Consumer behavior trends are shifting. Only 7% of people use single-word queries when searching for products online, while 56% use three or more words. [1].
These statistics underscore a pivotal transition in search dynamics, emphasizing the limitations of traditional search engines in capturing the nuanced demands of modern consumers.
The advent of conversational search emerges as a critical solution to this challenge, offering a more intuitive and human-like interaction with ecommerce platforms.
What is Conversational Search in Ecommerce?
Conversational search allows users to interact with an ecommerce (or any other) search engine using natural language.
It differs from a traditional search that relies on matching search results with precise, short keywords. Instead, conversational search enables users to write longer and more abstract queries, express preferences, and get personalized and relevant results.
Conversational search is already (and will be) the next big thing in the ecommerce world.
Why?
Let’s take the market’s giants as an example. Amazon is about to upgrade its already effective conversational product search to a Chat GPT-like search [2]. The company focuses on helping users find answers to questions, compare products, and receive personalized suggestions.
The same applies to LupaSearch - the e-commerce search that uplifts e-commerce search businesses with a rewarding search solution. Precisely, LupaChat LLMs offer a conversation-like search experience that turns abstract user questions into human-like answers.
Conversational search represents a paradigm shift in ecommerce, enabling users to communicate with search engines using natural language rather than relying on specific, keyword-driven queries.
This approach facilitates a more dynamic interaction, where users can express complex preferences and receive tailored recommendations, thereby significantly enhancing the shopping experience [3].
Don’t miss the chance to become a part of the future.
How Can Your Business Meet Changing User Needs?
User behavior has changed.
People stopped thinking of a highly specific keyword when searching for a product. Now, they type longer, more natural-sounding search queries and leave them to the search engine to process.
For instance, instead of typing a narrow, keyword-like search query as a salad dressing, users now might search for sugar-free dressing for spinach salad.
Most traditional search engines would fail to deliver products that match all criteria: sugar-free, salad dressing, and goes well with spinach.
But advanced, AI-driven site search can.
Therefore, the conversational search can provide your business with multiple benefits:
Improved user experience
By delivering highly matching search results, conversational search drastically improves user experience on your e-shop.
It allows users to express their needs and preferences in natural language. For example, on a LupaSearch-driven e-shop, a shopper can type “show me red dresses under $100” or “I need a gift for my mom’s birthday” and get results that match their query.
That’s the beauty of LupaChat - a Large Language Models-based search.
More personalized experience
Conversational search delivers more personalized and relevant results. That is because the search analyzes more than just a search query. It also considers the user’s context, intent, and behavior.
For example, LupaSearch - a conversational and highly personalized search engine - can use the user’s approximate location, recent search history, and preferences to tailor the results to their needs.
Reduced bounce rates
The more relevant the search experience, the more likely users will stay on the e-shop (and convert).
Conversational search effectively reduces bounce rates and increases retention and loyalty.
For example, a conversational search engine can keep the user engaged by providing relevant and diverse results and offering incentives and rewards.
How to Implement Conversational Search in Your Ecommerce Platform?
Achieving optimal conversational search functionality involves several key strategies, including multilingual support, ambiguity resolution, synonym integration, and the enablement of faceted search.
These components collectively contribute to a conversational search engine’s ability to understand and process user queries in all their diversity and complexity, ensuring that the search experience is as intuitive and effective as possible [4].
Steps: How to exploit conversational search in your e-shop?
Maximizing the effectiveness of the conversational search takes work unless you know how.
The best application is to integrate an e-commerce search solution like LupaSearch that supports conversational search (with LupaChat LLMs) and, therefore, unlock the added benefits.
Support different languages
A conversational search engine has to deal with synonyms, slang, spelling errors, negations, and other linguistic variations. Not to mention different languages users might search for your products in.
Pick a site search (like LupaSearch) that supports multiple languages and delivers relevant search results regardless of the language.
Handle ambiguity
Sometimes users’ queries are too vague to deliver matching products. In such cases, the most important thing is to provide something.
Empower such search engine features as did-you-mean functionality or similar suggestions.
By providing alternatives to users’ search queries, you can avoid guiding users to a blank page of zero results and make them stay longer in your e-shop.
Add synonyms
Users name the same products differently, depending on culture, location, native language, and jargon.
Make sure to include those differences in your site search strategy.
Continuously monitor search results and trends and add synonyms for most-searched words.
Or, if you pick LupaSearch as your e-commerce search partner, you can set it up to add the synonyms automatically, using the AI.
Support faceted search
Sometimes users search for a highly specific product, clearly stating the product’s size, color, price, or other attributes.
Make sure your ecommerce search supports faceted search and can automatically assign relevant (dynamic) filters accordingly to the search query.
For example, when a user searches for “show me blue sneakers under $100” or “I want cheap sneakers,” make sure to deliver the products that fit the criteria. In the case of LupaSearch, this solution would automatically assign query-relevant product filters: blue, cheaper than $100, and sneakers.
Ready to Uplift Your Ecommerce Search Experience?
Conversational search is a powerful tool for your ecommerce businesses to improve the user experience and drastically boost conversion rates.
Conversational search is not just an enhancement but a necessity for ecommerce platforms aiming to meet the evolving needs of their users.
Don’t miss the next big thing in ecommerce.
Schedule a demo with a LupaSearch product consultant, and let’s see how effective ecommerce search can benefit your business.
References
Tom Demers. The Long Tail Keyword Optimization Guide – How to Profit from Long Tail Keywords. October 1, 2022. WordStream. https://www.wordstream.com/blog/ws/08/03/09/long-tail-guide.
BY MATT DAY / BLOOMBERG, MAY 16, 2023. Amazon Plans to Add ChatGPT-Style Search to Its Online Store. https://time.com/6280051/amazon-artificial-intelligence-product-search-jobs/.
Penha, G., Bălan, A., & Hauff, C. (2019). Introducing MANtIS: a novel Multi-Domain Information Seeking Dialogues Dataset. ArXiv, abs/1912.04639. doi:10.48550/arXiv.1912.04639. https://arxiv.org/abs/1912.04639.
Papenmeier, A., Frummet, A., & Kern, D. (2022). “Mhm…” – Conversational Strategies For Product Search Assistants. ACM SIGIR Conference on Human Information Interaction and Retrieval. doi:10.1145/3498366.3505809. https://dl.acm.org/doi/10.1145/3498366.3505809.