Search and Discovery

eCommerce
Ecommerce search and discovery refer to the process of helping users find products efficiently and discover new items that match their preferences or needs.

Top Search and Discovery products, platforms, SaaS and solutions.

Ordered alphabetically by name.

EPOQ

1:1 personalization in e-commerce makes online shopping an experience and ensures an increased conversion rate
EPOQ website

KLEVU

Join thousands of ecommerce teams achieving up to 8% site-wide and 16% search conversion rates with Klevu AI search, merchandising, and product recommendations.
KLEVU website

Lily

Lily AI connects your customers with the relevant products they’re looking for.
Lily website

Lucidworks

The secret superpower of the world’s top brands Lucidworks powers the search and discovery experience for the world’s largest and most successful companies.
Lucidworks website

reccodo

eCommerce Personalization Engine. Boost your sales by creating personalized experiences that will turn your users into loyal customers, with personalized product recommendations and search results.
reccodo website

Recombee

Become the architect of your success with our AI personalization engine designed to align with the visionary strategy of product managers and tech teams.
Recombee website

Here are some key aspects of ecommerce search and discovery:

Search Functionality:

  • Keyword Search: Provide a robust search bar that allows users to enter keywords or phrases to find specific products quickly.

  • Auto-Suggestions: Implement auto-complete or auto-suggest features that offer suggestions as users type, helping them find relevant products faster and reducing spelling errors.

  • Search Filters: Offer advanced search filters to refine search results based on criteria such as category, price range, brand, size, color, and other attributes.

  • Faceted Search: Enable faceted navigation, allowing users to drill down into search results by applying multiple filters simultaneously.

  • Synonyms and Misspellings: Account for synonyms and common misspellings in search queries to ensure users still find relevant results even if their search terms are not exact.

Product Discovery:

  • Recommendation Engines: Utilize recommendation algorithms to suggest products based on user behavior, purchase history, browsing history, and preferences.

  • Personalized Recommendations: Provide personalized product recommendations tailored to each user’s interests, demographics, and past interactions with the site.

  • Trending and Popular Products: Showcase trending items, best sellers, or popular products to help users discover what’s currently popular or in high demand.

  • New Arrivals: Highlight new arrivals or recently added products to keep users informed about the latest additions to your inventory.

  • Cross-Selling and Upselling: Implement cross-selling and upselling strategies by recommending complementary or higher-priced items to users based on their current selections.

  • Image Search: Allow users to search for products using images, either by uploading a photo or using their device’s camera to capture an image.

  • Visual Recommendations: Offer visual recommendations based on the appearance or style of products that users are currently viewing or have shown interest in.

Enhanced Product Information:

  • Rich Product Data: Provide detailed product descriptions, specifications, images, videos, and customer reviews to help users make informed purchasing decisions.

  • User-Generated Content: Showcase user-generated content such as customer reviews, ratings, and photos to offer social proof and enhance product credibility.

Continuous Optimization:

  • A/B Testing: Conduct A/B testing on search functionality, navigation elements, and recommendation algorithms to optimize the user experience and improve conversion rates.

  • Data Analysis: Monitor user search behavior, click-through rates, and conversion metrics to identify patterns, trends, and opportunities for improvement.