You're Overlooking Half of Your Customer Data
AI-enabled unified systems offer a more holistic understanding of demand, author says. More than half of retail supply chain executives say they spend too much time making sense of data, but AI is here to change that—and everything else.
December 30, 2019
![customer data customer data](https://eu-images.contentstack.com/v3/assets/blt58a1f8f560a1ab0e/bltb684cdab24df064c/669eebfd73512fb2f5b0566f/customer-data_1577727506.jpg?width=1280&auto=webp&quality=95&format=jpg&disable=upscale)
We’ve all heard of the proverbial “glass half full.” This idiom suggests that it’s simply a matter of perspective as to whether a given scenario is good or bad, and that your level of optimism will inform your next steps. You may feel hopeful if you hear “that’s actually not half bad” when proposing an idea. Or, you might be willing to place a bet if you know your odds are 50/50. But “half” is not always good. You wouldn’t bake a cake with only half the recipe.
But here’s a scary reality: Most grocery retailers only understand one-half of a customer. In a hypercompetitive industry with more data to leverage than ever before, if you operate with a partial understanding of customer behaviors, motivations and preferences, optimism won’t get you far. It takes more than a healthy dose of hope and enthusiasm for retailers to forecast, plan and execute well if demand in fresh departments is not connected to center-store strategies.
So how did this partial understanding come to be, and how can you achieve a more holistic understanding of demand?
Disconnected Systems Keep One-Half of the Customer Equation Hidden
Retailers today leverage “fresh” as their competitive advantage in an e-commerce environment, but the prominence of fresh changes the nature of what occurs throughout the rest of the store. If customers are buying more produce or grab-and-go meals that means they’re shopping more frequently. That’s a win for retailers to see more of a customer throughout the month, but the transaction size each time is likely smaller, and they’ll be buying less frozen, packaged, boxed or canned goods. Retailers must be aware of these shifting dynamics.
Many organizations today operate with disparate demand replenishment systems. Even with best-of-breed center-store solutions, retailers are perplexed to find that forecasts are often incorrect; the predictions don’t line up to actual demand or sales results. That’s because most demand systems cannot understand the significance of increased fresh demand and how it affects the center store, plus how it ripples across the entire retail value chain. Planning, assortment, pricing, promotion and replenishment … each of these areas suffer.
By only understanding half of the consumer, you only understand half of the items that are relevant and important to them, and therefore, only half of the demand. But there’s a way to attain that big-picture view, through unified systems powered by artificial intelligence (AI).
AI Provides a Unified View of One Customer and Therefore All Customers
AI and machine learning can perceive all impacts to storewide demand, and I’d even venture to say that you cannot achieve a full understanding of consumer demand without these technologies.
Currently, 52% of retail supply chain executives say they spend too much time on data crunching—AI and machine learning solutions overcome this. Demand systems should also include machine learning, which drives continuous improvement of demand and forecast accuracy.
AI can leverage massive sets of information from all sides of consumer behavior to help you understand the full picture. It allows you to track every movement and trend to shed light on who your customer is and what they want out of their retailer relationships. And when applied correctly, AI alleviates inconsistent inventory buys, overstocks (and the resulting markdowns), out-of-stocks and margin erosion. To grow profitably, your demand planning and forecasting systems must contemplate all the demand, across categories and departments, and that can be easily done through AI.
Retailers who are on the right path are differentiating themselves in the market today through fresh and prepared foods. While customers will continue to be a moving target that grocers need to strive to understand, the even better news is that there is a way forward to achieve greater understanding. Acquiring AI and machine learning capabilities will improve your end-to-end supply chain—spanning categories and grocery departments—and bring a more complete and actionable knowledge of today’s retail disruptor: your customer.
Patty McDonald is global solution marketing director for Symphony RetailAI.