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Traditionally, consumers would visit retail stores to buy products, but with the rapid rise in digitization and e-commerce stores, the retail industry witnessed a massive transformation. This proved to be a necessary shift as the pandemic forced many offline retailers to adopt a digital strategy as more and more buyers moved online to purchase products.

Since this global shift, consumers have had a harder time finding the right product through the mass of new online retailers. This is made worse as shoppers often struggle to get relevant product search results, leading to a disappointing shopping experience. The exhausting process begins with shoppers entering the queries related to the desired product on the search bar or asking questions through a virtual chat assistant, checking or unchecking filters, comparing product descriptions, and navigating through hundreds and thousands of irrelevant search results that lack context and personalization. It is of the utmost importance for retailers and e-commerce players to think beyond traditional search and reinvent their online search strategy to deliver a better,  delightful shopping experience.

We’ve previously delved into how conversational search overcomes the limitations and challenges of traditional search and offers more natural, contextual, and human-like responses to search queries. Let’s explore it further.

How is Conversational Search Different from Traditional Search?

Unlike traditional keyword-based search, conversational search allows users to submit their queries by using complete sentences or natural-sounding phrases. It leverages AI to understand the customer intent from chat or voice utterances and returns contextual and personalized search results to consumer queries in a more humanized and conversational way.

These days shoppers are more often using natural language to search and discover products online. 

Example of a traditional search query by a shopper

Laptops

In contrast, a conversational search query may look like

Can I get laptops under $3000?

In the above example, instead of "Laptops," the consumer searches for "Can I get laptops under $3000." According to Google, over the past few years, the usage of "I" in search queries has increased by 65%. showcasing that shoppers are now searching with words and phrases like can I, should I, do I need, etc.

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In other words, retailers need to adopt technology like conversational search that can understand search queries asked in natural language and provide consumers with products they are looking for right away. This seamless product search and discovery experience not only saves the shopper time but also gets them closer to the sale, infinitely faster. Conversational search deciphers users' search intent and guides consumers throughout their shopping journey by delivering a relevant, frictionless, and personalized product discovery experience, which helps retailers to convert searchers into buyers. 

How Does Conversational Search Help with Guided Shopping and Improving the eCommerce Experience?

Customers usually leave online stores because they can’t find the right product or because it takes an enormous amount of time to search for it.  Having too many results takes away the joy of online shopping which causes a loss of customers and business. So, what should an e-commerce store do?

Conversational AI has continually proven itself to be the best tool to understand shoppers’ needs and leveraging guided shopping and conversational search is the most efficient way to sell online.

Guided shopping aims to replicate the in-store consultative experience for online buyers. Shoppers start their experience with a few questions, like who the item is for, what is the budget, or what color they want and based on their answers, the most relevant products are displayed to match their needs. This experience creates a smoother online shopping experience and encourages customers to make purchase decisions more quickly.

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As more customers move to digital channels for their interactions with brands, the adoption of conversational marketing is rapidly on the rise. Chatbots are now increasingly viewed as an essential tool in managing an influx of conversations efficiently.

The Rise in Usage of Conversational Search in Retail Chatbots

Over the past several years, leveraging retail chatbots has become increasingly popular. However, when search and chatbots function independently of one another, they simply don't provide a satisfactory user experience. Users often feel confused or frustrated with irrelevant product information because of a lack of context sharing between the two channels. 

Kore.ai SearchAssist, an AI-powered cognitive search assistant with conversational search capabilities, addresses these problems. It offers a unique search experience where users can ask questions or search for information through natural language dialogs. SearchAssist can understand user context, behavior, preferences, and intent and resolves the queries through a unified interface. 

When using conversational search, AI-driven chatbots with conversational search capabilities intelligently guide customers to the right products while providing a personalized online shopping experience.  In this way, it helps increase conversions and reduce the overall sales cycle. Additionally, machine learning capabilities enable them to comprehend customer needs better, share the most relevant product recommendations, and upsell and cross-sell products.

AI-powered chatbots with conversational search capabilities also support shoppers with all aspects of order fulfillment. Customers can use this technology to effortlessly search for and order a product as well as track their shipping status without ever needing an agent’s help.

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Take the example of Belcorp.

Belcorp faced a massive challenge in supporting consultants and consumers to track orders online. Belcorp leveraged Kore.ai conversational AI and search capabilities to build complex use cases like order monitoring and tracking to digitally deliver a superior, personalized, and seamless experience to Belcorp’s consultants and consumers.

We chose Kore.ai because it has established itself as a world-class conversational AI platform. Its sophisticated NLP engine and ability to roll out to various channels quickly have been key factors in our success, and the vertical solutions for retail offered by Kore.ai have allowed us to bring a personalized experience to both our consumers and consultants. The speed at which we were able to move to market is a testament to the value of the Kore.ai platform.

Venkat Gopalan, Chief Digital and Technology Officer at Belcorp

Benefits of Implementing Conversational Search for Online Retailers

1. Increases Cart Value and Boosts Revenue by Assisting Consumers in Shopping Journey
Conversational search not only empowers customers to find, search, and explore the right products based on their needs and preferences but also guides them with personalized product recommendations that further increase cart value and boost revenue.

2. Increases Customer Engagement by Bringing a Human Element Back Online

Conversational search brings the personal and physical in-store shopping experience online. It allows chatbots or virtual shopping assistants to have two-way conversations with shoppers to understand their needs and preferences. Shoppers can ask questions or request product suggestions and pricing through a single conversational interface, leading to increased customer engagement, trust, and brand affinity.

3. Promotes Online Shopping by Reducing Search Efforts for Shoppers

It takes a lot of time and effort to search and find the right product online before finally buying it. Still, online consumers always look for quick and easy shopping options. Conversational search provides the most relevant and contextual search results that help users make buying decisions quickly. 

4. Improves Conversions with Powerful Insights into Users’ Search Behavior 

By analyzing users' search behavior, one can get valuable insights into what users are looking for and how they interact with search results. Using key metrics, including top searches, searches with results, searches with clicks, or most clicked positions, retailers can make necessary changes to improve users' search experience that will further increase conversions.

Final Thoughts

The future of commerce is conversational, and conversational search plays a huge role in reshaping the online shopping experience. With the increased adoption of online shopping in the last few years, e-commerce companies are finding ways to deliver delightful, seamless, and personalized search experiences to their consumers. 

As an experienced tech partner for leading retailers, Kore.ai is happy to help clients take advantage of the conversational search strategy. Are you exploring ways to deliver an unparalleled shopping experience, reduce cart abandonment rates, and improve online conversions? Search no further - click here to learn more about the Kore.ai SearchAssist solution, an AI-powered conversational and cognitive search assistant that provides a unified experience by blending both search and support in a single interface, or try yourself for free or request a demo.

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