We're swimming (even drowning) in data—social data, CRM data, Google Analytics data... The list goes on and on. That data can help marketers better understand and react to markets than ever. The catch is that for that data to be useful, someone has to find, collate, and present it in a sensible form.
IBM's State of Marketing survey found that marketers around the world who use analytics in understanding individual customer preferences—and pinpoint media spend to target them—are more successful than other marketers in meeting revenue goals. However, IDC's CMO 2014 Predictions report finds "80% of customer data will be wasted due to immature enterprise data 'value chains.'"
A new breed of specialist is emerging among marketers, sales professionals, and business information analysts with a mission to improve and harness those data "value chains." Many weren't trained specifically for this role, but they understand their job and how technology can help them and their colleagues work smarter. So, everyone else on the team counts on them to help find the answers they need by pulling together the right data and presenting it in a format everyone else can make sense of.
What are the daily challenges marketers face?
1. Data is out of control
As systems of engagement proliferate, data piles up in CRM systems, marketing automation, social media, digital marketing, and Web analytics stores. Meanwhile, the Internet is bringing more external resources into play, ranging from demographic and sales intelligence resources to all the additional data beginning to be collected by the Internet of Things. This scattering of data is a major problem. Without 360-degree access to all available data sources, it is inevitable that organizations are destined to perform far below 100% of their potential.
2. There's too much data to handle
The proliferation of data is giving marketers a feeling of data overload—even before they connect into all the data they could be accessing. Inefficient data connections and integrations add to that burden, and excessively complex and unwieldy tools make harnessing certain data sources inefficient and costly. Time is wasted waiting for cumbersome batch updates, and many integrations are dependent on overstretched IT resources that add further wait cycles to the process.