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What is happening to Search and Discovery? Interview with Nate Barad from Algolia | RetailTechPodcast
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What is happening to Search and...

What is happening to Search and Discovery? Interview with Nate Barad from Algolia

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What is happening to Search and Discovery? Interview with Nate Barad from Algolia


 

⇒ Background

Search and discovery in e-commerce are undergoing a major transformation driven by AI, reshaping how people find and interact with products. Here’s a high-level overview of what’s changing:

From Keywords to Intent: Understanding What Shoppers Really Mean

Traditional e-commerce search engines relied on keyword matching—if you typed "red dress," you'd get every product tagged with those exact words. Now, AI-powered search uses natural language understanding, vector embeddings, and semantic search to grasp intent behind the query.

Example: “What should I wear to a beach wedding?” yields curated options, not just literal results.

 

From Static Search Boxes to Conversational Interfaces

Shoppers are moving from typing in a static search bar to conversing with AI assistants—via chatbots, voice, or even video.

AI shopping assistants help users browse, compare, and decide—like a digital store associate.

Search is becoming interactive, multi-turn, and feels more like a conversation than a query.

 

From Search to Discovery

Historically, shoppers had to know what they were looking for. Now, discovery is part of the journey:

AI curates personalized recommendations based on browsing, purchase behavior, and preferences.

Dynamic collections and guided shopping tools (like Algolia’s Shopping Guides) proactively present relevant options without requiring a specific query.

Visual discovery (e.g., "show me similar styles") allows exploration via images instead of words.

 

From One-Size-Fits-All to Hyper-Personalization

AI tailors results to each shopper:

Takes into account context (device, location, previous behavior).

Adjusts ranking dynamically—two users may get different results for the same query.

Enables zero-click experiences (e.g., showing exactly what the user wants on the homepage without a search).

 

From Search to Decision and Conversion

Search no longer ends with a list of links—it’s now part of the decision-making engine:

LLMs help summarize reviews, highlight product differences, and explain specs.

AI generates comparison charts, FAQs, and even product guides on the fly.

Helps overcome choice overload by acting as a trusted guide, not just a search tool.

 

From Static Catalogs to Real-Time Intelligence

Search and discovery now reflect real-time inventory, pricing, availability, and promotions.

AI adapts dynamically, even re-ranking products based on store stock or trending items.

 

⇒ Interview

In this conversation I speak with Nate Barad on how Algolia is tranitioning search software to the new age of conversational discovery.

Algolia is a search and discovery API platform focused on delivering fast, relevant, and customizable search for web and mobile apps. It provides a hosted search engine that lets developers integrate real-time, typo-tolerant search with features like:

InstantSearch.js and front-end SDKs

AI-powered relevance tuning

Personalization and merchandising tools

A/B testing and analytics

Dynamic re-ranking

Key Industries Served by Alogolia include ecommerce (e.g., LVMH, Gymshark), media & publishing (e.g., Medium, NBC), SaaS / enterprise apps and marketplaces

 

Watch on YouTube.

Apple Podcasts.

 

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