In the past several months, retailers have seen how COVID-19 has accelerated numerous digital trends already set in motion before the pandemic, including higher customer expectations when it comes to searching for products and services online. Whether a simple website search, e-commerce shopping query or chatbot question about shipping, customers are often met with off-target answers that leave them frustrated or on the way out the digital door.
Solving the problem of search disengagement, new artificial intelligence tools let companies deliver the most relevant answers to their customers — and transform the bigger customer data puzzle in the process.
Solving the problem of search disengagement, new artificial intelligence tools let companies deliver the most relevant answers to their customers — and transform the bigger customer data puzzle in the process.
Helping companies integrate AI-powered search into CX, customer service, e-commerce and employee experience, Montreal-based Coveo taps into a goldmine of data to generate relevant and engaging search results at every touchpoint. Hand-in-hand, customer data and AI tools that make that data actionable lead to a more personalized and relevant retail customer experience, from a customer’s initial product search to upselling and purchasing.
“It’s that notion of bringing product and content together in the right space, in the right place in the customer journey,” says Mark Floisand, Coveo’s SVP Product & Industry Marketing. “Customers don’t want to sit in a call centre hold queue and wait for an answer that might or might not be right.”
Coveo builds their machine-learning models based on data that is the most meaningful to companies and their customers. So for companies with all kinds of valuable information strewn throughout their systems — product specifications, fixes, cheat sheets, troubleshooting guides, customer feedback and more — Coveo creates a common index from that data, turns it loose through search and returns results that customers are looking for.
From AI search utility to personalized CX
As with customer service-related searches, the search or chat box of an e-commerce or retail website is a dynamic way for customers to interact in their own words with a company, and provide companies with important information about their needs. The difference is that Coveo’s AI-powered search, with access to all the information on every product of a company, is able to understand a customer’s query and give them the details they need on the products they’re looking for, as well as related products they’re likely to be interested in. That strategy leads more effectively from brand engagement to increased sales.
Coveo’s AI-powered search, with access to all the information on every product of a company, is able to understand a customer’s query and give them the details they need on the products they’re looking for, as well as related products they’re likely to be interested in.
Considering the volume of data on products and customers today, true personalization of CX can only be made possible through AI tools. A successful desktop search utility 15 years ago, Coveo saw an opportunity in multi-tenant cloud-based architecture: the company modernized its platform with AI, making it easily deployable and able to track analytics data at scale.
In his work with tech giants from Apple and Adobe to Sitecore and SAP, Floisand has seen firsthand how AI needs to be used as a strategic tool for meeting customer expectations and achieving business objectives, in CX and beyond. Coveo has seen its platform increase companies’ search capacities and help them orchestrate more complex and successful customer journeys — the AI company was recently named as a strong performer in The Forrester Wave™: Journey Orchestration Platforms, Q2 2020. It’s a level of choice and flexibility in CX that has quickly become what customers expect.
“In a perfect world, a marketer would say here’s my ideal customer journey map, how do I steer people through it?” explains Floisand. “That perfect world doesn’t exist though. The only right map is the one for that individual at the moment they’re in. If you funnel all these individuals through one journey path, many of them will resist or abandon it. So why not use machine learning to give you the best chance of getting the most relevant content to every individual, wherever they are on their own journey?”
Putting data to work for retail customer experience
In retail commerce, where personalization has to happen in a few clicks after a customer lands on a website, companies need AI tools that quickly put together those clicks as data points. Coveo’s AI collects data around those clicks and around the products themselves, builds a multi-dimensional, personalized e-commerce space out of that data, then provides relevant and up-to-date search results and other recommendations. Customers will stay on the site and move closer to a sale.
In that way, AI platforms like Coveo are helping customers get what they need while changing the experience of the user interface itself, an essential yet often overlooked part of the customer journey. For a customer who wants to buy a one-off, higher-ticket item like a freezer, they’ll typically search out a local retailer rather than go to a marketplace like Amazon. Browsing that smaller retailer’s online catalogue, however, isn’t always a pleasant experience, digging down through categories on a sidebar and reading extraneous details that might slow down or halt their purchasing decision. If a customer cares most about a freezer’s dimensions, Coveo’s tools make sure that’s what they see first.
