What is Enterprise Search?

You wake up on a workday and get asked, 'how do we purchase a business sub?' you might share a link to a how-to article or even jump on a call to share your screen.

What if you had to do it a hundred times everyday?

You wouldn't, no one would. That’s why we document information first. But what happens when we have a big team? When simple ‘search for keywords across tools’ doesn’t cut it anymore?

That’s when Enterprise Search comes into a company’s DNA. And why wouldn’t it? Gartner thinks 54% of information workers across the globe complain about interrupting their work to look for relevant information.

An Enterprise Search helps employees query the entire company’s documented knowledge to find answers. It started out in a Google-like interface when the tech was invented as an in-house tool by enterprise companies. Because of the growing demand for enterprise search solutions, there’s been quite a lot of improvement and the emergence of new dedicated solution providers.

In fact, the best ones take information retrieval up a notch using AI. Rather than serving a doc matching your keywords, AI-search engines understand questions like, “What’s our time-off policy?”, look up relevant docs, and give an exact answer.

To label these properly, Gartner created a new enterprise search category called "Insight Engines," which help businesses synthesise or even proactively by ingesting, organising, and analysing data. Forrester defines the same category as "Cognitive Search," a search function which uses AI capabilities like NLP and other machine learning capabilities to ingest, analyse, and query digital data content from multiple sources.

So, there’s a lot to uncover. Keep reading to understand more about what enterprise search is, about search analytics, how it benefits enterprises, and how to implement it.

What is Enterprise Search?

Enterprise Search is a search tool that helps employees find information across all company sources, all types of data, to cut down on information retrieval time. Your team can either build it or you can purchase a dedicated solution.

And the productivity gains from an enterprise search solution are massive. Instead of looking up all tools and DMing teammates, employees just search in 1 place and get the exact information they need. It’s like using Google - but a private one that has results from all your apps, docs, databases, tables, spreadsheets, etc.

Enterprise search solutions do that by identifying and enabling the indexing, searching, and display of specific content to authorised users across the enterprise. But let’s understand more about why it’s important in the first place.

So, why is Enterprise Search so important?

Enterprise Search is important because it saves millions of dollars in company time that would’ve been wasted in searching for information.

McKinsey says employees spend 1.8 hours every day searching for information. And the number is likely to go up with every new email, doc, or spreadsheet your company creates.

While 1.8 hours/day doesn’t seem a lot, the power of compounding shows exactly why it’s a huge problem. As per our Time Saving Calculator, a company with 500 employees making an avg. $60,000/yr could be saving a whopping $89,710/yr if they dealt with the everyday questions about information access amongst employees. But there’s a lot more pros.

How does Enterprise Search work?

Enterprise Search works in 4 phases. Here they are:

  1. Data Collection & Indexingsome text
    1. Crawling: The enterprise search engine uses web crawlers (similar to web search engines) to explore data sources and identify relevant content.
    2. Data Transformation: Extracted data from various formats is transformed into a structure that the search engine can understand.
    3. Indexing: The transformed data is organised into a searchable index, much like the index of a book, allowing for quick retrieval.
  2. Query Processingsome text
    1. User Query: A user enters a search query (keywords or a natural language question).
    2. Query Understanding: The search engine analyses the query, potentially using techniques like natural language processing (NLP) to understand the intent behind the search.
    3. Searching the Index: The search engine looks for matches between the user's query and the contents of its index.
  3. Result Ranking & Presentationsome text
    1. Relevance: Results are ranked based on how well they match the query. This can involve factors like keyword occurrence.

Ishaan Gupta
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Ishaan Gupta is a writer at Slite. He doom scrolls for research and geeks out on all things creativity. Send him nice Substack articles to be on his good side.

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