Imagine the most efficient salesperson at your favorite store and how well they predict just what you would like to buy. Now imagine the same efficient salesperson, except it’s not just you she knows about — she knows about thousands like you and helps each of those yous with just as much precision. That’s an exceptionally watered down, oversimplified version of what personalization and AI mean to the ecommerce world. And if you’re competing with the Amazons of the world, that clever algorithm is your best friend. It isn’t good enough to be the one with the best products. Not anymore, at least. You also need to ensure that your products are easily discoverable as well. Advanced machine learning and intelligent algorithms capable of understanding and predicting shopper behaviour make this possible. But the challenge lies in incorporating that intelligence while understanding that you’re dealing with real human beings just like you, who think like you and shop like you. How can we ensure machines are clever enough to be just the right amount human? The Real Deal About Personalization Brands that create personalized experiences — through AI and other advanced technology, see a six to ten percent increase in revenue as per research conducted by Boston Consulting Group. 1:1 personalization akin to what Amazon and the other big players boast of require heaps of data about each individual customer. However, such targeted personalization only works for under 25% of the shoppers. And even for those shoppers, a simple change in behaviour or device would impact the recommendations they would see. What is possible — for the remaining 75% and a vast majority of online shoppers, is personalization based on segmentation. Understanding aspects of shopper behaviour such as where they are located, their device preference, number of visits to the site etc. help understand what products would make most sense to them. Help Shoppers Find What They’re Looking For I’ve often heard the word ‘intent’ pop up in marketing discussions. It made me wonder about intent in the context of ecommerce and what it would mean for an online retailer. After some soul-searching and stares-out-of-the-window, I arrived at an interesting analogy. Strong search is the clever merchandiser’s attractive window display, relevant recommendations are the capable salesperson’s suggestions, and easy navigation are the broad comfortable aisles you amble through in a brick-and-mortar store. Successfully recreating that experience online is what decoding customer intent is all about. Online retailers need to ask themselves two questions:
or and Machine.
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- How well can I gauge intent when a customer lands up on my site?
- How well am I able to cater to the perceived intent of the customer?