Retail is changing fast. Forcing us to modify the way we gather consumer insights and alter the way we streamline them into our business strategy.
Today, more than 84% of consumers start their purchase journey in the digital realm. They are interacting with the product at multiple touch points, every day, and leaving behind them heaps of insights, regarding what they want and what they need.
The risk of solely relying on these methods is that they use up a lot of time and money, and until the data is collected and processed it is already obsolete. It also suffers from human bias and error, and often requires constant consumer participation.
Digital sources used to understand consumers minimize most of the risks traditional methods posed. The data is available in real-time. There is no human intervention, and therefore no human errors. There is no need for ceaseless, active consumer participation. Everybody is participating, by default. And it is all executed on a global scale. Lessons can be easily learned and shared from one location to another.
But, monitoring consumer intent from the digital world manually is probably not going to work. The amount of data is enormous and the complexity of the data available is convoluted.
Thankfully, AI and machine learning technologies are here and they are at a fully operational stage. With the help of advanced tools, all the sources can be connected together to produce relevant consumer insights at a high scale and simultaneously share them across different locations, worldwide.
And above all, we need to make sure these consumer insights are new, relevant and actionable.
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