Learning to pivot when your assumptions are off target

A leading provider of market research and advisory services came to 3Pillar Global looking for help with what they assumed would be a data visualization engagement for three of their core market research platforms. The platforms were slowly losing customers and bleeding revenue. The company’s goal was to retain their existing customers by making the vast amounts of data available in these platforms more accessible and useful.

Users of these products typically work for large corporations like Amazon, Walmart, and eBay. This means the data and insights they’re looking to derive are highly specific and context-driven, like iPhone purchasing trends in Eastern Europe or electric vehicle purchases in North Carolina. The market research company wanted to take advantage of emerging data visualization tools to give users an intuitive way to digest and quickly grasp platform data and insights, then share it with colleagues, up to and including C-level executives.

“I’m so proud and pleased with what we’ve accomplished. Your work and dedication to the customers & the vision is remarkable. Our business results continue to improve & our future looks even brighter. Each of you is key to our success. Keep up the great work & push us to do our best.”

– VP of Product Development, Leading Market Research Company

Through successive rounds of user interviews and prototypes, we helped the company peel back the layers of product features and functionality to uncover their users’ real needs, rather than what they thought were their needs. Unbeknownst to the organization, users often only wanted or needed specific slices of the datasets from the platforms. Other times, they sought to aggregate data from multiple reports or combine it with reports from different vendors and/or their own internal datasets. This meant users regularly exported data out of the market research platforms and into external tools like Excel. There, they would filter and manipulate the data to fit their needs before using those external tools to perform any kind of data visualization.

In short, while adding data visualization capabilities to the firm’s platforms seemed like a slam dunk, we quickly uncovered that there was much more to their users’ needs than met the eye. That being the case, introducing this new functionality to these products was unlikely to do much, if anything at all, to improve their existing customer experience and stem the bleeding of customers and revenue.

The user interviews, assumption testing, and prototyping we conducted not only prevented the company from building features that their customers wouldn’t use, it helped identify which specific product functionality would be most valuable to them. We recommended that they build an aggregated data view first, which allowed users to consolidate data from multiple reports on-platform as well as ingest their own proprietary data, and then filter the aggregated data as needed. This approach kept users on the company’s market research platforms rather than requiring them to manually massage data in Excel.

Undertaking our Product Validation offering and allowing us to help guide important product investment decisions with real financial implications proved to be a win in more ways than one for the market research company. Thanks to our recommendation to build the aggregated data view first, we ensured the company met a pressing, previously unspoken customer pain point. Only once that higher-order need was fulfilled could the value of the data visualization they originally sought be realized.