Digital shopping isn’t what it used to be. As people increasingly turn to ecommerce channels, especially as a result of COVID-19, consumer expectations are rising—particularly for search relevance and customer service.

Did you know that, today, 96% of customers will leave you for bad customer service? And that a whopping 72% of those will do so afteronly one negative experience?

When it comes to search relevance, the statistics are also telling. In 2019, around 60% of shoppers expected a high level of search relevancy in their result; in 2020, 80% expected it. Today, content relevance is pretty much a necessity in digital commerce.

That’s not surprising. When customers have access to hundreds of brands and thousands of products with only a few clicks, the faster you can reach them on a personal level and meet them where they are as individuals, the better.

What may come as a surprise to many is how easily you can achieve true search relevancy today—with the right tools.

In a recent Relevance 360° Week session, our co-founder Laurent Simoneau chatted with Scott Compton, Senior Analyst at Forrester Research and retail ecommerce specialist who recently authored a report called “Drive shopper relevance with AI-driven digital commerce search.” They discussed what it takes to deliver true relevancy, why personalizing experiences for anonymous users is challenging, and how to overcome these challenges with the search relevance technology that’s available today.

How do you personalize an anonymous session?

Many ecommerce companies face the challenge of anonymous sessions, meaning you have no historical data on users. This is a result of the general increase in digital traffic in the past year and a half, and the fact that people are increasingly shopping across brands. 

At the same time, consumers come with high expectations of relevant experiences like the ones they’re used to getting from the likes of Amazon and Netflix. But the problem is that, unless you’re a tech giant, your customers are either one-time shoppers or they don’t create a profile that allows you to gather rich historical data from them. 

There’s good news: today, you can create personalized and relevant experiences even for anonymous or one-time users. According to Compton, the technology to provide personalization-as-you-go has come a long way in the past five years.

An image shows a man using a table to search for wood working schematics

“Historically, it has been very difficult to personalize on the go,” says Compton, “but today the tools are already here for most companies to take advantage of them.”

The first step? Make use of every piece of information you have on the visitor as soon as they come in. That data allows you to begin personalizing their session immediately. “For example,” says Compton, “if they came through a coupon code that you had put out through an affiliate program, or if they came through a search ad, where they typed in the word ‘savings’ or ‘discount’ as a search query, then you know they may be a price-conscious shopper.”

Other indicators you might use are the shopper’s geographical location and the time of day they log in.

Then, as they browse your site, your goal is to capture their behavior on the site in order to figure out their intent.

Today, ‘clickstream personalization’ (or what we call session-based personalization) enables you to personalize and fine-tune the shopping experience even for first-time users. It’s also very easy to implement especially if the company offers you a trial period that allows you to plug and play. 

The Data Silo Problem

Fractured data is one of the biggest obstacles to understanding intent. “Figuring out intent requires the convergence of various types of data: marketing information, behavioral data, understanding different channels, geographic data, semantic data,” says Compton. “But that’s the main challenge for many organizations today: they’re still operating to a large degree within silos.”

The main reason, according to Compton, is organizational. Organizations still measure employee performance individually, which prevents collaborating as a team in a meaningful way.

In practice, that means that marketers who are driving acquisition campaigns have all the data related to paid search programs. Meanwhile, merchandisers know all about the product information. But they don’t have access to each other’s data, so they can’t collaborate or build on each other’s successes.

But the convergence of data is at the core of figuring out intent and providing search relevance

“When you break down silos and align all data, stakeholders can start working towards a common goal,” Says Compton. “Really understanding the context of the user. Not so the organization can use personalization, but so that they provide the most relevant experience possible for the customer.”

Convergence of Data Means Better Customer Experience

Organizations that connect their disparate silos will see results quickly, according to Compton. By unifying their internal knowledge, they begin working together as a team to solve their customers’ problems, not their own. By connecting ecommerce, customer service, employee knowledge management, you create relevance across the board.

For example, say someone comes into your site through a search ad about a sale. The system captures the information that they’re a price-conscious shopper and makes it available to all connected components. When they search for “red shoes” on your site, the system takes that into account when providing them with results. It will also inform their customer service experiences and chatbot interactions.

Once you determine intent, you can attach it to the customer record used throughout the organization to create true relevance across the board.

By connecting data, AI and machine learning power relevant results in ways that weren’t previously possible.

According to Compton, that’s not common yet, but the tools are available today to get us there. Organizations that make use of these tools will see results quickly and position themselves ahead of the competition.

A Single Platform vs Separate Services

Convinced and ready to provide better relevance for your customers? You might have some questions, like which tools to use. Or, what are the benefits of using a single AI-powered platform versus a set of disparate plug-and-play services?

Many people view AI search engine platforms with suspicion. That’s possibly because just a few years ago AI was a black box. You didn’t know why and how it did what it did and had very little control over it. However, today’s AI platforms make transparent which decisions are being made. This includes why and how they bring you the results you’re getting. Today’s powerful AI platform is like an API-first plug-and-play service: easy to implement, including a unifying composition layer on top. 

Want to avoid the challenge of aligning many disparate services or handling a months-long redesign project to get all the parts right? One powerful unified platform is the way to go.

Platforms like Coveo act as the composing layer, the intelligence behind the entire experience. 

A graphic displays unified vs federated search, and discusses the differences between them
With its unified index, Coveo offers an easier and faster way to achieve true search relevance.

Stop Thinking About Search as “Search”

Most importantly, retailers need to stop thinking about search as “search.” 

“It’s easier to make a list of what isn’t search, than make a list of what is search,” says Compton.

A search experience isn’t simply a product keyword query anymore. Today, search includes content with customer service, deep product content, or searching through videos that lets you compare products. It also includes things like looking up a wait time at checkout or asking a question through a chatbot. 

Queries are getting longer, too. People are searching more on mobile. This means their queries are longer and more conversational—and also harder to interpret. (Compare “red shoes” in a search box versus “show me vegetarian food near me” through mobile voice search.)

The longer the query, the harder it is to determine intent. This means AI and machine learning are essential today for brands to stay afloat.

Compton emphasized the potential impact that an AI platform can have on your business. “The impact that an AI engine can have on an organization is far bigger than most retailers are imagining. The time for a return on that investment is quicker than you think. The effort required to both implement it as a first initiative and ongoing tuning is smaller than you think.”

Interested in listening to the complete conversation? Catch the full presentation here

Dig Deeper

Worried about keeping up with digital giants? Learn how AI can make your business more relevant than ever with Your Guide to Delivering Intelligent Shopping Experiences.