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...
At Nielsen, we have a clear view of open, one that is not ajar or a “bit more open.” To us, open means exactly that—open. We define open as the ability to use different parties and types of data, models to enrich and applications to consume and take action.
Granularity matters to marketers because it gives them the ability to distill huge chunks of marketing activity so that you can understand the smaller components.
With so many DMP vendors fighting to stand out, it’s no surprise that many marketers aren’t able to truly differentiate the competing solutions. And to be fair, from an eagle’s eye view, I don’t know that there is a way to.
Marketers today have more than enough data available to them, but they’re looking for better ways to use and connect their data sets to gain deeper, more valuable insights.
Digital adoption is sweeping the globe. The uptake of mobile devices and increasing access to the internet have huge ramifications for businesses in all industries. Retailers can’t afford to ignore this new reality.
There are many problems and challenges ahead of us. We also have many possibilities and options to wade through as we navigate the right way forward. It’s up to us to leverage the opportunities by adopting better strategies for using data and technology.
Data is everywhere. As our individual behaviors leave an ever-expanding data footprint, we are faced with the challenge of making sense of all of this data and extrapolating meaningful insights to drive performance.