Want a shirt you saw someone wearing on social media? Bingo! It’s yours. Realize you are running out of coffee filters? You yell out an order to Alexa and voila! They are en route. There is name for this type of online interaction: contextual commerce, which is online retailing that makes it possible for consumers to buy in the moment as they scroll through unrelated content or are simply going about their daily lives. According to Eli Finkelshtey, CEO and co-founder of Constructor.io, "Contextual commerce is the idea that consumers should be able to buy whatever they want, wherever they want, with as few hoops to jump through as possible.”
It's a good theory, but how easy is it to execute? A look at contextual commerce over the years shows the progress, admittedly in fits and starts, it has made. The earliest iterations of contextual commerce were retailers’ blogs, which used story-type content to support products that could be purchased on their sites. These proved to be successful but had the distinct disadvantage that they weren’t necessarily part of the flow of a consumer’s online life.
More recently, other channels have emerged that have been met with varying degrees of acceptance and success. Digital and mobile wallets have become commonplace and make buying-in-the-moment a snap. Other examples include technologies like the Internet of Things (IoT) — such as Amazon Dash — and voice search devices like Echo, which — although cumbersome — can order products in the moment.
A Technology Story
But true context commerce — such as when you see a blouse on Facebook and can make it yours within a few clicks — can be surprisingly difficult to achieve without a brand seeming to deliver a hard sell and without making the consumer click too far outside of the original content.
That is because, as Finkelshtey said, "There’s no single underlying technology for contextual commerce — it’s more a philosophical idea that can be achieved through different types of technology.” But with any philosophy there are usually practical real-world implications that present a challenge.
For example, scale is a big issue for retail brands using contextual commerce, said April Mullen, director of consumer-first marketing adoption at Selligent Marketing Cloud. “Most brands have built themselves to get up and walking with AI technology for contextual commerce, but rarely can those brands go from walking to running. Delivering seamless, personalized experiences at scale is going to be a big hurdle, but not an impossible one.”
On the back end, there are numerous systems a retail can harness to connect with consumers. “Any multivariate platform like Rich Relevance, Optimizely or Maxymiser can associate content with a shopper’s context,” said Chris Haines, director of consulting at Amplience. But there are challenges with contextual commerce, he continued, namely that none of the leading ecommerce platforms are built to handle content — or any non-product data for that matter. “As a result, retailers have to shoehorn content into the shop flow using cumbersome and inefficient workarounds, making it a square peg in a round hole.”
Haines said that the ideal solution is to use purpose-built technologies such as headless content management systems (CMS) that can deliver content to multiple locations simultaneously. “This requires a modern, microservices approach to a brand’s tech stack,” he said. “Once it’s set up, a headless CMS can publish directly to a platform like Salesforce Commerce Cloud without requiring any manual effort.”
Artificial intelligence also plays a significant role in the better executions of contextual commerce. "Almost all concepts in contextual commerce require AI to help detect important attributes about the context,” Finkelshtey said. “If, for example, you want to buy a shirt you saw on social media somewhere, some machine vision algorithms would help detect and offer up that shirt and other shirts like it. If you ask your Alexa to buy more coffee filters, it would use AI for speech recognition to convert your speech to text, then use AI with Natural Language Processing to understand the intent of your sentence is to buy more of the coffee filters you previously purchased, and then more AI to understand which specific brand of coffee filters you might mean based on your purchase history.”
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The Onset of 5G
Many of these issues could be solved when 5G becomes commonplace, according to Robb Hecht, adjunct professor of Marketing at Baruch College in New York City. At that point, the integration of AI and the Internet will increasingly be accessed through IoT like Alexa, as well as new rollouts in our refrigerators or TVs, he said. “In the online buying process, speed is king, as as 5G rolls out making the Internet and commerce transactions faster and more seamless, e-commerce retailers are going to feel increased pressure to shorten the cycle between user engagement and customer purchase,” Hecht said.