When it comes to online shopping, Alexa is one of the widely used machine learning-based conversational interfaces. While many of us love to ask such tech interfaces to better understand our needs, most merely cannot handle conversation beyond one or two questions. In other words, we’re beginning to see the indicators of where the machine starts to “understand” human senses.
Senses-based discovery — visual, voice or touch — isn’t just a scene from a sci-fi movie. Today, we’re closer than ever to marrying human senses with machine learning to enable truly personalized virtual shopping. With natural language processing becoming more and more common, what will the next iteration in the humanization and democratization of artificial intelligence (AI) mean for both brands and consumers? One thing is clear: choices to consumers will exponentially increase, creating high demand for technological innovations to understand shoppers’ needs. In this exciting evolutionary journey of retail, online and offline experiences have already started to mimic each other.
As the online and offline worlds start to resemble each other more and more, recreating the in-store experience as closely as possible online is every e-commerce site’s dream. The best personalization is knowing what a single, specific customer wants, the same way an offline boutique knows their customers extremely well and caters directly to them. Today, that type of personalization can be experienced online with just a few clicks.
Merchandising web pages based upon the way an individual customer interacts with a product in-store creates a more relevant shopping experience with higher conversion. AI-powered discovery tools can profoundly aid in personalizing the customer journey and enable the site to be more “human” in presenting choices that the consumer really wants to see. However, we still have a long way to go to understanding human senses in online shopping the way a sales associate can ascertain in an offline shop.
One of the areas of innovation getting quite a lot of attention is understanding visual senses. In the tech world this is often referred to as visual discovery, which is rapidly becoming more widely available. Visual discovery allows shoppers to find what they want by sharing an instant image click from their live environment. No one could imagine even five years ago the sheer volume of choice that consumers would be faced with today.
For example, say you’re at lunch with a friend and you really like her blouse. If you were simply to search “blouse,” literally hundreds of choices would be thrown at you, quickly causing frustration and search abandonment. Now imagine that you had taken a photo of your friend’s blouse, then uploaded it onto the site. If it were visual search-enabled, a highly curated selection of blouses that look like the one in the photo would be presented. This isn’t uncommon for the likes of an Amazon.com shopping experience, but such innovations need to be widely available to all retailers.
Where are we headed as an industry in terms of understanding consumers’ interactions with an online shop? A personal hypothesis is that we will move to multi-query searches. All search engines today are single query. However, when the search engine comes back with questions about that blouse — e.g., what color, what size, what price range — that’s when the search engine will be able to drill down quickly to present the exact item consumers want at that moment.
The word “my” is the key to personalization. When you’re a frequent customer at an offline boutique, and you tell the sales associate — who knows you well — that you’re looking for a birthday gift for “my” daughter, you would be presented with hyper-relevant choices. Replicating this offline experience online is the height of personalization. Today, consumers are treated as look-alikes, being shown products based upon a basket of similar consumers’ previous purchases. With the visible end of third-party cookies in the coming years, I think we will see all websites humanizing the approach to their customers by treating each one as an individual based upon their behavior on that site.
The best piece of advice for small to midsized retailers — online or offline — is to know your customer as well as possible. Even if you don’t have tools such as AI-powered discovery engines, I would highly recommend that you capture every interaction your customers have with your brand. Keep it simple: understand your customers. If you try to copy Amazon, you’ll fail. But unlike Amazon, you have a greater luxury to understand your customers because you’re much more personal to them. The more you understand them, the more you can drive a truly personalized experience.
Nilay Oza is the CEO and co-founder of Klevu, a powerful and extensible e-commerce search solution that delivers search results based on shopper intentions and behavior, in real time.
Source: https://www.mytotalretail.com/article/the-future-of-personalization-marrying-human-senses-with-machine-learning/
