Why Retail Needs to Pay More Attention to Data and AI
A few weeks ago, Target CEO Brian Cornell described innovation pilots as "nice little experiments that distract the organization." His focus at Target is finding ideas that stick; technology that can sustain scaling across their stores, employees and customers over time. Although Cornell's comment rubbed some retailers the wrong way, he made an accurate point: there's too much testing and not enough long-term learning in retail today.
We're at a place where the store of the future is here and every headline introduces a new technology to master. From augmented reality (AR) to virtual reality (VR), to artificial intelligence (AI) to natural language computing (NLC), retailers are constantly distracted by chasing the shiny new toy. What most don’t know is that none of these acronyms work without one simple building block: data unification.
If you ask anyone about the 2002 futuristic movie "The Minority Report," they'll probably remember the iconic scene at the GAP when Tom Cruise’s character interacts with a store associate hologram to purchase an item. Today, that's not only possible, but it exists in locations all over the world. The wow factor of this technology is what drives the initial investment, but it rarely sustains it over time. The disappointment comes when those great visuals aren't equipped with the right back-end connectivity that can make them personal and transactional. Business owners must find new technology that's measurable and can drive business results.
So many of these innovations are handicapped because their visual capabilities outpace the data availability. Even with advanced analytics available to every retailer, it's still rare to find data organized and structured in a way that can be used. The merging of data, such as purchase history, recent web searches, items returned and why exist in data silos that prevent decision makers from seeing the total impact of their innovation investments.
While data is the downfall of traditional retailers, it's the foundation by which Amazon.com's power is built. Amazon will win because its structured data not only powers its e-commerce personalization, but also informs every business decision the company makes as it enters the brick-and-mortar arena.
However, what legacy retailers forget is that they're sitting on a gold mine of data from their stores, seasoned employees and customer interactions. I've sat in many meetings about this precise topic and I’ve had to remind these legacy retailers why they can still win — through their physical scale and human connection.
If you're one of these retailers, I suggest using these three steps to begin your data unification:
- Invest in creating data streams that business stakeholders can understand and use. Take a look at your data warehouse. Do you know what’s in there?
- Identify your data black holes. What are all the data points about the customer that are required to power new technology in the long run?
- Look for new technology that can fill these data black holes for you easily.
It’s not too late to start these steps today. With the presence of AI and machine learning, gathering, sorting and consuming data is easier than ever. Once this data door is unlocked, it will enable retailers to deploy new tests, gather insights through deep learning and prove returns on investment. This is exactly how little experiments turn into long-term solutions.
Don White is the CEO and co-founder of Satisfi Labs, a company that creates end-to-end artificial intelligence solutions for enterprise brands.
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