What Organizations Need To Know Before Jumping On The AI Bandwagon
By Gary Saarenvirta, Daisy Intelligence
Today, offering WiFi access is so ubiquitous that seeing an ad for it seems odd. But check out the window of your local coffee shop and you might still see an old, fading sign that says, “WE OFFER FREE WiFi!” Exclamation point and everything.
By now, merchants know WiFi is an expectation, not a value add. But when WiFi was first introduced, it represented a new form of retail one-upmanship.
You can always introduce products to outflank the competition or renovate a store with shiny new shelves, but WiFi was different in that it was something consumers could not see, hear or feel. But it was transformational.
Artificial intelligence (AI) is similar in that it is invisible, impactful, and transformative, but retailers should pause before jumping on the bandwagon. According to a forecast by market research firm IDC, retailers will spend $5.9 billion on AI tools this year. Throw in the fact that the term “AI” is the technology du jour, if you will, and it’s easy to understand the urgency with which CEOs are questioning their AI strategies — and examining whether or not they even have one.
However, just because a benchmark for deployment exists doesn’t mean every retailer needs to jump on the bandwagon and implement a new technology. Companies have their own specific goals around revenue, profit margins and expenses, so decisions and ROI should be calculated based on those goals.
Next, let’s consider what AI is. It’s often used to describe everything from basic predictive analytics (where historical data is used to guess what might happen in the future) to chatbots on an e-Commerce site. Recent research, however, suggests AI based on reinforcement learning is the technology that will truly make a difference in complex environments like retail. By conducting experiments, reinforcement learning identifies what to do based on the results in a trial-and-error fashion.
Finally, and possibly most importantly, AI isn’t something retailers can just go out and buy like other technology solutions. Identifying and/or building a custom-made AI solution tailored to specific business needs is complex and needs to take into consideration the desired outcomes, and your competitive landscape.
Confusion around an emerging technology is not new. Remember virtual worlds like Second Life? Retailers were encouraged to set up shop there, but it’s practically a wasteland today. Think of mobile apps as well. Should every retailer have one? Some experts suggested it at first, but today retailers are encouraged to maintain a solid, informative, mobile-ready web site instead.
The AI Use Cases Retailers Should Consider
To gain a competitive advantage through AI, take inspiration from your smartest customer. You know the one — the customer who seems to have done a lot of research before they come into a store. And even once they have a product in their hands, they have specific questions about how it will work in the context of their daily lives. You know they’re likely to make a purchase, but their meticulousness means they are more likely to recommend your store to family and friends if they have a good experience.
Investing in AI is similar. Take the specific situations and questions asked by your smartest customers and consider them your “use cases.” Instead of jumping on the AI bandwagon out of fear, what are the areas within your company where AI can do things humans could never do, even if you hired an army? Do you have data on which business recommendations and decisions can be made using sophisticated analysis and interpretation? If so, there’s an opportunity for AI.
Once you find the right AI use cases, everything else follows — from the specific companies to work with to the way your processes and compensation packages will be adjusted. Examples of the best AI use cases in retail include promotional product selection and pricing.
When it works well, true AI — which has been deployed to deliver optimal benefits for retail environments — isn’t technology that consumers will notice the way they came to look for WiFi signs. That’s because AI automatically and transparently improves the retailer-customer connection — and the bottom line.
Gary Saarenvirta is Founder and CEO, Daisy Intelligence, leading the development of the company’s AI platform that transforms massive quantities of consumer data into profitable decisions. A preeminent authority on AI, Saarenvirta works with leading global corporations to drive revenue and growth. The former head of IBM Canada’s data mining and data warehousing practices, he also led Loyalty Consulting Group, providing analytical services for one of the world’s most successful coalition loyalty programs, the AIR MILES® Reward Program. Saarenvirta holds a B.A.Sc. and M.A.Sc. in Aerospace Engineering from the University of Toronto.