Features of Enterprise Search Software
An enterprise search tool is used to organize and provide data to internal users. Large businesses are producing an increasing amount of data, making it difficult and expensive to identify relevant information without the proper search tools. Enterprise search aims to address this issue. You will discover the use cases for corporate search and how it functions in this post.
When shopping around for enterprise search software, it’s essential to look at various features. In addition to the functionality of your platform, consider the vendor’s experience in helping businesses deploy a solution. Ideally, the vendor will partner with you to tailor the solution to your business’s unique requirements.
A leading enterprise search software to look for various features to help the business.
Faceted search
One of the most useful features of enterprise search software is its faceted search feature. These search features allow for more specific search results, which helps to reduce the total number of results a user has to filter through. Whether a user is looking for a specific course, subject, or topic, facets allow for a more targeted search. As a result, users can easily refine their search without learning complex syntax.
When implementing facets, however, enterprise search software vendors must be aware that too many facets can overwhelm users. Therefore, the number of facets should be appropriate for the use case and the level of user savviness.
Relevancy management
An enterprise search platform should have features that enable it to integrate data from multiple sources and manage relevance. This solution will reduce manual searches in specific departments and help managers make better decisions based on data. The software vendor should be able to work with the organization to customize the solution to meet its needs. They should also have a history of helping other businesses deploy their solution.
Relevancy management features of enterprise search software should include aggregating logs and extracting relevant words and phrases from unstructured data. Relevancy management features should also measure how the information is distributed across multiple channels. A good solution will also offer analytics on the number of clicks and abandonment rates. This information can then refine the results and make them more relevant.
Data source connectors
Enterprise search software relies on data source connectors to access data from various sources. While this may seem easy to implement, creating a connector for every data source you may have can be difficult. Thankfully, there are several pre-built connectors and custom integrations available. Enterprise search software can also include additional features such as e-commerce search and customer support search. This feature allows enterprises to use the software as an employee knowledge management tool. In addition, most enterprise search software vendors include connectors to multiple data sources and extract or crawl the content, meaning the software can deliver results more relevant to the user’s intent. These capabilities are essential for delivering valuable employee and customer experiences.
Scalability
Enterprise search software makes it easy for employees to find the right content and data they need, which enhances their efficiency and productivity and can increase their job satisfaction. It can also lead to higher profits. Without a scalable search solution, employees would have to read, assess, and re-read documents dozens of times daily.
Enterprise search software should support millions of queries and connect to multiple systems. It should also provide tools to manage knowledge management among employees. The majority of enterprise search software providers provide a range of connectors for integrating with different data sources, such as CRM, ERP, and other business applications. By contrast, legacy search systems require multiple IT staff members to manage and can only be used by more experienced IT professionals. Additionally, they do not support AI and ML integration.
AI-driven algorithms
Using AI-driven algorithms to power enterprise search software can help businesses understand and engage with consumers. These systems can use machine learning, natural language processing, and artificial intelligence to find the most relevant information for users and deliver personalized content. In addition, the insights these algorithms produce help brand teams better understand how customers engage with their products.
Using AI-driven algorithms in enterprise search software presents a unique set of challenges. First, it isn’t easy to track and measure the performance of AI-driven algorithms without tracking every step of the process. While most enterprise processes are linear, search queries are different. The intent behind a search varies depending on the individual and what they are trying to find. As such, companies must ensure that their AI-driven algorithms are trained on data from existing information sources and are relevant to the user’s needs.
