Name: How and Why Knowledge Graphs Enable AI-powered Discovery
Uploaded: 2025-02-27T17:03:05.987Z
Duration: 17 min 4 s
Description: How and Why Knowledge Graphs Enable AI-powered Discovery

Transcript for "How and Why Knowledge Graphs Enable AI-powered Discovery": Alright. Welcome, everyone, and thank you for joining today's session, how and why knowledge graphs enable AI powered discovery. I'm really excited to dive into this topic because as many of you know, it's not every day that we see such dramatic shifts in the local search environment, especially the kind of changes that we've witnessed over the past year. These shifts are transforming how we discover, connect, and interact with local businesses. And as digital marketers, you have a lot of questions. So by the end of this session, our goal is for you to leave with a deeper understanding of how knowledge graphs work, why they're a game changer for AI driven discovery, and how you can leverage them to enhance your digital marketing strategies. To give a quick overview of our agenda, we'll start by defining what knowledge graphs are and the role that they play in AI powered discovery. From there, we'll explore how a knowledge graph can help structure and organize vast amounts of information while also making it easier for AI to provide more accurate, precise answers to user queries. Then we'll discuss the positive impacts of using a knowledge graph to manage your business information. And lastly, we'll end on some key strategies that you can use to optimize your brand for the new world of AI powered search. So whether you're looking to improve your local SEO, enhance your content strategy, or just simply stay ahead of the curve with AI, our goal here is for you to leave feeling confident and inspired to incorporate knowledge graphs into your digital marketing strategies. Give a quick, brief introduction. My name is Trent Ruffalo. I'm a senior product marketing manager here at Yext. I've spent the last eight and a half years in the local search industry. And during that time, you know, I've been able to work with a number of brands of all shapes and sizes and learn a lot about their unique challenges, but also hear about how they're solving those issues with different effective marketing strategies. So I'm really excited to bring that experience as well as that perspective into today's session. So with that, let's jump right in. So first off, why are knowledge graphs key for discovery? Well, probably everyone tuning in right now, this is what you care about the most. How do I make sure that, you know, you're showing up in local search everywhere your customers are searching? Well, for the longest time, that's primarily been on Google. But with the rise of, different AI powered search platforms like ChatGPT, Perplexity, and even Google AI overviews, and many, many others that we're seeing, we're witnessing this shift in how consumers are searching for and interacting with local businesses. For the first time in, you know, I don't know how many years, Google's market share has dropped below 90%. And when you look back historically, that 3% drop in just a few months is actually very significant because Google's market share has remained relatively consistent for as long as we can remember. So we can speculate as to why this is happening, but there is certainly an obvious correlation, you know, with the strong adoption of these different AI powered search platforms like ChatGPT. And Gartner is predicting that this is only the beginning by 2026. And so when we think about it, that's, you know, roughly a year from now. Google search traffic is expected to drop by 25%, and that's because of these changes in consumer search behavior. This is huge because as digital marketers, your main focus has always been, how do I make sure my brand shows up on Google? But now it's not just Google. You're also going to have to develop a strategy that optimizes your brand on these new AI powered search platforms. So how can you develop a strategy that optimizes your brand for those traditional search platforms like Google as well as the future of search that's powered by AI? Well, the secret behind that is organizing your business information and then delivering it not only to Google, but also to AI in a very structured way. And that is exactly what using a knowledge graph does. It organizes information in a structured interconnected format, and this makes it so that search engines and AI models can easily parse and understand it. So in fact, Google relies on their own knowledge graph to deliver the best results to users when they're searching. And if you were to go and ask Chip, Chat GPT directly, you know, if a knowledge graph is important for, you know, your business to show up in AI search, you'll see that they say it's actually critically important. And so the reason is that those knowledge graphs provide AI with structure, easy to understand information. And so this is what's foundational for these different AI systems to deliver the most accurate and trustworthy responses. So it's it's important to remember, these AI platforms, they're powered by large language models. And what those are, they're essentially computers, and they're trying to display what they feel is the most trustworthy information. So the more that these large language models know about your business in a way that they can understand, the more likely that they are to surface your brand in local search queries. And the great thing about incorporating a knowledge graph into your local marketing strategy is it sets you up for success, not just on the chat GPTs of the world, but also on the traditional search platforms like Google. So now that we can see, you know, roughly how important a knowledge graph could be for showing up in search, wanna take a quick step back and actually just, make sure we understand what a knowledge graph is specifically in the context of managing your brand's information. So if I can put it, you know, pretty simply, a knowledge graph is a, you know, pretty powerful way to manage and structure your brand's information because it allows you to store and manage any type of data, but it also allows you to establish relationships between those as well. So you can see here in a sample knowledge graph, a business could look something like this where it has locations, jobs, events, different products and services that they offer as well as FAQs. But what's unique here when using a knowledge graph is it connects all of this data is related, how it's connected. So you could set up a structure that indicates certain products are sold at specific locations. Different FAQs are associated with specific services that you offer, where your events are located, what jobs are available at different offices, stuff like that. So this structure just makes it easier for traditional and AI search platforms to understand and, again, surface your local business