In this article, I have highlighted the key trends in the search analytics software industry that you should know and how analytics certification could prove to be a useful resource in this scenario.
Enterprise search analytics is a huge market. Almost every company is investing in some way or the other to improve their overall search analytics that directly influences the effectiveness of their sales and marketing capabilities.
AI is the cornerstone of Enterprise Search
AI-powered enterprise search is already making big waves in the industry. A majority of the leading analytics certification programs are designed keeping the enterprise search management practices in mind. AI based search platforms are mostly designed to deliver on DIY (Do It Yourself) concepts, and thus offer a highly flexible model to users when it comes to deploying, configuration management, maintenance, and software update mechanisms.
According to the leading industry resources, enterprise search is defined as the technique of identification, discovery, and analysis of various content types from diverse sources, such as databases, intranet, internet, and user generated content. These are searchable by a set population of users, mostly authorized by the company that is producing the content in the first place. In the last 5-6 years, we have seen a large volume of such enterprise content getting a restricted access from the developers, even as the concept of Open Web has taken a new flight in the recent months.
The software that is used to manage the enterprise content is called Enterprise Search software. The commonly used Enterprise Search software would do Indexing, Query Processing, and Matching of reference source documents and return the query to the Content Management Systems. If the content type is in a non-text format, it would be indexed in Digital Asset Management (DAM) systems.
The whole idea of having AI do your search management ensures that there is absolutely no error or deviation in your final outcomes.
So, what type of AI is used in the modern enterprise search management tools?
We are seeing all kinds of AI technologies being used in the systems. These could be deployed for search workflow, automation, security and identity management, or for collaboration. In the last 18 months, the enterprise search software has moved into a comfortable space that allows users to embrace remote working through wide ranging collaboration platforms.
When we speak only of AI in enterprise search software, these could be of the following types:
Semantic Search – It is a simple query search that employs text analytics and image processing techniques.
NLP: When we have to discover data from tons of historical documents and call records, analysts use natural language processing techniques. These could be used to process voice data, caller information, and so on.
Voice Search: This is a sub-field with an NLP stack that allows users to focus only on the voice part of the database. This is used extensively in modern contact centers and customer services management teams, such as Amazon, Flipkart, Airtel, and others.
Are we ready for Augmented Search?
A countless number of analysts are debating over the future of enterprise search capabilities. One such debate discusses the potential entry of augmented enterprise search that is attributed to the popularity of AWS, Elasticsearch, and Solr search engines. Cloud-based search is definitely spreading its roots deep and far, and it would be reckless for analysts if they miss augmented search capabilities in the current context of business intelligence tools.
Search teams are adding advanced capabilities to their existing resources, and these are mostly used for enhancing the security posture of their database. We know numerous instances where search databases have been a target for cyber threat agencies that use the target to steal valuable data, and in return for the data theft information, seek a ransom. This is called the ransomware, which can be erased to a certain extent by using advanced AI capabilities or augmented predictive intelligence focusing on security angles.
AI-enhanced security search databases could be integrated with any other database and further refined for delivery outcomes. This is what makes modern recommendation libraries so powerful. You can see this in Netflix, Amazon, and YouTube algorithms.
There are many developments and innovations happening at the same time within the SaaS enterprise domain, we should keep an eye on AI.