Deep: The UX of Search Explored
How in-product search functionality is evolving. Real world examples from Instacart, Pinterest, Asana, Google, Linear and more.
🔒DoP Deep goes deeper into the concepts and ideas that are covered in the Weekly Briefing to help you learn lessons from the experiences of top tech companies. If you’d like to upgrade to receive these in-depth pieces of analysis you can upgrade below. New reports added every month.
The ability to search and find exactly what you need inside a product can play a critical role in engagement and retention; a user who can’t find what they need is ultimately a user who churns. For many leading companies, AI has transformed in-product search from a simple find-and-retrieve function into something more ambitious: visual, conversational, and capable of taking actions.
In November, LinkedIn announced major changes to its global search UX, Rippling shipped a new feature that displays the profile photo of a person when you search for them and Instacart recently confirmed that its search results now include AI generated images of items using an in-house proprietary image generation model called PIXEL.
If you look closely at the prompt text used in many leading products’ search bars, you’ll now notice that users are now prompted to not only search for something - but to “ask a question” too - signalling the shift towards the merging of traditional search with AI Assistants.
For product teams, understanding how the UX of search is evolving can help you to think about engagement and retention tactics that you may not have previously considered. It’s been a full year since the last time we explored in-product search UX and in this second edition of the UX of Search, we’re going to take a closer look at 20+ new examples of how in-product search has evolved since then with real world examples from YouTube, Asana, Instagram, DoorDash, Linear and others.
We’ll dig deep into their UX and identify some of the key trends and themes that matter to product teams.
Coming up in this new UX of Search Deep Dive:
20+ real-world examples of how search is being reimagined across B2C, SaaS, and ecommerce - with downloadable UI examples you can keep and use as a reference
The hybrid search pattern that’s quietly taking over major products - where traditional search and AI Assistants merge into a single interface
Why one company’s “Search-Forward UX” strategy drove a 20% increase volume - and how they balanced traditional search with conversational AI
Why search bars are quietly becoming command centers - and how one company’s search capabilities became powerful enough to justify an entirely standalone product
The new UX patterns that companies like Instagram, DoorDash, and LinkedIn are using to help users search without typing a single character
All of the 20+ examples in full
What’s included in this UX Deep Dive report
This analysis goes deep into some of the newest ways users can search in products. Here’s a snapshot of some of the examples featured:
How this analysis is structured
The full report includes 20+ real world examples of how search is implemented in products that span across B2C, SaaS, ecommerce and more. Each example is broken down into:
Company - the Deep dive includes examples from DoorDash, Pinterest, LinkedIn, Google Maps, Cursor, and more.
Search feature / type - the report focuses mostly on innovative new ways that users can search in products with a further breakdown of the UX components of that specific search feature to follow. Search feature types include new experimental generative AI carousels in YouTube search results, visual and semantic search and hybrid search where traditional in-product search is combined with AI Assistants to offer different search experiences inside one interface. This is becoming increasingly common and we’ll explore some examples together.
UX components - each example is tagged with the core UX components that power that specific search functionality - more on that below.
How it works - an explanation of how the search feature works.
UI example - downloadable UI images and videos that you can download and save for future reference.
Link to more info - links to more information to learn more about the search feature in more depth.
The different UX components explained
The UX components focus specifically on the search feature / functionality that’s included in the report, with over 10 different components. This includes:
Carousels - Horizontally scrollable result sets, often grouped by category or type. Common in e-commerce and other content discovery contexts. This allows multiple result categories to coexist on screen without overwhelming users and works well on mobile. Airbnb, Miro, Netflix, Google Maps and others all now use carousels in some form.
AI integration - search experiences that use AI to understand intent, generate results, or provide conversational interfaces. Some companies like Reddit, Amazon and others are increasingly combining AI with traditional search to create hybrid interfaces. We’ll dig into these together.
Search suggestions - dynamically displays possible queries or results as users type, helping them refine or complete their search faster.
Quick filters - predefined options that allow users to narrow search results instantly. DoorDash uses smart tags like “Gluten Free” or “Spicy” to help users quickly refine food discovery.
Advanced filters give users detailed options like date ranges, content types, or tags to refine search results further.
Actions - search functionality that doesn’t just find content but triggers workflows or commands. This is where search starts to converge with command palettes and AI agents.
A deeper look at examples from companies featured
Now let’s dig deeper into some of the examples of the UX of search included in this analysis. As well as digging into the examples in more detail, this analysis also examines some of the key emerging themes and insights that are relevant for product development teams.
We’ll start with some of the ways that AI is transforming in-product search functionality and opening up new opportunities for product teams to drive engagement.