information. So to give you a very, very common example, something that you all might do, when you're searching for something like coffee shop near me, Google can now understand that, hey. You're a coffee shop. You're located at a, you know, this specific place. You're offering this specific service, and perhaps you're even related to a nearby landmark or, you know, even a community. So this is how Google with a knowledge graph is able to interpret your information and then provide consumers with the most relevant results based on each search query. There we go. And this concept of structuring data, you know, with relationships is especially powerful for businesses that have professionals. So whether, you know, those are health care providers, like doctors or physicians or financial professionals, like agents, advisors, mortgage loan officers, these individuals often work across multiple locations, and this can lead to a lot of challenges with maintaining accurate and up to date information for each professional across each of those different respective locations. Well, the same can be said for organizations that have teams of individuals. Right? So think of a group of financial advisors who work out of the same office. Well, each advisor may have a, you know, a unique set of products or services that they offer. So an example, one may specialize in insurance, one in wealth management, others in retirement planning. So this relational data structure ensures that only accurate and up to date information about each adviser's offerings is always gonna be seamlessly delivered across each of the different digital channels, that you're powering data to. So moving on here, using a knowledge graph can, yes, be a powerful way to organize and structure your data, but what are the main benefits of actually doing so? Well, first benefit, I think we've touched on it a good amount already, but it can help increase your search discoverability. You know, a lot of these traditional platforms like Google and AI, they thrive on structured data, and that's because, again, it helps them easily understand information about your local business. And this is what allows them to provide those consumers with the best and most accurate search results. Second primary benefit here is setting your brand up for success for the future of AI. At this point, it seems like there's, you know, a new large language model that's popping up every other week. Well, regardless of what new AI search platform comes out, the need to deliver structured data is a data strategy is something that you're always gonna be able to count on. And then lastly here, using a knowledge graph is a powerful automation tool. So your data changes a lot, and it needs to be updated across multiple different search experiences. Well, a knowledge graph is great because it will automatically update and synchronize your information in real time, and this just ensures consistency and accuracy across all the different search experiences without the, you know, the necessary manual work, to do so. So I wanna give a quick example of what I mean by that specifically when it comes to automation. So imagine that we're launching a new product, something like a LTO, a limited time offer for a burger combo. Well, without an olive graph, I would have to go I would manually update, you know, this this product offering across my listings. So that would would be Google, Facebook, Yelp, and many others. I would have to add that offering to my landing pages, as well as my menu, landing pages. I would have to update those, that information across my search experiences across different different locations. Not happy this one by one, obviously, very time consuming. And because I'm doing it manually, you know, I'm more prone to errors. But with the knowledge graph, everything is connected. So I could simply just specify which locations are offering this new burger combo, and the system would automatically update that information everywhere it appears. So, yes, across my listings, Google, Facebook, and Yelp, as well as my landing pages and different search app or even chat experiences. So, you know, again, this example here, if the burger combo that I was offering is only available, you know, say, locations one and two, but not at location three, well, that knowledge graph ensures that only those, you know, first two locations are gonna display the new item with you know, while location three is gonna remain unchanged. So, again, not only does this save you all a massive amount of time, but it's also gonna significantly reduce the risk of errors or inconsistencies in your data. So with that, I wanna finish off today's session, with just a few key strategies that will help you prepare for the future of search at powered by AI. First is to use a system where you can store and build, your local business information with a knowledge graph. So the positive impacts of using a knowledge graph, again, can help increase search discovery, can provide your brand with a data strategy that is primed for AI, which is certainly the world that we're going into, and it can reduce a lot of manual effort when you need to add or update your data. Next here, I wanna talk about creating AI driven content. So these AI powered platforms, what they do is they display information a little bit differently from a traditional search engine like a Google. What this means is how you create an optimized content should also be a little bit different. So instead of just focusing on keyword optimization for ranking in traditional search, you should create content that is, you know, maybe more question focused, and this tends to be more optimized for those generative conversational search experiences. And then lastly here, you'll wanna distribute all of your structured data to as many places as possible, especially AI powered platforms like ChatGPT. They reference in they're referencing local business information from a variety of both, you know, first party as well as third party sources. So for you, the more places that you can put your data in a structured way, make sure it's represented accurately, the more likely that these AI powered platforms will trust your data, thus improving your chances of showing up and ranking higher in search. So with that, kinda leave you all with this. If there's one thing, for you all to remember or take away from today's session, it's that delivering the most amount of structured data in as many places as possible will arguably be the most effective data strategy for succeeding, in this new AI world of search. So what that means is that, you know, your AI strategy essentially becomes your data strategy. So those are the, key strategies wanted to leave you with. I hope, again, you found this session to be helpful and informative. Thank you all again for tuning in. Don't hesitate to reach out if you have any questions, and please enjoy the rest of the event.