Forrester’s Laura Ramos implores B2B marketers to “make a date with their big data destiny.” It’s true that B2B marketers can’t brush off big data as a consumer trend. But they also must understand the limitations that are inherent in big data analytics.
The changing expectations of business buyers – empowered by mobile and social media – “presents big problems to B2B marketers” who are used to leading their campaigns with products and features, Ramos wrote in a blog post last week. B2B marketers “now find they need to fulfill these expanding digital expectations by getting closer to customers and knowing much more about them — a tough problem if access to, quality of, and practices around using customer data are underdeveloped,” she explained.
Ignoring important lessons
Economist Tim Harford goes a step further, suggesting that some of the statistical frameworks on which big data is built are flawed. “While big data promise much to scientists, entrepreneurs and governments, they are doomed to disappoint us if we ignore some very familiar statistical lessons, Harford wrote in an article for the Financial Times.
Harford says one of the myths of big data is the definition that “N = All” – in other words, when we have access to all data, there’s no sampling bias “because the sample includes everyone.” But that’s not quite true. “Big data sets can seem comprehensive but the “N = All” is often a seductive illusion,” Harford writes. ““There must always be a question about who and what is missing, especially with a messy pile of ‘found data.’”
As an example, he offers Boston’s Street Bump smartphone app, which uses a phone’s accelerometer to detect potholes as people drive around the city and uploads the data to a government server for identification and analysis.
“Solving the technical challenges involved has produced, rather beautifully, an informative data exhaust that addresses a problem in a way that would have been inconceivable a few years ago. The City of Boston proudly proclaims that the “data provides the City with real-time information it uses to fix problems and plan long term investments.”
Yet what Street Bump really produces, left to its own devices, is a map of potholes that systematically favours young, affluent areas where more people own smartphones. Street Bump offers us “N = All” in the sense that every bump from every enabled phone can be recorded. That is not the same thing as recording every pothole.”
Using big data to produce better insights will require “large strides in statistical methods,” Harford wrote. “‘Big data’ has arrived, but big insights have not.”
That conclusion is echoed by Dennis Kempner, president of Biel’s Document Management, in a blog post on AIIM.org. “The importance of data isn’t that it exists; it is what we are going to do with that data,” Kempner wrote. “Data analysis is useless if there is no one there to relate it to the company, the company’s mission and what consumers are looking for.”
Beyond basic profiling
Where will these insights come from? B2B marketers, Forrester’s Ramos wrote, must be “willing to go beyond basic customer profiling to tap into the abundance of behavioral data and firmographic insights found in conventional as well as unconventional B2B data sources.” Those sources include Internet browsing, search, smart device usage, content consumption and business community social activity.
“By analyzing the footprints that their best customers leave behind, B2B CMOs can more accurately map their journeys and use technology … and analytics to predict where the next best business opportunities will show up,” Ramos wrote.
As long as they understand the inherent gaps and potential biases in the data they’re collecting. “The data are bigger, faster and cheaper these days – but we must not pretend that the traps have all been made safe,” Harford wrote. “They have not.”