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The Role of Search in the New Age of Commerce: Insights from Shoptalk

The Role of Search in the New Age of Commerce

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After a whirlwind week at Shoptalk, one thing is clear: we’re entering a new era in commerce.

The world’s largest conference for retail and commerce was brimming with technological innovation. Leading retailers like Macy’s, Nordstrom and Target took the stage to talk about how technology is bridging the gap between brick & mortar and digital stores. The days of segmenting the conversation between in-store and online sales are numbered. E-commerce is just commerce. Five years from now, if your kids are hanging out at “the mall” it will look nothing like the physical mall you and I grew up with.

As retailers look to reinvent their businesses, it is evident that there is no fixed formula for success. It’s also clear that enterprises are not looking into a singular reinvention event, but investing in a constant process of innovation based on obsessive data and customer experience analysis.

Within this framework, the power of search is being reexamined. E-commerce search was a heavy contender for the spotlight at Shoptalk and rightfully so. Search is a touchpoint within the customer journey that has largely remained unchanged for 20 years but is now being redefined, in terms of function, scope, and channel.

The role of search

In this new age of commerce, search is everywhere. Your customers are searching for products online before they decide to visit your store. They’re trying on clothes in physical stores to later search for the item in your digital shop to see if it’s on sale. Store clerks are leveraging search in-store to filter through inventory and provide better customer service. So we can conclude that search does play a prominent role in revenue generation, both for online and brick & mortar purchases. Yet, currently, search results on most e-commerce sites leave much to be desired.

Case in point- I set out to search for ruby slippers (disclaimer- I’m a father of two little ladies and Wizard of Oz plays on repeat in our home), and received the below results. How come?

In simple terms- most search engines treat a query as a set of keywords. Thus, when a shopper searches for a specific item, the engine will set out to retrieve all products whose description contain those same keywords, without distinguishing whether it’s a book title, a brand name or a lipstick color. This approach leads to poor recall and precision- which in turn, means low chance of a sale.

While software can identify items in general, it doesn’t have the built-in knowledge humans have. To solve this, artificial intelligence and machine-learning methods can help search engines tap into understanding. To ensure shoppers retrieve the kind of products they’re looking for, site search must be driven by knowledge and not just by keyword matching.

Jack of all trades versus Master of e-commerce

In fact, the future is already at your doorstep. Twiggle provides this kind of knowledge-based search to leading retailers. We’re also not the only ones who believe in this approach. Google, my alma-mater operates a knowledge-based search. If you attended ShopTalk, you presumably looked up the weather in Vegas and received a relevant response in the “Knowledge Graph box”.

But there’s an important difference between us. Google tackles knowledge by breadth- its Knowledge Graph gathers information about people, places and things from a variety of sources. The jack of all trades of search, the graph covers a great many topics, from the weather report to the biography of Russell Crowe.

In contrast, Twiggle operates on a deeper, conceptual level exclusively for e-commerce, processing products as a concept, documenting their attributes and their context. Twiggle’s Knowledge Graph is specifically designed to represent the world of consumer products and masters a deep understanding of the things people search for and want to buy. It indexes all the products in an online shop to easily recognize and display relevant products when a consumer asks for them. Twiggle’s understanding will therefore retrieve ruby slippers, that specific kind of sparkly, red shoe, worn by Dorothy to magically transport her back to her hometown of Kansas.

Context is key

Take something as simple as a shoe. You and I understand that a shoe is an item of footwear, intended to protect and comfort our feet. We know that some shoes are designed for specific purposes, like ski boots or dancing shoes. And that they can vary widely in style and cost. Some shoes are made of leather, others of rubber. All of this is context that helps us understand what we want, and what to ask for when we’re shopping. It helps a shop assistant offer better service that in turn, ensures higher odds to make a sale.

Twiggle’s rich ontology gives a search box real-life context for the word ‘shoe’ so it can deliver the most relevant results. And this kind of understanding infuses your customer journey with broad, deep and structured knowledge.

So when shoppers search for specific products, the search engine can rely on Twiggle to break down the query with natural language processing and analyze both structured and unstructured product data. Our Knowledge Graph enables both these processes so as to display the most relevant products to match the consumer’s query.

How can you talk if you haven’t got a brain?

As trends evolve and digital solutions continue to develop, one thing remains the same- consumers are the heart of commerce. And I believe, the best way to engage with them is when they initiate conversation. That’s why I know search will become the brain of e-commerce, a kind of network that connects the items shoppers wants to buy, with the products you want to sell.

Conversational commerce will then be something entirely within reach. With the power of a deep e-commerce Knowledge Graph, technology will have enough of a brain to intelligently respond to consumers. Thus, voice search is the catalyst that returns freedom of expression to the consumer and shifts the responsibility of understanding to technology.

It won’t be as easy as clicking our heels together three times- but Twiggle’s Knowledge Graph takes a huge leap towards the end of the yellow brick road. We’ve made search more intelligent. We’ve built technology that helps machines understand what shoppers say and what they mean. And that cultivates trust, loyalty and perhaps even a little bit of wonder in the customer journey.

The above is an expanded version of my presentation at Shoptalk.

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