The Value of Intelligent Search
for Modern Businesses

The amount of digital content presently available to the average digital end-user is immense. However, customer service brokers must contend with an equally dense amount of digital information so as to deliver a positive customer service experience for their clients. To satisfy both stakeholders who navigate this growing mass of digital content and information, enterprises are shifting towards intelligent search algorithms to alleviate the burden of trawling through the densely packed world of knowledge and information.

What Precisely Is an Intelligent Search?

A smart or intelligent search is a broad term that refers to searching systems that are driven by intellectual machine learning (ML), natural language processing (NLP), and digital artificial intelligence (AI). Intelligent searching contains a semantic vector search, and a thoughtful and cognitive search. By combining these differing ideals, an intelligent search can intuitively comprehend what an end-user is seeking by considering their prior goals, previous searching history, and searching theme. Succinctly, an intelligent search can simplify an end-users ability to find what they are searching for.

How Does an Intelligent Search Work?

Intelligent searching understands the goals and intentions of consumers by incorporating NLP, ML, and semantic vector searching. Both ML and NLP promote the ability to predict and create tailored search results for each end-user. Semantic vector searching ‘learns’ from periodic customer behavior to facilitate queries in a shared vector space – similar to groceries organized in shelves within a physical customer shop or store. Employing these technologies creates an intelligent searching experience that can deduce way beyond the search query that was typed into the search screen field. The outcome permits an end-user to access relevant content for specific research purposes or connect them with detailed product information required for a particular endeavor.

What Makes Intelligent Searching So Important?

Intelligent searching is critical to constructing a meaningful digital experience. Customers have access to an increasing number of resources on the web, making finding what they desire all the more challenging. The amount of information available can impact more than just consumers. Customer assistance agents will also feel the consequences of accelerated digital adaptation. There are more digital support tickets and customer information requests to review and resolve and being able to accomplish so quickly is paramount to retaining the quality of service that customers demand. Having intelligent searching solutions readily available can greatly improve the customer’s ability to locate what they are seeking and the customer support agent’s ability to provide information quickly.

What Are the Key Stakes with Intelligent Searching?

Intelligent searching is a highly personalized process dependent on the end-user. Even more so, several abilities should be a component of every intelligent searching strategy as follows:

Intelligent Searching Should Be Conversational:
A searching session is typically not a single query or a single response set. Instead, it is a natural conversational information flow that forms part of a bigger picture. There is usually a specific goal in mind for the end-user, and they may not understand or grasp the perfect search terms to use. Intelligent searching can fill those data gaps by comprehending how a regular person speaks and responds – and always yield accurate search results.

Intelligent Searching Should Be Natural:
Likewise to the above point, regular people do not think about specific “searching queries.” They want only to input those words or phrases that will describe what they are searching for and hopefully find it within the search results. NLP technology makes it easier for computer searching systems to comprehend what an end-user is endeavoring to convey when they articulate what they are familiar with – and ML makes it easier for computer searching systems to improve that communication process.

Intelligent Searching Should Be Personalized:
Every user has an individual goal set when they are searching for content. With the boundless answers possible for a single search or question, personalization allows intelligent searching to be a consequential experience wherein the end-user can feel totally understood. Personalization can be achieved when the searching system has access to the end user’s prior search history, searching frequency, and other relevant searching metadata. These data elements all add up to create an accurate digital picture of the end-users intention behind precisely what they may be searching for.

Intelligent Searching Must Be Responsive:
To operate a natural and personalized intelligent searching system, brands must hear and understand what the end-users are requesting. They need to understand their genuine intentions and serve searching results only for those true intentions. For example: what if the user traverses backwards to a previous web page and double-checks certain content? Intelligent searching systems must have self-checking cycles built-in within – to understand the consumption of searching queries, and therefore understand the resultant impressions obtained by end-users.

Searching Intelligently

The value of information will continue to mature and grow, and an intelligent searching process has never been more important for enterprises. By being suitably managed, findable information supports more suitable business decisions, it will save time, reduce costs, and minimize implementation risk. But most of all, an intelligent searching process facilitates those organizations to create a competitive advantage over their lagging rivals. Increased deftness, improved service and innovation are key indicators of digital transformation. Moreover, the more adept those companies are at finding information using the right context, the more analytical data will be available to encourage appropriate – and strategic – business decision making.