Analytics evolution creating changes for market research
JANUARY 5, 2012 – Although the purpose of market research has remained the same for many years – essentially, to understand what makes consumers tick and how they make the decisions they do – the tactics for achieving that insight have changed drastically.
With new developments in technology and data collection, it may be time for marketers to “radically rethink our approach,” Stephane Hamel writes for Online Behavior. He says the analytics model resembles a triangular cycle, with business feeding into technology, which leads to analysis, which points back to business purposes.
Rather than looking at analytics as a continual push-and-pull between the IT and marketing departments, Hamel argues it should be seen more like a three-headed beast, involving the points on the triangle.
The first step when integrating analytics into the company, he says, is to determine what the business goals and strategies are.
“In a perfectly mature organization, those would come directly from the business stakeholders,” Hamel notes. “The reality is, most often, you need a business analyst to ‘translate’ and bridge the gap between business considerations and something analysts can work with.”
Once the leadership has figured out exactly what it wants to achieve with data analysis, it’s key to understand the technology that will be used to gather those facts and figures. It’s not enough to simply shrug off responsibility for the project to the IT department. Make sure there are a few team members who know how the tools work, as well as those who can follow the workings of the website, the connections between the site and the back office, and how the online operations affect data collection and SEO, he says.
Finally, after gathering everything, the analysts have to come in. Process the raw data and turn it into useful statistics that can help solve problems and enable the decision makers to arrive at actionable conclusions that can inform development of a new product, the design for an upcoming marketing campaign or some other business strategy.
While this may seem like a fairly straightforward, albeit labor-intensive, process, there are several challenges that often go overlooked. Kim Davis outlines some of the “no brainers” and the areas that need improvement in an article for Internet Evolution.
Business analytics professional Alberto Roldan told Davis that there would be three major issues in the industry over the coming months, including a high demand for employees who have analytic skills. Additionally, IT departments and organizations will have a hard time meeting the demands of analytics projects, all while companies continue to refresh and improve their “predictive models and business segments,” Davis recounts.
She also notes that she hopes to see more businesses exploiting their transaction data and integrating decisions with social media, as well as the retail, healthcare, energy, CPG and banking sectors relying more heavily upon advanced analytics.
“Use of analytics to monitor the social media feedback loop is indeed going to become essential for any enterprise which has any kind of outward facing relationship with its market,” Davis predicts. “Not only will enterprises need to turn around analytics projects within a matter of a few months; they will increasingly see the value of getting as close to real-time analytics as they can.”
However, there are a few developments that Davis says will be unlikely to happen in the very near future, such as integrating voice recognition and natural language software.
One thing is certain, she says – businesses that hope to effectively and efficiently make data analytics part of their strategies will need to beef up their in-house resources and have those employees leading any data-based projects, even if some of the grunt work is outsourced to third parties.