Way back in the Internet dark ages of January 1996, Bill Gates wrote about and coined the phrase “Content Is King.” He was talking of course, about Web content and the need for people and organizations hoping to monetize the Internet to consistently produce fresh and relevant topics in order to gain the interest and loyalty of viewers, just as television had been doing, radio before that and print media the longest of all. His assertion that “over time, someone will figure out how to get revenue” from Internet advertising is frighteningly similar to today’s gurus predicting much the same in regard to social media marketing. Just as back then—when companies and marketers struggled with deciding whether a Web presence was needed—today there are still major corporations only testing the social media waters, even if only half-heartedly, to keep pace with competitors.
For me, however, two lines in the Gates vision statement take on a slightly different connotation than his thoughts on content: “The definition of ‘content’ becomes very wide” and “Over time, the breadth of information on the Internet will be enormous, which will make it compelling.”
I read those two lines and what immediately strikes me is the overwhelming amount of data being generated during these last 17 years and how it is being captured, nurtured and put to work in areas such as Lead Generation, Brand, Affinity, Cross-Channel and Retention marketing. If at all.
IBM has an infographic regarding the flood of Big Data they use in demonstrating how their Netezza device handles integration for several major marketing organizations. This shows how, with connectivity, speed and bandwidth issues having become nearly eradicated during just the last two to three years, the amount of collectible, actionable data has exploded.
Unfortunately, the amount of irrelevant and useless data being collected is even greater than the actionable data, and being able to simply store that much data, let alone begin to organize and digest it all, is a major concern for most organizations. Before even thinking about the incorporation of Big Data initiatives, there should be an organizational review of quality for the existing information held in the collective datamarts that feed the central repository used for decision-making. Long before Big Data, the issue of Bad Data must be addressed.
Whether you are a B-to-B or B-to-C marketing entity, the creep of inaccurate data is constant across every customer and prospect contact you currently maintain. Experian-QAS has a stark reality “Cost of Bad Data” infographic showing the millions of dollars lost each year as a direct result of inaccurate and incomplete contact information. Complacency and budgetary shortcuts speed the process even more. Whether it is via an in-house effort or using third-party tools and vendors to perform ongoing hygiene, the vitality of your contact strategy is not sustainable without regular maintenance.
Once secure in the clarity and accuracy of your core data, you can move on to the integration plan for all of the additional goodies sprouting up from the Big Data seeds being sewn across every outbound and inbound marketing channel being utilized. But again, more planning and decision-making is critical before just jumping in and trying to grab every nugget. Perhaps the Fortune 50- to 500-level corporations might have the resources to take this on in one massive project, but I doubt that many small, mid or even larger brands can just dump everything into a pot and begin using the information gleaned into a successful series of campaigns. In a SAS/Harvard Business Review whitepaper I read recently; “What Executives Don’t Understand About Big Data,” this quote stood out to me:
“What works best is not a C-suite commitment to ‘bigger data,’ ambitious algorithms or sophisticated analytics. A commitment to a desired business outcome is the critical success factor. The reason my London executives evinced little enthusiasm for 100 times more customer data was that they couldn’t envision or align it with a desirable business outcome. Would offering 1,000 times or 10,000 times more data be more persuasive? Hardly.”
Having the foresight to develop phased approaches for data incorporation based on both short- and long-term ROI is the most realistic approach. Using results from the interim stages provides the ability to thoroughly test and analyze and measure value, keeping the project moving forward steadily while minimizing roadblocks to the longer-term goals.
My initial recommendation for the process would be along the lines of:
- C-Suite leadership establish the long-term goals for organizational success and with other Senior Management develop the phases to follow based on data, budget and resource availability to be assigned through each phase.
- Set the expectations and build the benefits case of the project across the entire company, communicating these goals in order to coordinate the gathering and availability of resources needed from whatever silo in which they reside.
- Design the KPIs that will be required in determining accuracy of marketing integration of the insights being introduced during each phase.
- Test and Measure every step of each phase for completeness and success before moving on to the next.
- Build simple and multivariate test panels into marketing campaign segmentation to analyze what new data elements truly provide sustainable lift in response.
I would love to hear your thoughts.