“Coveo is doing this on the basis of proven outcomes, not only what people searched for but what purchase paths were successful,” says Floisand. That virtual circle of positive experience from companies to customers and back again all comes down to integrating AI tools into a CX strategy that itself is integrated into a data-oriented business plan.
Connecting a company’s most meaningful data
While most organizations use several system tools in multiple departments to solve specific issues, typically these systems don’t talk to each other. AI solutions can tie systems together through pockets of user data. By connecting, indexing and unifying data with AI, companies can serve more meaningful content to their departments and to the customers they serve — and keep data more secure on top of that. In aggregate, all that data provides a more meaningful view of customers and their choices.
While most organizations use several system tools in multiple departments to solve specific issues, typically these systems don’t talk to each other.
“The more we can avoid silos and utilize the commonality of interaction data, the better,” says Floisand. “If you’ve got a lot of traffic on an e-store or a self-service portal, the tool has learned a lot already about customer flow from interaction data. So if a company wants to spin up a chatbot service, for example, it can take advantage of where existing volume traffic has shown proven success and bring that to bear in a new mode.”
Floisand illustrates the process with an example of a customer searching for a notoriously hard-to-purchase-online product: tents. “People want to know not just their dimensions but how easy they are to put up, so they do a lot of scouting on YouTube. If a company has tent construction videos generated by them, their vendor or their customers, a tool like Coveo can bring that video content right onto the tent category page of a company’s website and offer other relevant products alongside it, actively helping someone make a decision. It’s going to improve conversion rates, it’s going to enable customers to buy what they want through an experience they enjoy, and make it less likely that they’ll return products.”
To an AI platform, the video is simply more data to index and present in the shopping flow. From a CX perspective, that indexed video data hits all the business metrics — increased conversion, higher value due to upselling along the way, lower return rate — and leads to greater profitability.
Helping retailers be retailers, not tech companies
The future of how people buy online will depend not only on new technologies but on strategic brand experiences and engaging e-commerce. Retailers and brands facing the rise of massive online retail marketplaces have to stand out from their competition and create experiences that drive demand — personalizing retail customer experience is one major way to differentiate themselves.
The future of how people buy online will depend not only on new technologies but on strategic brand experiences and engaging e-commerce.
“In e-commerce, 50% of the market is concentrated in the hands of four big players, but what about everybody else?” asks Ciro Greco, Director of AI at Coveo. A neuroscientist who transitioned to tech, Greco emphasizes the importance of AI in natural language processing to boost retailers’ search capabilities into the realm of personalized CX.
“Many companies in the retail commerce sector aren’t super technical and will generate data in a very different way than the big players,” Greco continues. “On top of that, most retailers just aren’t AI companies. Coveo is saying, ‘be a retailer, don’t try to be a tech company’. Get the right tools and focus on your products and revenue path.”
For most brands and retailers, what matters most in terms of data is not necessarily quantity but quality, since their customer base comes to them with specific needs. To stay competitive and generate revenue, these companies don’t need to deal in nearly as much data as big marketplace players do — but they do need smart data solutions that integrate into their systems, stay current and make their data actionable.
“Coveo’s broader function is as a uniform layer stretched across a company’s customer touchpoints,” explains Greco. Since every touchpoint has its own idiosyncrasies, a unified indexed layer of data can help align the goals of different departments, leading to better understanding of customer behaviour at every touchpoint. “When a customer lands on your website, they’re in a place and going somewhere,” Greco reiterates. “There’s a lot of information we can take out of that alone, and that’s exactly where the AI comes in.”
At the heart of Coveo’s platform is a drive to make companies more competitive through AI. “When there’s something that your company does very well, there’s no need to be wiped out by the big players,” says Greco. For traditional retailers who are rebuilding and augmenting their websites and online stores to meet customer expectations, AI tools like Coveo’s are a quick and effective way to put data to work bridging the gap between retail customer experience and successful business outcomes.
– written with files from Keatext contributor Robyn Fadden
