How to leverage AI Search to transform your help portal into a customer self-service hub

Kshitij Gupta

May 5, 20238 min read

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Customer support leaders have been implementing self-service capabilities to decrease call volume and operating costs. However, these efforts may go to waste if customers bypass self-service channels altogether.

With the rise of self-service expectations, customers seek more than just frequently asked questions (FAQs). They want to have quick and easy access to the information they need without having to spend time navigating complicated portals or sifting through large knowledge bases. When they can't find what they're looking for, it can lead to frustration and a need to reach out for help from support or coworkers.

According to Gartner, as many as 37% of customers prefer to pick up the phone rather than attempt self-service channels. This occurs during the search stage of the customer service journey, which is often overlooked by the customer support leaders. This experience is not beneficial for anyone involved, as it interrupts workflow and can overload support agents with repetitive requests.

However, improving search results can be a challenging task for organizations. It often requires significant time and resources to make even small improvements, particularly in complex and ever-changing environments of information.

Thanks to recent advancements in AI algorithms, implementing intelligent search features can now be accomplished in a much shorter amount of time and at a lower cost compared to traditional methods.

Table of Contents

What is intelligent search?

Intelligent search, which is powered by artificial intelligence technology, can break down data silos and enable employees and customers to locate the information they require with ease and efficiency.

With intelligent search, end-users have the ability to extract information from various sources both inside and outside the company, regardless of the format. This includes big data in databases, digital content, webpages, document management systems, or even on paper.

Unlike traditional keyword-based searches, it utilizes machine learning to identify user intent based on contextual cues and delivers highly relevant information. Intelligent search can also be referred to as enterprise search, smart search, natural language search, AI search, AI-powered search, or cognitive search.

One of the key advantages of AI-powered search technology is its ability to allow for automatic tuning, meaning that the system can adapt and improve over time without manual intervention. This process involves analyzing user behavior to understand their intent and preferences. For instance, if users consistently click on the third entry in the search results, the system recognizes that it is the most relevant and adjusts the ranking accordingly. This results in a more efficient and effective search experience for users.

Moreover, AI search can also leverage natural language processing (NLP) to understand the intent behind search queries and produce more accurate results. NLP algorithms can identify synonyms, antonyms, and other semantic relationships to produce a more comprehensive list of results. This enables users to quickly and easily find the information they need without the frustration of sifting through irrelevant or incomplete results.

In this blog, we'll delve into the world of artificial intelligence search capabilities and how they power lightning-fast search processes. By leveraging the latest in AI and machine learning, these search technologies are able to quickly provide users with personalized and relevant recommendations, fulfilling their information needs in a matter of seconds.

Pain points with legacy search solutions

Are you struggling with legacy search solutions that don't seem to be meeting your company's needs? You're not alone. Many businesses are finding that their traditional search methods simply aren't effective in today's digital landscape. Let's take a closer look at some of the pain points that come with legacy search solutions.

Irrelevant suggestions

Legacy search engines rely on keyword matching in titles and are unable to understand the context or intent behind a search query. This often leads to irrelevant suggestions and makes it difficult to find the most relevant content or information.

For instance, when searching for "how long does it take for a sim card to be activated", the legacy search may only match the keywords "how long does it take" without fully understanding the context of the query, resulting in irrelevant search results.

An image showing irrelevant suggestions prompted by a user query

No handling of typos/special characters

Legacy search engines lack the ability to handle typographical errors and special characters, such as extra spacing or operators like hyphens. As a result, users may receive inconsistent or irrelevant search results. For example, if a user types in "prodcut" instead of "product", the legacy search engine may not be able to correct the typo and will instead suggest different search results. Additionally, if a user includes a hyphen in their search query, the legacy search engine may not recognize it as an operator and will provide different search results than what the user intended.

An image showing search results for iPhone 8, 11 and X series for a query about iphone-14

No recent and brand-approved content on top

The legacy search engine is unable to prioritize recent and approved brand content for relevant searches. As a result, outdated and irrelevant information is often displayed at the top of search results, causing frustration and dissatisfaction among customers and users.

No featured results support

Legacy search engines are not designed to highlight specific posts or content for certain searched keywords. This means that helpful and relevant content may not be prioritized and may be buried within search results. This can create a poor user experience, especially for customers seeking quick answers to their questions.

No personalization based on user behavior

Legacy search engines have another limitation in terms of personalization based on user behavior. They are not equipped to identify user patterns and utilize feedback to refine search results for frequently searched queries. Due to this, the legacy search is unable to optimize results for common search behaviors, resulting in suboptimal content suggestions.

The inadequacy of legacy search in meeting such basic requirements can lead to dissatisfaction and reduced engagement with the platform. Therefore, leveraging AI-powered search solutions can address these limitations and enable businesses to deliver a more personalized and effective search experience.

How AI search can help

AI-powered search for customer self-service has many advantages. Let's take a closer look at them.

Understands the intent behind the query

With smart AI search, users can quickly find the information they are looking for without having to go through multiple searches or use different phrases to get the desired result. This is because smart search can understand the context and meaning behind a query, allowing it to suggest the most relevant and contextually sound results to the user.

As a result, users can save time and effort in finding the information they need, leading to a better overall experience.


An image showing relevant search results for a query

In this image, the AI-powered search demonstrates its ability to comprehend the intention behind the user's query and provide the most fitting and relevant results at the top, unlike legacy search engines that rely solely on keyword matching.

Handles typos and special characters

The AI-powered search technology has the ability to recognize and account for common typing errors that occur during a search query. This saves users time and effort that would have been spent correcting mistakes. Additionally, AI technology is able to interpret the usage of various operators, such as hyphens and different spacings, to provide consistent and accurate results.



Provides the latest and brand-approved content on top

By leveraging AI algorithms, businesses can easily identify and prioritize content that is most relevant to their customers, and promote it to the top of the search results. This not only enhances the customer's search experience but also increases the likelihood of them finding the right solution quickly and efficiently.

Furthermore, AI search can also feature specific results for particular keywords present in a customer's query, providing even greater control over the search results.

One index, multiple sources

Furthermore, the AI search integration enables different types of content, such as knowledge base articles, community posts, and custom pages, to be retrieved from a unified index without the need for customization. This allows users to conveniently browse all content at once, without having to navigate between different platforms or sources.

Additionally, having a unified index allows for better tracking and analysis of user behavior, enabling brands to gain insights into user search patterns and preferences, which can be leveraged to improve the overall self-service experience.

Personalized results

AI search can also provide personalized results based on the customer's search history and behavior. This means that if a customer frequently searches for a particular topic, the AI-powered search engine will learn their preferences and start prioritizing results related to that topic.

Key takeaways and closing thoughts

  • Legacy searches rely solely on keywords, while AI-powered searches use contextual understanding to provide relevant results.

  • With legacy searches, even small variations in the query can lead to inconsistent results, but AI algorithms can handle these variations effectively.

  • Legacy searches also fall short in displaying brand-approved and recent content for relevant queries, resulting in poor search outcomes, whereas AI-powered searches prioritize such content.

  • Additionally, AI searches offer other advantages such as featured results, dynamic re-ranking and the ability to personalize search results using feedback from users.

This is just the tip of the iceberg when it comes to the potential benefits of integrating AI search into your business. As AI technology continues to advance, the potential of taking your customer self-service to the next level through AI search is limitless.

If you have any inquiries or would like a personalized demonstration of how Sprinklr AI search can revolutionize your operations, check out our Self-Service tool today.

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