Your business and the world at large are drowning in data, yet your customers and employees have a thirst for information. Whether it is products, documents, or support information, you need a way to deliver the right information to the right person at the right time.

You need a way to unify data from across all your systems in order to generate a holistic understanding of the content you possess and the users who are interacting with it. Because, ultimately, you can use that dual understanding to give each person what they are looking for – ideally before they even know it.

At the recent Relevance 360 conference, digital technology gurus Vincent Bernard and Nicolas Bordeleau revealed what you need to do just that: a Relevance platform.

Listen to the full talk for all the thrilling details:Relevance Platforms: The Secret Ingredient for Your Tech Stack

What is a Relevance Platform?

According to Vincent Bernard, a lead solution architect at Coveo, “A Relevance platform brings together the content you have with the way that people interact with that content.” Any search engine can answer user queries, but is matching documents with keywords enough to find what your customers and employees want? Quite often, the answer is no. And no can be devastating to both sales and productivity.

By applying artificial intelligence and user-assistive technology on top of search, a Relevance platform can breathe new life into applications by making them smarter, more helpful, and – in the end – more profitable.

Today’s customers and employees alike demand a smooth and natural experience free of friction. A Relevance platform provides this experience to people by guiding them to what they need to find – without them even realizing it.

It finishes their queries with auto-complete. It even suggests the next question. Additionally, it promotes the most relevant results to the top, not just the ones with the most keyword matches.

Bottom line: It knows what you want before you do and recommends both items and queries tailored to you as an individual.

How Does It Work? 

“If you don’t know what people are looking for and what they’re not able to find, it’s really hard for you to create those pieces of content or restructure information,” says Nicolas Bordeleau, Coveo’s VP of Product. “There is a lot of insight in the relevance engine. The engine gives back to the users, but also the administrators.” 

On the one hand, users get recommendations and find the content they want. Based on what it knows about the user, relevance technologies boost the most germane results to the top. And it then takes note of what the user ultimately selects in order to learn and improve the next interaction.

On the other hand, administrators get insight into what users are searching, finding, and most importantly, what they are not finding.

Coveo’s Relevance platform gives an equal chance to natural ordering and AI-based ranking. Ultimately, user behavior is the best indication of intent. As more users click an item returned for a query, the platform can infer that this is the best result. Additionally, administrators can tune this down as needed – for instance, to promote higher-margin items over the most popular. 

How Do You Implement It?

“The first thing you want to do when implementing a Relevance platform,” says Nicolas Bordeleau, “is start collecting data.” Connect the platform to your source systems. Next, collect user behavior by connecting the platform to all your properties. Think about where you want to deliver a better experience. Bordeleau recommends a “progressive approach” for larger organizations. It is often easier to implement the platform across different applications incrementally instead of a “big bang.” 

In each use case, it is vital to think about both reactive and proactive touchpoints. A reactive interface is where you deploy a traditional search box. A proactive touchpoint operates without specific user input. After analyzing user behavior, the platform can make recommendations for what they might need in addition to what they have already found, or even what they might need next.  

For a health care insurance company like Humana, this might be a policy option or some health and wellness information.

For an ecommerce site, this might be what product to recommend to an individual customer.

While this implementation process may sound difficult, it doesn’t have to be. For example, the Coveo platform makes integration rather simple through: 

  • SDKs: allow developers to use the technology stack of their choice
  • Connectors: support virtually any source and 100 different content types
  • UI Toolkits: enable developers to compose interfaces of standard search-UI functionality such as type-ahead support
  • Security features: ensure data is as secure in your Relevance platform as the source system itself and protected against a cyber attack
Are you ready to adopt a Relevance platform? Ensure it has what you need:Read: 10 Must-Have Features for a Relevance Platform in 2021

Can AI-driven Relevance Provide Value for Smaller Sites?

While you do need to collect some amount of user traffic to provide better results, even small sites with little traffic have benefitted from better search almost immediately.

The big idea is that an AI-based relevance engine is how digital giants and industry leaders have turned over record profits. It is valuable for them, but it is essential, accessible, and affordable for other firms with varying business models.

And don’t forget that machine learning can automate and simplify a lot of the work as your organization grows.

Dig Deeper

For all the details, check out Nicolas Bordeleau and Vincent Bernard’s talk from Relevance 360. They explain these points and more from a product and practitioner point of view. 

If you’re ready to adopt a Relevance platform, read 10 Must-Have Features for a Relevance Platform in 2021 to ensure that the one that you choose will work for you.

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About Andrew Oliver

Andrew C. Oliver is a developer, technologist, and writer. He's worked on data, search, and software architecture for some of the world's largest companies. His regular column in InfoWorld covers AI, cloud, and data architecture along with other developer topics.

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