What is unified search and how can it help your organization stay on top of the game?
Digital interactions today are drastically different from how they were only a few years ago. In the past, visiting a website, opening an email, or using a mobile app were completely discrete experiences. Each data silo was separate from the others.
Today, we live in a completely different world. Users expect a frictionless digital experience that gets them to their goals or solves their problems as quickly as possible.
Even though technology has advanced in leaps and bounds, unfortunately, we still feel the effects of the old days’ fragmentation in our everyday lives.
Fragmented Experiences Break Digital Journeys
In customer service…
Ever been frustrated by customer service where the help center representative had little to no information about your problem? Or, even worse, had to be updated on your previous conversation with another agent? Then you are familiar with the disappointing effects of a disjointed system.
In the digital workplace…
The same is still common in the workplace. You might be using a collaboration app to work on a shared document.
Instead of devoting effort to developing new creative ideas to further your company, you spend hours navigating disconnected apps. Getting lost in multiple databases in search of the right documents. Or just searching the intranet for relevant information to only realize that the data you need is out of reach.
These frustrating experiences are still all too common today in both small and large organizations. They’re also more costly than most businesses are willing to admit.
And more…
Fragmented search not only costs businesses time and money. It also prevents them from building the foundation for the implementation of generative AI.
The good news is that unlike a few years ago, the problems associated with fragmented search are easily avoided today with the help of a unified search engine.
What is unified search and how can it help your organization stay on top of the game?
Before answering this question, let’s look at the more common type of enterprise search that is used in most organizations today: federated search.
Federated Search: What Is It?
The Early Days of Search: Siloed Search
In the early days, “search” meant logging into a system and typing a query into a search box.
That search box could only access the one particular data source attached to it and nothing else. If you had to search multiple sources, you had to go through the login and search process again, and again, and again. There was just no way for that search field to access disparate sources of information.
If you forgot which data silo the content lives in or the password to log into a particular database or storage system, tough luck. If you had the crazy idea of comparing your search result across the sources you just searched, you were looking at hours of manual data organization and reorganization.
The Rise of Federated Search
When federated search first came along, it finally gave users a single search interface in which to query across multiple data silos. Finally, a single search term typed into a single search box was able to send the request for information across and get results from multiple sources of data.
That’s because federated search indexes multiple data sources at once and retrieves information from all of them via a search application that’s built on top of search engine(s). So when a user makes a single search query, the federated search engine simultaneously searches multiple, usually disparate databases and ecosystems, returning results from all sources and presenting them in a single user interface.
Federated search was a huge step forward from traditional search and became invaluable in large organizations that had thousands of documents and data sources in the cloud and on-premise, where searching them via traditional search was simply impossible.
Why Federated Search Is No Longer Enough
For a while, this seemed like the perfect solution to the search problem.
Yet as digital interactions became more common, people’s expectations around their search experience became higher, and some problems with federated search became apparent.
Now that we spend more time in front of our screens than ever, we want these interactions to get us to our desired search result quickly. In reality, people don’t have the time or desire to search anymore.
Today’s users expect the system to anticipate their next move, interpret their misspellings correctly , and learn from their previous clicks and searches to present relevant results fast.
Disconnected journeys
Today, a buyer might start with a mobile app to search for an item. Then they’ll check online reviews of the item or ask a question about it in an online community. And then they’ll search the web for instructions on how to install it. They’ll only contact the help center for troubleshooting if they can’t find a solution to their problem on their own. And when they do, they expect their interaction with the agent to move as smoothly as possible.
Whether people realize it or not, they expect their digital experiences to be highly relevant and personalized just for them. They don’t want to waste additional time explaining their issue to yet another customer service agent. They expect their needs to be anticipated and their problems solved before they even spell them out. And rightly so.
Why? Because the technology that enables a unified search experience is available today. It’s used by the digital giants who set the bar for the rest of us, whether we like it or not.
The kind of search experience that’s expected by users today is impossible to achieve with federated search. A good, advanced search experience today requires capabilities such as autocomplete , query suggestions , filters and faceting , and so on. Unless each separate index supports each of these capabilities, your federated search won’t be able to offer these.
Unsatisfying search experiences
In addition, with federated search, it’s impossible to achieve true relevance. Because each index is searched separately, the results are ranked by source—and ranking by relevance across all content sources is impossible.
Finally, with federated search, the response times will often be quite slow. Because it searches across multiple indices, the response time will be only as fast as its slowest content source. A few years ago that might not have been a problem, but shoppers’ expectations around speed have changed dramatically as well.
