Data warehouses and CRM
By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time. Contact TechTarget at 275 Grove Street, Newton, MA.
CRM needs data warehousing, this tip argues, because it's the best way to aggregate huge amounts of info to analyze and use to develop marketing and sales plans. Yet the inverse is not true. This tip is excerpted from The CRM Handbook, by Jill Dyché published by Addison Wesley's Pearson Technology Group.
One of the strengths of a data warehouse is in its ability to store large quantities of historical data, enabling companies to compare customer behaviors over time. For instance, by storing customer purchase history, a company can evaluate what might have attracted a customer to making a purchase or gauge whether that customer's purchases are increasing or decreasing. Comparing time-variant data can provide the company with the information it needs to deploy intelligent marketing and sales campaigns and offer customers appropriate levels of service. Storing historical customer data is the main reason for the enormous growth of data warehouses, both literally and figuratively.
Failure to integrate customer data across all touchpoints results in having only partial customer data, which can in turn cause poor decisions about how to treat customers. This is why data integration is an oft-stated goal of CRM stakeholders in survey after survey. It's also one of the biggest challenges of today's CRM initiatives.
The best-intentioned companies often slip up when it comes to providing data warehousing and the accompanying business intelligence capabilities to their business users. On the one hand, the IT department understands that data cannot be divorced from CRM and that the corporate data warehouse is the ideal CRM source system. On the other hand, the business community is pushing for a quick win and doesn't care where the data comes from as long as they get it fast. The business begins using its CRM application without a vision for how to drive ongoing business-process improvements.
IT scrambles to provide enterprise data to the CRM application without understanding which data will support the actions and business processes the business wants to improve. The businesspeople keep asking when it will all be finished.
So begins the slippery slope of the CRM point solution. The data warehousing community saw with its stovepipe data marts that effectively served organizational needs but were tough to link together, stovepipe CRM systems represent the burgeoning reality for many companies, even those with robust enterprise-wide data infrastructures. When the time tomes to integrate disparate CRM systems there is often more work -- and more expense -- than if CRM had been built around the data warehouse the first time.
At a recent conference, a well known industry analyst proclaimed CRM to be the new data warehouse "killer app," The analyst hailed CRM as the first practical application for vast amounts of customer data and claimed it would reinvigorate many a dormant data warehouse.
Such proclamations, although quotable, aren't necessarily right. Data warehouses provide a rich source of analysis for a range of topics, customer-focused and otherwise. They contain product defect data, welfare claims, criminal records, and human gene sequences, among other information. Indeed, there are thousands of data warehouses that don't involve customer relationships.
CRM is not a mandate for data warehouses; it's not even a data warehousing best practice. But the inverse is true: Data warehousing availing rich customer information across the enterprise is definitely a CRM best practice. Even so, data warehousing -- while necessary to a successful CRM program -- isn't sufficient in and of itself.
Click on the title to learn more about The CRM Handbook.
What did you think of this tip? Was it informative, or at least entertaining? E-mail and let us know.