What is Enterprise Search?

Enterprise search is technology that effectively connects and indexes content from your organization’s diverse repositories and file types, making it easier for employees to find information. Intuitive enterprise search engines achieve this by connecting all your data silos into one unified data repository, making it possible to search across your entire information ecosystem.

The experience can be frustrating for employees who often need to dig through data silos and disconnected systems like email, Slack, and the corporate intranet to find an elusive document or asset. This takes time and can be demoralizing for employees, particularly new hires, who may spend hours each day searching for the content they need to do their job. 

Enterprise search technology helps solve this problem by combining data, good UX design, intelligent algorithms, AI, and ML to create the perfect information retrieval system.

Examples of Enterprise Search

Enterprise search is a tool for businesses. It enables employees and internal stakeholders to securely search for proprietary company information from internal and external digital sources. It’s not Google, indexing every web site across the planet. Rather, it’s a search application for your organization’s digital assets which may include things like your website, Intranet, cloud file servers, Slack, CRM platform, and more. It must be secure and supremely relevant for it to be useful.

Common Enterprise Search Use Cases:

• Website search – Thanks to sites like Google and Amazon, most of us expect website search to be easy and relevant. What that means for companies is that your search functionality – whether it’s for employees or customers – must provide the same kind of search experience as the big guys. That is, personalized search results that are relevant, helpful, and tailored to the individual user’s needs. A robust enterprise search engine makes the whole user experience much better.
• Customer self-service – Effective enterprise search gives customers access to a host of digital content like FAQs, product documentation, troubleshooting guides, and blog posts. It enables people to find answers quickly and on their own. This leads to a couple of positive outcomes. First, it makes the customer experience a more satisfying one. It also reduces the volume of inquiries to your call-center customer service team, while making information more equally accessible to agents and internal employees.
• Call center support – Call centers field hundreds or thousands of incoming questions every day, which is why it’s critical that call center agents have a comprehensive search tool. AI-powered enterprise search allows call center agents to find relevant info in a snap during customer calls. It’s a time saver that helps agents provide top-notch service and resolve customer issues.
• Team support from anywhere – It is also important for internal teams, like sales reps or support staff who rely on it to access important data, product details, or case histories. Since it’s constantly indexing and updating your digital content, it makes the most recent information available. This means that new hires, remote workers, and employees at all levels have access to the most current documents, policies, training materials, and other resources they need to do their jobs.

How does Enterprise Search Work?

Your company’s knowledge is like an enormous library filled with resources that include many things – your employee handbook, past pitches, customer information, blog posts, product information, brand guidelines, webinars, meeting notes – you get the idea. It’s a body of knowledge that’s large and constantly changing. 

Enterprise search acts like a librarian with the robotic recall and speed of Data from Star Trek. Using AI and ML, enterprise search solutions can instantly find any piece of content and use the context of the searcher to present information that’s relevant. 

Before enterprise search can work its magic, it needs to centralize the information scattered across your organization’s various data silos. This process, called data unification, connects all your repositories, whether they’re on-premises or in the cloud, structured or unstructured. This breaking down of information silos is what makes all your knowledge accessible from one place.

Once the data is unified, the enterprise search engine crawls and indexes everything. It’s constantly updating this index, so the information is always fresh. When an employee performs a search, the engine uses AI and natural language processing (NLP) to understand what they’re looking for. It goes beyond matching keywords, recognizing patterns and connecting intent to real-language search queries. 

The search tool deciphers search intent based on what it knows about the searcher. It can also be programmed with permissions that restrict access to certain information for certain user profiles. This keeps sensitive information secure while still providing useful information, ranking results based on relevance and presenting them in a user-friendly way.

Key Enterprise Search Features

• Connectors integrate your data sources, regardless of format or location.
• Security controls ensure only authorized users can access sensitive information.
• AI and ML work to continuously improve search relevance based on user behavior and search patterns.
• Natural language processing allows users to search using everyday language instead of specific keywords.
• Intuitive user interface with features like autocomplete, faceted navigation, and personalized results for easy information discovery.

What are the Different Approaches to Enterprise Search?

Enterprise search solutions can take different approaches to deliver powerful, relevant results and enhance the user experience. Some key differentiators include:

• Advanced NLP capabilities – NLP is what allows the search tool to better understand a searcher’s intent even when the query they use don’t exactly match the document or content. 
• Machine Learning – Sophisticated ML algorithms continuously optimize search results based on user behavior. This is an iterative process, so that results become more relevant as the engine “learns.” 
• Personalization – Some enterprise search solutions like Monetate tailor results based on a user’s past behavior, in-session actions, or contextual factors like location or weather.
• Integrated Capabilities – It is most powerful when it’s integrated with other key capabilities, like product recommendations, A/B testing, and customer segmentation. 

In Monetate’s case, personalized search is a component of our broader personalization platform and part of what creates a powerful end-to-end digital merchandising and discovery experience. 

Enterprise Search Vs. Site Search

Enterprise search isn’t synonymous with website search, though it often incorporates your company website into its mix of digital sources. Think of website search as your company’s front door. It’s limited to your website only and helps visitors find what they need using the website search function. 

Enterprise search is more like a backstage pass. It lets employees and internal stakeholders like consultants search across your company’s digital content, from documents to databases. It gives employees access to information that’s not typically available to the public.

Benefits of Enterprise Search Software

The major benefit to using enterprise search is that it helps both customers and employees find information easily and quickly. From a retail perspective, a good enterprise search engine is mandatory since it’s how customers find the item they need on your website or app, no matter how big your catalog is. 

But it’s not just about happy customers. Enterprise search also makes your employees’ lives easier. Your customer service team can quickly find product specs, reviews, or shipping info to answer questions. It also gives your marketing and sales teams access to past campaign materials, sales performance data, and customer behavior data. Since it’s connected to internal resources and databases, it enables employees to locate approved brand messaging and assets to help create messaging, offers, and content.  

AI and ML make it possible for enterprise search engines to improve over time. They get better at understanding user context, recognizing NLP queries, and connecting employees and customers with the most relevant information in real time. 

Enterprise Search Trends

There are a few recent trends contributing to the need for more efficient, AI-driven enterprise search. A push towards improving total experience is requiring that companies optimize search for all users including customers, employees, and other stakeholders. Enterprise search is a great way to connect customers and employees with the right information via a more intuitive UX that aligns multiple platforms and disparate sources of information. 

The rise of conversational search also plays a role in how companies provide and present information to users. Voice assistants like Apple’s Siri and Amazon’s Alexa are training people to search using natural language queries versus typed keywords and phrases. These search tools also use past user behavior, first-party data, and searcher context to customizer results.

In short, the way people search for information is changing. This means your approach to how you optimize, align, and present content also needs to change. The search experience is, increasingly, a personal experience. Expectations about how results are presented, including relevance, are high. Corporate search results must reflect individual user needs.  

Another big trend is economic uncertainty, which Retail Dive reports as a continuing issue this year. This naturally has a huge impact on the retail industry. With consumer budgets tight and competition stiff, companies need to invest in personalization and improved digital shopping experiences. Powerful enterprise search is an effective way to achieve both.