Not yet. For many years, firms have let their own intuition about “business value” guide their investment in, and development of, database systems that record their knowledge of their customers’ experiences. Concerns about the accuracy and data quality within these systems have largely been calmed by layers of data governance and good MDM (Master Data Management) practices – especially when a concerted push toward CRM is in play. Regardless of whether a capstone CRM system is present, we see that today the component systems are contributing customer experience data of much higher quality and value to the overall organization than in years past. Smart Data Integration practices make the consolidation of disparate customer data sources not only doable, but the solid foundation upon which many marketing customer databases are built.
The Gap: Digital Interactive and Social
The emergence of digital interactive channels and social networks poses a challenge for the typical database solution…How do we capture and standardize the characteristics of the customer we’re interacting with online (identity)? How do we know if their behaviors or activities are significant to the brand or marketing strategy (relevancy)? Having less than definitive answers to these questions could cause the average marketing customer database to seize up and its developers to break out in hives. To the product marketers, these less-than-perfect and rapidly changing data sources are a valuable source of leading indicators of consumer behavior.
Uncertainty is not defeat.
Although potentially difficult to accept for “black and white” system developers, the real answer is to allow probability into the Data Model of your marketing database. Probability that a point of contact( a cookie or an email address) is a known customer or prospect, and probability that their actions or expressions are indications that are important enough to be leveraged in marketing decision making. The level of uncertainty – which could range from completely anonymous activity, to indications that visitors are members of probable segments-- and ending up with a direct connection to contact names and/or direct consumers – needs to become part of the database design. When supported by sound behavioral segmentation and predictive modeling used to make the probable connections, the customer database can survive the challenge, and retain its value to the enterprise.