Credit by : Daniel Newman
Before getting into this year's trends, I want to go over some of the hits and misses we chose for 2019. While we did see major and necessary improvements in omni-channel retail and AI/cognitive computing, I’d say we still have some work to do with cardless checkout and smart beacons. Yes, those technologies are still percolating and will likely continue to mature in the coming year. But for 2020, I see some more significant trends moving the industry forward.
2020 will be the year where it is virtually unnecessary to see, feel, or test a product in person before you feel confident enough to buy it, thanks to augmented reality. We recently saw Toyota launch a new AR program that allows users to try out 10 of their cars without ever picking up the keys. Just as importantly, in my opinion, consumers didn’t have to download an app to try the experience-something that can be a huge deterrent for those of us burned out on downloading apps just to see if they’re worth downloading. Toyota is not the only company using this feature--far from it. Companies like Target, Lowe’s and Amazon have found that augmented reality may be especially helpful in decreasing the number of returns they see from online shoppers. Indeed, while e-tail will hit $5 billion in value by 2021, it is estimated that 25% of purchased items are sent back. Augmented reality could mean retailers keep more of their sales because consumers more fully understand what they’re buying at point of purchase. Technology in this area is also catching up as companies like Microsoft launch second generation augmented reality headsets, which is one of many newer, lighter headsets and wearables that will make AR more immersive for retail customers and employees.
Now, Now, Now
Amazon Prime taught us that shoppers are no longer willing to wait more than two days to receive their products. But Amazon’s recent shift to free one-day shipping shows that they’re getting even less patient. Studies show that 88% of consumers are willing to pay for same-day (or faster) shipping. We can see from the rise of apps like Instacart and Shipt that people are drawn not just to the convenience of grocery delivery, but the ability to get what we need in two hours or less. GrubHub and UberEats have made eating out and eating in both fast and ubiquitous while Amazon Prime Air even promises delivery in 30 minutes or less!
Clearly, consumers are shopping at the speed of digital transformation and expect their products to be delivered just as quickly. I know I’ve personally abandoned my shopping cart when I realized there were no expedited delivery options available. The question now is whether smaller retailers will be able to keep up with the expense. Mom and pop shops: take heart. I can see the drive of small and large Amazon competitors leading to a stream of third party logistics companies expanding their immediate delivery services to help those smaller companies compete.
Make It Easy--and Personal
Today’s consumers don’t just want their products fast, they want to be able to get information about them quickly. They want to go to your website and be able to compare prices, styles, delivery dates, see your recommendations of things they may like even more--preferably all on one screen. That’s why AI is so important in digital retail. Consumers are constantly dropping hints at the types of things they like and want--and how much they want to pay for them. The savviest retailers will be gathering that information from endless sources like social media to IoT sensors and using AI and deep learning to make the shopping experience as easy and personalized as possible.
This is an important trend that will continue to come to the top of the list for at least the next few years. For CMO’s and business leaders, investments in advanced analytics platforms that can leverage the power of machine learning and AI is critical to retail success. I’ve seen examples like Chico’s utilization of SAS for advanced retail analytics that allowed the company to consolidate omni-channel customer data in 2 hours rather than 17 hours enabling more rapid delivery of timely offers and less stress on infrastructure. While this is one good example of putting advanced analytics to use to personalize retail experiences. It is also part of a bigger story that implores retail companies to make the investments in analytics and AI tools that allow them to know customers better and deliver better offers, in the right channel at the appropriate moment. This trend will only be further zeroed in on by the best retailers in the future.