Insights from the Retail Robotics and AI Conference and the Retail and Consumer Goods Analytics Summit. (Part 1)
“Data is the new oil” will be the “retail apocalypse” storyline of 2018. We will hear it – over, and over, and over again.
But unlike the apocalypse storyline – a shoulder-shrugging, sky-is-falling, backward glance at the past, data as oil is a forward-looking call to action.
In April, McMillanDoolittle sponsored Northwestern University’s and the Platt Retail Institute’s 2018 Retail Robotics and AI Conference. We followed that up by attending the 2018 Retail and Consumer Goods Analytics Summit. Combined with our strategic work in consumer insights, the internet of things, and immersive retail experiences, the conferences helped us coalesce some of our thoughts.
Retailers need a data strategy – how to capture it, how to use it, how to embed it within the culture of their organization. But more importantly, they need a retail strategy.
Clive Humby first coined “Data is the new oil” in 2006, after introducing retail to loyalty programs and data gathering with the Tesco Clubcard in 1993. A decade after data first became oil, Jack Ma described “New Retail” – including the linking of data from the digital to the physical world. Since then, Chinese companies have led the way in capturing and learning from data. After these companies, Amazon struggles to catch up (yes, we said struggles). And trailing Amazon, the remainder of US retailers wonder where to invest in data strategies.
The truth is that until there are massive disruptions that create access to and the interpretation of more and more data, “winning” on data alone is impossible if you aren’t an Alibaba or Amazon. That’s why data isn’t a strategy.
The winners in retail are, and will be, those that find the positioning that elevates them to the top of the consideration set. Today, data can refine that positioning to a level it never has before – this is the “quick-win” data opportunity. The “quick-win” incorporates new methods of capturing consumer insights, such as machine learning. It is an achievable and inexpensive step to fine tune your retail positioning utilizing new access to data. In turn, refining your positioning is the first step to developing your data strategy. More on that tomorrow.