Collecting it isn’t enough – loads of organizations have piles of data gathered over years and years that just sits there, waiting to be harnessed. Analyzing it isn’t enough – insight is of no value sitting in some silo. Nor, in today’s fast moving markets, is data-driven intelligence delivering its full value when it doesn’t hit the desk of someone in a position to respond until six months after the fact. The true value of big data isn’t realized until it gets placed into the hands of those who can understand what it means and will do something with it.
That’s the core insight delivered in a new Forbes Insights report sponsored by artificial intelligence solutions provider Rocket Fuel. Data-Driven Insights Are Only Part Of The Journey: The Best CMOs Take Action, illustrates how leading organizations are no longer simply exploring big data, toying with what it may or may not be able to accomplish. Instead, data pipelines and analysis are becoming fully operationalized to the point where they fuel not only strategic initiatives, but also daily or even minute-to-minute decision making.
Products and pricing
Consider Chobani, a company largely responsible for introducing Greek yogurt to the U.S. marketplace just seven years ago is now the $1.4 billion market leader. The company aggregates and analyzes what chief marketing and brand officer Peter McGuinness refers to as an “enormous” amount of data. It scours a wide range of sources to develop a clear picture of events in as close to real time as possible. That’s because, says McGuinness, “we ‘action’ the data so that it creates competitive advantage for us in the marketplace.” In other words the company mines its data for everything from strategic insights (what new products should we introduce?) to tactical decision making (what are our competitors’ prices this afternoon?).
Switch to packaged goods giant Unilever, where Global SVP Marketing Marc Mathieu says that today, “everything is digital.” The company, in fact, has enormous stores of data—and it is Mathieu’s belief that “data will change the way we market in ways none of us really yet fully understand.” However, he insists, companies need to think about data on “people’s terms.” That is, says Mathieu, “we shouldn’t think of data as a way for us to know more, but as a way to help people in the most positive and impactful way.”
A good example of turning this thinking into practical action is in hair care. Being a leader in hair care products, and noticing that hair is one of the most frequent searches among women, several years ago, the company built an online presence called “All Things Hair”. In addition, working with Google, Unilever developed an algorithm that would comb searches relating to hair in the hopes of discovering new trends in their early stages – before they might become waves. In this way, Unilever can stay ahead of the curve with both its product development/refinement as well as and the information it shares with virtual community. As Mathieu explains, this is another way big data can help drive “brand relevance” as well as “create individualized solutions to meet peoples’ needs.”
Another example of the practical applications of big data comes from UnitedHealth Group. According to SVP marketing and brand Terry Clark, the company has vast stores of data, “and not just marketing data but data about outcomes.” One of the key opportunities, says Clark, “is that we can take this data and use it to improve relevance and transparency in ways that can help consumers get the best health outcome at the best cost.” Using data to help consumers find the right information for their needs and make the right choices, and then doing the right things for these consumers, says Clark, “is the right way to grow and sustain our business.”
Data gets it done
The above companies provide examples where big data is actually getting things done. But quantitative research conducted for this report (a global survey of nearly 300 senior executives) suggests there’s much more work still to do. Specifically, just over half say their organizations do not fully understand who is engaging with their products. Precisely half say that they do not fully understand who likes or dislikes their products. And finally, nearly half of respondents say their company is wasting money in its marketing initiatives—a view particularly evident among insurance and healthcare executives and among CEOs.
That all said, the survey shows that performance against these objectives improves significantly among those companies with a strong understanding of big data. That is, those who “know” big data have far keener insight into who is engaging with or who likes/dislikes their products or services. They are also far less likely to feel they are wasting money on marketing initiatives.
It is also noteworthy that those with the greatest understanding in big data are significantly more effective in targeting customers. Across a range of media, including traditional avenues such as television and print but also across the digital and even out-of-home spectrums, those companies with a good understanding of big data score significantly higher relative to the overall findings. Meanwhile, those who “know” big data are also far more likely to pull more data from more sources (such as web, mobile, CRM or GPS) as well as conduct more rigorous analysis (such as the use of machine learning).
The CEO/CMO partnership
A unique element running throughout the analysis is its comparisons between the views of CEOs and CMOs. In some instances, CEOs have a more critical view of marketing performance than do CMOs. But in other cases, the roles are reversed. Overall, the report finds that charting a path for marketing in the digital age requires a close working relationship among peers from the C-suite. The good news is that the overwhelming majority of CEOs report a good relationship with their CMO—and vice versa. But again worth noting: such partnerships are significantly stronger at companies that “know” big data.
Overall, the report shows how pioneers are achieving breakthroughs in pushing data-derived insights into frontline processes. It’s not enough to collect and or analyze data. The intelligence must be put to practical use. In this regard, the case studies and survey findings provide a significant body of suggestions for others to consider.