A unified search engine can create a layer of relevance by connecting all these disparate interactions. And if they’re connected by the right platform, the data from these interactions follows your customers as they move between channels and delivers personalization at every touchpoint.
Today, relevance is important in every sphere of digital interactions, be it ecommerce, workplace, service, or websites. Here’s how to achieve integrated search experiences with the help of a unified search engine.
What Is Unified Search?
Unified search differs from federated search in that it creates one unified index of content, across all content storage systems. This includes the option to crawl or push content stored in the cloud or on-prem via connector library or APIs. It also ranks the entire corpus in a single user interface, applying relevance across the board to deliver meaningful results.
The unified index is the staple of a unified search engine. This index can be populated by many sources, each configured to regularly retrieve items from a specific content repository. This is also along with permissions and security identities to replicate a secured system. You can pull content into an index using cloud-based hosted crawlers found in source connectors (e.g., Salesforce, Sitemap, Web, etc.) or use a Push API instead.
Unified search has faster query response times than federated search. This is because results are sourced from one unified index as opposed to searching multiple systems with query-time merging. By contrast, in federated search, the response times are only as fast as its slowest content source.
Full, Rather than Partial, Relevance
When your search relies on a unified search engine, relevance is applied across the entire content corpus of content. It can even self-optimize with the application of machine learning. That means that results will always be ranked by relevance, regardless of the source.
When you deploy a unified search engine, a better user experience is guaranteed. Search results are blended and pages can be built from a component library or APIs. Sorting, filters, faceting, and other capabilities of the search UX are built on top of the unified index.
A unified search engine solution might sound daunting and even costly — because by definition, it needs to be more comprehensive. If you are building it yourself, it can be costly in terms of resources and time to develop and deploy. If you are looking at a SaaS solution, you need to make sure it has pre-built connectors to ease integration from all those silos.
And if you want one index serving many channels, you should make sure your solution offers a headless approach — so you can tailor the search UI to the channel itself.
How Unified Search Future-proofs Your Organization
But the best part is that unified search future-proofs your organization’s search system by providing a solid foundation for the implementation of artificial intelligence and generative AI.
Once you have all that content flowing in from all those silos, machine learning helps establish which content asset is the most relevant for the search query, and uses behavioral signals to help determine relevance.
Having to incorporate models that are tuned to your business cases (knowledge management, customer service, ecommerce) can require expensive expertise. Or, you can find a vendor who invests in AI research and development.
These off-the-shelf models can take into account several pieces of data beyond simple keyword matching; after all, it is a relevant result if you search for ‘relevance blog,’ and the title of the first result is ‘relevance blog.’ But is it really that relevant if it’s four years old, and you know there’s a newer one?
This is further complicated in use cases like ecommerce, where a search is often just a single word. No amount of manual keyword tuning is going to fix that — especially since those keywords aren’t just tied to a product, but also the context in which it was submitted. A rule can— maybe —fix this, but it’s a band-aid fix at best. Rules still require human intervention, which can increase costs.
Machine learning can take all of that off of search architects’ plates, giving them the space to create the experiences your users want.
Unified Search and Generative AI: The Perfect Combo?
Unified search also provides the perfect foundation for the implementation of generative AI.
Generative AI has already taken the business and tech world by storm. It is quickly becoming a must-have in every organization.
Coveo Relevance Generative Answering uses the Coveo platform to ground content. It does this by retrieving relevant content from trusted sources that a user is allowed to see. Access controls protect proprietary and private information. Only approved documents will be fed to the LLM to generate the answer, ensuring compliance and data security.
The same cannot be achieved with federated search that relies on disparate indices.
Conclusion: Unified Search Is Where Your Business Needs to Be
If you still equate “search” with “search box,” think again. With a unified search experience, every interaction informs the next interaction, across platforms and channels.
Intelligent search tailors content to you and your issue. Regardless of whether you’re searching through product documentation or on the company’s website. If you decide to contact the call center, the representative will automatically know what issue you are trying to solve. They will see the relevant content in their knowledge base to help you solve it.
Today, your customers and employers expect nothing less than that. And the only way you can get there is with unified search.
Dig Deeper
Interested in learning more about a platform that can take your search beyond the box? To invest relevance in every touchpoint, Coveo links all your content sources together in one index. Without needing to move files anywhere.
Learn more about how our intelligent search platform makes content discovery effortless, with AI-powered results you can see on day 1.