Infotools' Executive Vice President, John Bird, recently had a two-part series published on ESOMAR's Research World blog called "The square peg in the round hole?" The articles considered the challenges that ensue when using business intelligence tools to handle market research data; suggesting ways in which insights professionals can ensure they choose fit-for-purpose technology to improve ROI and workflows.
After all, while such tools have an undeniable place in the modern enterprise world, it’s incumbent on business leaders to remain up to speed when it comes to their respective strengths and the weaknesses. All too often, wide-ranging capability remains underutilized. It’s also important to consider the data type being analyzed and to question whether a specific tool or platform is the right fit, he warns.
What’s more, the truth is that many business intelligence (BI) tools are not the best solution when it comes to attempting to get the most out of primary research data. Meanwhile, the costs of bespoke re-engineering can quickly mount, with complex workarounds also leading to delays.
John outlines the five common challenges for brands using BI tools for market research data – and shares how to tackle these.
“Chucking all sorts of datasets into a lake can see it quickly become a swamp,” he warns – especially in a world in which many BI tools are designed for aggregate and relational data but can’t process respondent-level data or multiple data inputs. Furthermore, it’s important to accomplish tasks such as examining weighted data, significance testing and processing multi-response questions.
He also stresses the need for automation when it comes to delivering necessary speed and accuracy.
Yet, fit-for-purpose technology which can improve ROI and workflows does exist. And, to this end - as John points out in the second article - insights professionals must ask important questions such as:
- Can it organize all my data - such as survey responses, online interactions, in-store shopping data, social media posts and qualitative interviews - while providing the deep level of detail I need?
- Can it ensure accurate insights by doing things such as weighting the data for representativity, quickly?
- Does it allow all team members access - boosting efficiency, buy-in and collaboration?
- Does it allow for sharing of updated insights to answer questions on the fly?
The key lies in leveraging technology that helps, rather than hinders, the insights process. Read the full articles here and here.
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