We’re all familiar with the concept of search. We search for things online every day. Whether it’s typing something into Google, into our phones, or within a specific website or app, the act of entering a search term and being served a set of results is well known. We do this so often and so automatically that the process behind the act of searching isn’t something we often think about. But what does searching actually entail?
What is traditional search?
In traditional search, you have to know what you’re looking for. You don’t go to Google and start typing aimlessly; you have something in mind that you need to find. Secondly, you have to identify the best way to phrase your query in order to surface the thing you’re looking for. For example, if you’re searching for information about Guru’s conference Empower, simply typing a generic term like “empower” into Google won’t cut it. You need to give the search engine context. And finally, you have to actually go somewhere, like Google or a search bar, to type in your search terms.
Pretty simple, right?
But what if you don’t know exactly what you’re searching for? What if you have a fuzzy idea, but don’t know how to articulate it? We’re all familiar with the feeling of looking for things in Google Drive and not remembering exactly what that document was called. These moments occur all the time, every single day. When you can’t remember what the resource you need is called, or you can’t remember whether you saw it in Slack or Gmail, or you can’t remember who shared it, how do you go about finding it? Traditional search won’t help you much.
Furthermore, search eats up valuable time that prevents us from doing our jobs.
What if you didn’t have to go anywhere and actively search at all? What if the information you need could find you instead? That’s what we mean by the best search is no search. Let’s dig in to what that looks like.
What is no search?
No search is the concept of having needed information pushed to you without you having to know exactly what you're looking for. No search does not mean that search is going to disappear. Search isn’t going anywhere. We will always need search to surface things, unless someday we develop technology that can read our minds (a scary thought). When we say “the best search is no search,” that’s not to advocate for eliminating search altogether. It's only to say that sometimes there is an alternative to search, and that involves discovering information without having to physically do the searching.
If we return to the basics of search, you can see where it may fall short: You have to know what you’re looking for, you have to know how to phrase your search by providing additional context, and you have to physically type in your query. Executing a search means that you need to know that something exists, and that necessarily excludes things that you don’t know exist. Imagine you’re a sales rep and you get a request from a prospect for an example of how a current customer solved Problem X. To surface an example, you go to your sales enablement tool and search “case study Problem X” and choose from the results.
But here’s where search gets limiting: your search bar is like a blank slate with zero context other than what you give it. So even though you have an entire email from this prospect explaining what they’re looking for, you still have to start fresh in the search bar and enter your own context. Because of that, you search for what you know exists, like “case study.” But what you don’t know is that there is a quote in a blog post that perfectly addresses Problem X, yet that result may not be returned because you specifically looked for a case study. Or, because the term “Problem X” doesn’t appear in the title of the blog post.
Now, imagine instead that you don’t have to search at all. What if you could leverage the context already on your screen – the prospect’s email – and have all relevant information pushed to you (whether you know it exists or not) based on that context, without having to physically type in a search term at all? You’d probably discover the blog post you didn’t know about that better answers your prospect’s question than the case study you chose. The best search is no search; and, with Artificial Intelligence, it’s a reality.
What is AI-powered search?
AI-powered search is when information is algorithmically suggested without you having to search for it. Technology has already started saving us from searches. We get searchless suggestions all the time: your address pops up in Waze when the app thinks you might be getting ready to drive home; your iPhone suggests contacts to text based on ongoing conversations; your Explore page in Instagram shows you posts you might like based on other posts you’ve liked. Already the apps we rely on everyday are using the context of our lives to serve us information that we might find interesting. And this is inherently helpful because it saves us time and doesn’t force us to duplicate efforts by resupplying existing context. And if the suggested result isn’t on point (maybe you’re not driving home) you can ignore the suggestions and search for a new address anyway.
The overhead involved in physically searching may not seem like that much, but if you could save 30 seconds every time you needed information and received that exact piece of knowledge as a suggestion rather than at the end of a search, how much time would you save each week? How much time would your team at work save each month? How much time would your organization save each year? Best yet, how much frustration would you save everyone?
At Guru, this is the lens through which we’re thinking about the future of knowledge management and the way people work. While we are continuously improving our search functionality within our product, (because again, barring mind-reading robots, we’ll always need search as an option), we are looking ahead to optimizing for saving users the trouble of searching when possible.
What are the business implications of AI-powered search?
The workflow implications of cutting down on search when suggestions can deliver the pertinent information more quickly are exciting. We move through our days at a breakneck pace – the time it takes to re-enter context into a search bar when a suggestion could do the job instead will soon feel like waiting for dialup internet. Getting that time back frees us up to focus on more strategic initiatives. Plus, searching requires mental energy and task switching, which decreases productivity. If a support rep has to divert their attention from a customer on the phone to search for knowledge, they may miss what the customer is saying or frustrate the customer by asking them to hold while they search. In our world of instant gratification, why make a valued customer wait around if you don’t have to?
The way we work is changing, and the knowledge we need to do our jobs should find us where we work.
