Advances in AI have made search engines “smarter,” allowing them to draw on their own ever-expanding knowledge graphs to answer users’ questions with a higher degree of specificity than ever before. The fact that search engines can now answer complex natural language queries accurately is reframing consumer expectations — people are being trained to search for exactly what they want. They expect answers and your organisation must be able to provide them.
You can achieve this by building and maintaining your own knowledge graph, which will allow you to manage your information at scale and deliver the right answers everywhere people are asking questions. Here’s what a knowledge graph can help you do.
Answer multi-dimensional queries in all search experiences.
When your customers search for things like stores, advisors, offers or events, they’re not searching for those words — they’re searching for the real things those words refer to. A knowledge graph can understand what they’re actually looking for in the real world, and it can get your customers exactly what information they need.
Let’s revisit the example in our previous post on understanding knowledge graphs: a potential patient searches for “best dermatologist near me open Saturday who takes Cigna.” Delivering the correct answer requires information from across your organisation: ratings (“best”), speciality (“dermatologist”), office location (“near me”, hours of operation (“Saturday”) and insurance accepted (“Cigna”). How can your organisation deliver an answer — on your own site or in search results — that requires information from marketing, operations, facilities, compliance and more?
With a Knowledge Graph, you can define the relationships between all these entities — your ratings, professionals, locations and insurance — so that an AI-powered discover service can answer this question. And your organisation increases its chances of ranking for that very specific, high-intent query.
To “speak the language” of search engines, you need your own brand knowledge graph. If your information is missing or your entities aren’t mapped to one another in a way that search engines can understand, you won’t show up in search results — and a competitor might.
Deliver answers on your own website.
So you understand that customers have high expectations for the kinds of answers they can get from search engines. But now they’re beginning to expect the same thing from your website, too — and the experience often doesn’t live up to these expectations.
Let’s say someone receives a personal recommendation for a financial advisor at Advantage Advisors named Roy Gonzalez. Instead of making a general search for a financial adviser, they start their journey on the Advantage Advisors website, looking for Roy Gonzalez’s phone number.
After a few pages and several clicks, however, they’re likely to give up if they can’t find the information. They’ve been trained by Google, Alexa, and Siri to just ask questions, but they can’t do that on most websites. And what do most consumers do when information isn’t easy to find or search for? They give up. They bounce back to exactly where they would have started otherwise — a search engine.
This could lead to them finding incorrect information — or worse, a competitor. Delivering the answers customers are now trained to expect, directly on your website, leads to revenue. So your organisation needs a knowledge graph to enable you to take control of this experience.
If a potential customer searches, for example, “financial adviser near me who speaks Spanish,” and your website’s information is structured to answer this question, then they can find Roy Gonzalez’s individual adviser page (which includes his hours, office address and phone number). The customer can then call to book an appointment directly from the result.
That’s a great customer experience — and one that leads directly to bookings and revenue.
Learn how your business can build its own knowledge graph with Yext.