This is part two of a podcast about big data and CRM. For part one about big data's applicability to CRM processes, click here.
Applying big data to customer relationship management (CRM) enables companies to get a more complete picture of their customers and perform real-time customer service. But these goals aren't possible when an organization's systems are siloed or customer data is poor quality.
In part one of this podcast, independent consultant Peter O'Kelly defined big data and highlighted its broad applicability in CRM processes. In part two, he talks about technology challenges that need to be addressed before companies try to tackle big data and about the steps needed to manage data resources.
"If the data you're working with is incomplete or inconsistent, [it] can create bad customer experience patterns," O'Kelly said.
O'Kelly discusses rapidly changing service expectations and the need for companies to handle large amounts of customer data to improve the customer experience. The proliferation of data management products, however, has created a "paradox of abundance" in the market, making it harder to find a system that meets company requirements.
According to O'Kelly, data quality is the foundation for instituting big data initatives. Unfortunately, "basic data management has been considered a less significant priority" in business today, he said.
"Many enterprises simply don't have their data houses in order today," O'Kelly said. "They have to go back and clean, refine or extend their existing data resources before they can … use them for big data opportunities."
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