The customers have spoken: Three bad experiences with a brand and they’re done. In fact, 90% of consumers expect online shopping to be better than in-person shopping.
The e-commerce giants of the world, from Amazon to Alibaba, have set a high bar. Now, all customers expect the same level of relevant information and personalization.
The only problem is that 99.9% of companies aren’t Amazon or Alibaba. They don’t have the vast infrastructure, mountains of customer data, teams of data scientists or funds to draw from.
But I’ve found you don’t need endless resources if you want to build customer loyalty, increase cart size and improve conversion rates. You just need to create relevance. Here’s how.
Break down the elements of a shopping experience
Before you can create relevance, you need to understand the fundamentals of a shopping experience. Customers usually have a goal in mind.
When they walk into a store, the customer is on a mission to find the right product at the right price and if needed, they want to have someone answer their questions or to be inspired.
That could be, “is there another product that’s best for what I want?” or “is there an alternative at a better price?”
Understanding your customer helps you recreate a best-in-class experience virtually, by using Artificial Intelligence or another tool.
For instance, the AI you use—whether for product recommendations or to power the site search—should understand the customer’s shopping goal, or intent.
A customer who has already put an umbrella in their shopping cart probably doesn’t need another umbrella product suggestion, but they might need rain boots.
Customers like shopping in stores because they can easily see, navigate and sort through what they want. Online shopping should provide them with the same experience.
If they’re searching for a desk, and they ask about a “light”, you could infer that they are likely looking for a desk light. In the analog world, this is exactly what you would get.
Delight customers with relevance
Grocers have recently outpaced other retailers in the online shopping experience: They make it easy to find products. They recommend new products based on taste. They make it easy for customers to reorder favorite items. If a product is out of stock, they make a relevant alternative product recommendation.
This is a shopping experience powered by relevance. Even with web browsers removing third-party cookies, retailers still can create digital, personalized, relevant shopping experiences.
This is not necessarily new, but a digital shift; retailers already do this in the analog world. When you walk into a store, no one needs the personal history of a customer to create a good experience.
Instead, a retail associate is there to observe what items they are gravitating towards, help answer questions, or point them in the right direction. Retailers just need to look at this from a digital perspective.
AI can often be that virtual sales associate. We’ve developed an algorithm at Coveo that provides personalization as a consumer shops online even if they aren’t logged into your site. It thinks like a consumer or personal shopper and keeps an eye on how someone is interacting with the site.
It becomes a personal shopping assistant, making recommendations in the search bar on what product category a specific customer might want to peruse or what other items might be a great compliment to that backpack in their shopping cart all in real-time. It solves the cold-shopper or anonymous shopper problem.
Unfortunately, 50% of consumers still sometimes-to-always experience a problem when shopping online. They face problems with customer service, website navigation, search or even paying.
Relevance can help solve these issues and delight your customers as they find exactly what they need. AI-powered relevance can create personalization, improve browsing, highlight better recommendations, provide better search results—and more.
Create a better search experience
Without relevance, if a customer spells a search term wrong—they’ll find zero items or the wrong ones.
If they put in something too broad, they’ll get 5,000 items. If they search for “pants” instead of “trousers,” they might get widely different items if products are classified in American or British English.
If you were shopping in-store, none of this would be an issue. The sales assistant would know if you misspoke, could ask a quick follow-up question to narrow your search, and can likely recognize the difference between an American or British accent.
That’s why I fully believe search is the key way to create relevant experiences and meet customers’ high expectations online. An AI that thinks like a customer will be able to recognize a misspelled word.
It can tell based on how a customer interacts with the website what item out of the 5,000 they might prefer. And it can tell whether you use American or British English on your web browser.
When sites improve their search, customers will reward them: the basket size goes up, the conversion rate increases, the time spent on site expands—a lot of KPIs improve.
Poor search hurts revenue: 43% of consumers said they would pay more if they could find what they’re looking for in just a few clicks.
Google-like search is within reach of everyone today, thanks to the democratization of AI. Retailers of any size can take advantage of AI to create instantly relevant customer experiences and meet the high standards that customers have cultivated.
It’s no longer available only to the e-commerce giants—to the Amazons, Alibabas, and eBays of the world—it’s available to you.
Brian McGlynn
Brian is the General Manager of E-Commerce at Coveo, a market-leading AI-powered relevance platform that injects search, recommendations and personalization solutions into digital experiences.
Brian is a long-time tech industry veteran with 20 years of experience building and hyper scaling organizations. Prior to joining Coveo, Brian held leadership roles at Intershop, Hewlett Packard, Deloitte and IP.com.