We’re all familiar with the concept of search. We search for things online every day. Whether it’s typing something into Google, into our phones, or within a specific website or app, the act of entering a search term and being served a set of results is well known. We do this so often and so automatically that the process behind the act of searching isn’t something we often think about. But what does searching actually entail?
What is traditional search?
In traditional search, you have to know what you’re looking for. You don’t go to Google and start typing aimlessly; you have something in mind that you need to find. Secondly, you have to identify the best way to phrase your query in order to surface the thing you’re looking for. For example, if you’re searching for information about Guru’s conference Empower, simply typing a generic term like “empower” into Google won’t cut it. You need to give the search engine context. And finally, you have to actually go somewhere, like Google or a search bar, to type in your search terms.
Pretty simple, right?
But what if you don’t know exactly what you’re searching for? What if you have a fuzzy idea, but don’t know how to articulate it? We’re all familiar with the feeling of looking for things in Google Drive and not remembering exactly what that document was called. These moments occur all the time, every single day. When you can’t remember what the resource you need is called, or you can’t remember whether you saw it in Slack or Gmail, or you can’t remember who shared it, how do you go about finding it? Traditional search won’t help you much.
Furthermore, search eats up valuable time that prevents us from doing our jobs.
What if you didn’t have to go anywhere and actively search at all? What if the information you need could find you instead? That’s what we mean by the best search is no search. Let’s dig in to what that looks like.
What is no search?
No search is the concept of having needed information pushed to you without you having to know exactly what you're looking for. No search does not mean that search is going to disappear. Search isn’t going anywhere. We will always need search to surface things, unless someday we develop technology that can read our minds (a scary thought). When we say “the best search is no search,” that’s not to advocate for eliminating search altogether. It's only to say that sometimes there is an alternative to search, and that involves discovering information without having to physically do the searching.
If we return to the basics of search, you can see where it may fall short: You have to know what you’re looking for, you have to know how to phrase your search by providing additional context, and you have to physically type in your query. Executing a search means that you need to know that something exists, and that necessarily excludes things that you don’t know exist. Imagine you’re a sales rep and you get a request from a prospect for an example of how a current customer solved Problem X. To surface an example, you go to your sales enablement tool and search “case study Problem X” and choose from the results.
But here’s where search gets limiting: your search bar is like a blank slate with zero context other than what you give it. So even though you have an entire email from this prospect explaining what they’re looking for, you still have to start fresh in the search bar and enter your own context. Because of that, you search for what you know exists, like “case study.” But what you don’t know is that there is a quote in a blog post that perfectly addresses Problem X, yet that result may not be returned because you specifically looked for a case study. Or, because the term “Problem X” doesn’t appear in the title of the blog post.
Now, imagine instead that you don’t have to search at all. What if you could leverage the context already on your screen – the prospect’s email – and have all relevant information pushed to you (whether you know it exists or not) based on that context, without having to physically type in a search term at all? You’d probably discover the blog post you didn’t know about that better answers your prospect’s question than the case study you chose. The best search is no search; and, with Artificial Intelligence, it’s a reality.
What is AI-powered search?
AI-powered search is when information is algorithmically suggested without you having to search for it. Technology has already started saving us from searches. We get searchless suggestions all the time: your address pops up in Waze when the app thinks you might be getting ready to drive home; your iPhone suggests contacts to text based on ongoing conversations; your Explore page in Instagram shows you posts you might like based on other posts you’ve liked. Already the apps we rely on everyday are using the context of our lives to serve us information that we might find interesting. And this is inherently helpful because it saves us time and doesn’t force us to duplicate efforts by resupplying existing context. And if the suggested result isn’t on point (maybe you’re not driving home) you can ignore the suggestions and search for a new address anyway.
The overhead involved in physically searching may not seem like that much, but if you could save 30 seconds every time you needed information and received that exact piece of knowledge as a suggestion rather than at the end of a search, how much time would you save each week? How much time would your team at work save each month? How much time would your organization save each year? Best yet, how much frustration would you save everyone?
At Guru, this is the lens through which we’re thinking about the future of knowledge management and the way people work. While we are continuously improving our search functionality within our product, (because again, barring mind-reading robots, we’ll always need search as an option), we are looking ahead to optimizing for saving users the trouble of searching when possible.
What are the business implications of AI-powered search?
The workflow implications of cutting down on search when suggestions can deliver the pertinent information more quickly are exciting. We move through our days at a breakneck pace – the time it takes to re-enter context into a search bar when a suggestion could do the job instead will soon feel like waiting for dialup internet. Getting that time back frees us up to focus on more strategic initiatives. Plus, searching requires mental energy and task switching, which decreases productivity. If a support rep has to divert their attention from a customer on the phone to search for knowledge, they may miss what the customer is saying or frustrate the customer by asking them to hold while they search. In our world of instant gratification, why make a valued customer wait around if you don’t have to?
The way we work is changing, and the knowledge we need to do our jobs should find us where we work.
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