Convinced that huge levels of COVID-driven FMCG growth in many countries were masking a larger, fundamental change, a team of Nielsen data scientists dug into the data to understand the nuances underneath the broader retail data. And they were right.
Pandemic-led shifts to further online adoption and an increased focus on neighborhood and small-format stores have become an ongoing normal in China's rebound from COVID-19.
The stores we shopped in yesterday are not the stores we are shopping in today, and unlikely to be those we shop in tomorrow. There is no longer a need to squint … our data scientists have brought this phenomenon into plain sight.
Some of the highest revenue-generating grocery stores in the world are facing sweeping changes to their customer bases and their ability to deliver value to brands as people change where they shop—a change that, for some, may be permanent.
You don't have to look far to see rapidly growing or already mature 'disruptors' in retail and manufacturing, but the long tail of market disruption goes way beyond that in today's age of consumer disloyalty.
The data generated by our day-to-day activities can help brands and marketers understand consumer needs and drive growth for their businesses. But first, they need to make sense of all the data.
AI is enabling companies to better understand how consumers are shopping, why they shop and most importantly, predict what consumers will buy in the future. This is fundamentally shifting how companies explore product development cycles, pricing models and understandings of how to change the minds...