Despite what you might have read, retail is not dying. Sure, brick-and-mortar retailers today face significant competition from their digital counterparts. But with the right omni-channel strategy, they can outperform online-only stores by providing the best of both worlds – the convenience of online e-commerce along with the human experience of physical stores.
Last week, Macy’s announced its new President will be Hal Lawton, a former eBay and Home Depot executive who is credited with building Home Depot’s stellar interconnected retail experience. Macy’s knows that the path to sustainability involves a unified online and in-store strategy and it has plans to expand its data analytics and consumer insights.
That’s because today retail stores are sitting on an enormous mound of customer and enterprise data, which includes point-of-sale receipts, online visits and purchases, warehouse inventory, and so on. And all of these data points are extremely valuable with the right data analytics strategy and technology in place.
Today retail stores are sitting on an enormous mound of customer and enterprise data and all of these data points are extremely valuable with the right data analytics strategy and technology in place.
In particular, AI assisted customer analytics has allowed retailers to know when to do what and where. As a result, a store can maintain optimal inventory levels and anticipate what a customer will want to look at on their next visit. It can also pair up a customer’s in-store and online activities to ensure a seamless customer experience and optimal conversion rate with each visit. Imagine, a sales representative having the most up-to-date customer information at their fingertips to help the customer determine the next best action.
It is these kinds of capabilities that will allow companies to stay relevant and win big.
If any of this resonates with you, tweet at me or email me to share your thoughts and experience with analytics.
Founder and CEO of Syntasa
Jay is the Founder and CEO of Syntasa (a Marketing AI Platform loved by Marketers, Data Scientists, and Data Engineers). For the past 12 years, he has been a successful entrepreneur, having started two high-growth companies. Jay also has over 20 years of professional experience in the field of analytics, data science, performance measurement & management, and strategic planning, having worked at several organizations, including American Express, TARP Inc. and Viant Corporation.