that get their information directly from the CRM application. Many have partnered with BI tool vendors to provide query and reporting capabilities as part of their standard offering, but the licenses restrict you to only the data in the CRM applications. Not one of the CRM applications by themselves, analytics modules notwithstanding, can provide the capabilities inherent in the CRM top 10 focus areas - predictive analytics, customer valuation, personalization or EBM.

 

While I am not suggesting that CRM vendors include a data warehouse as a part of their product offering, I do think they should rearrange that mental rolodex a bit and give CRM and BI a more equal billing. Acknowledging that a robust BI environment is needed in addition to the CRM applications to do comprehensive predictive analytics, customer valuation and personalization would also be nice. I believe that the BI vendors and practitioners are beginning to do this. Just last month in this column, I looked at how operational intelligence (using right-time analytics to monitor and manage daily operations) has extended the reach of BI into traditional CRM territory by requiring BI teams to modify operational processes. None of the BI practitioners that I know of advocate trying to accomplish operational BI without the operational applications. In fact, it is just the opposite. Most are strong proponents of the need for a comprehensive conceptual architecture, such as the Corporate Information Factory, that highlights all of the components required for business operations (operational systems), business management (operational data store) and BI (data warehouse and marts). Each component has its place in the architecture. Integration points between the components are highlighted and closing the loop between operations and analytics is a key objective.

 

One day, maybe. Until then, we have our work cut out for us.

 

References:

  1. Christine Cignoli. “CRM and Customer Service Market Trends: Top 10 Buzzwords.” SearchCRM.com, August 1 2007.

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