Deep: The UX of Search Explored
How top tier companies are building in-product search capabilities - and how AI is impacting the future of product search UX
🔒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.
Hi everyone 👋,
The ability to quickly find exactly what you need when you’re using a product can be transformative; get it right and activation and engagement rates may increase. Get it wrong and you risk losing a user who becomes frustrated with not being able to find exactly what they need.
In this Deep dive, we’ll explore how the UX of in-product search is evolving with examples from 20+ leading companies including: LinkedIn, GitHub, Linear, Miro, Perplexity, Threads and more.
The examples include new AI-powered search capabilities as well as a breakdown of traditional in-product search functionality and modern UI enhancements like keyboard shortcuts and predictive text. If you’re considering adding search capabilities to your own product or are interested in how this space is evolving, this Deep dive should help bring you up to speed.
Coming up:
Understand the different UX components used in modern search functionality design, including pop-up modals, keyboard shortcuts, AI integrations, advanced filters and more
How in-product search is evolving with new AI offerings from Reddit, Slack, Amazon, Linear, TikTok and others
How Ring’s new AI powered doorbell search helps users get exactly what they want - quickly
How product teams are incorporating new technologies like RAG to make in-product search more powerful than ever - with examples companies like Slack and Intercom
The list of 20+ companies featured in full
How this analysis is structured
For each product’s search functionality that’s featured, we’ve included various aspects of how the search functionality works.
The analysis includes the following:
Company - the company featured. This deep dive includes 20+ leading tech companies - including startups like Intercom as well as larger companies like Amazon, Threads and others.
Search feature - the specific search feature highlighted. This includes a variety of different types of in-product search functionality including global search (which allows users to search anywhere within a product) to more unique features like TikTok’s sound search, Shopify’s semantic search or Google Maps’ search in store.
UX components - specific types of UX components used in the search feature including pop up modals, keyboard shortcuts, AI integration, advanced filters and others. More on this below.
How it works - more detailed information about how the search feature works to help provide more context.
UI example - an example of the search feature in action along with sample UI and videos of the search functionality. All UI examples can be downloaded and saved for future reference.
Link to more information - more information about how each search feature works.
The different UX component categories explained
As part of this analysis, we’ve looked at various different types of UX components. There are 8 different UX component categories in the analysis and this includes:
Pop-up modals - some products use a focused overlay to display search results, advanced search options, or filters without navigating away from the current page. Notion and Intercom do this in their core search functionality, for example.
Keyboard shortcuts - an increasingly popular option which provides quick ways to initiate a search or filter results. Companies like Linear, Miro, GitHub and others all offer keyboard shortcuts for users to quickly initiate search.
AI integration - enhances search by using natural language processing, suggesting related terms, personalizing results, or predicting user intent based on behavior. Ring’s new IQ search lets users find the exact clip they want just by describing it, for example.
Quick filters - Predefined options like "most recent" or "most relevant" that allow users to narrow search results instantly.
Main navigation - some products will include their search functionality in their main navigation. In these instances, the search feature is categorized accordingly.
Search suggestions dynamically display possible queries or results as users type, helping them refine or complete their search faster.
Advanced filters give users detailed options like date ranges, content types, or tags to refine search results further.
Predictive text - Auto-completes users’ queries based on input, reducing typing effort and guiding them to likely search terms. Perplexity’s core product does this when you’re writing a query, for example. Others do this, too.
A deeper look at examples from companies featured
Now that we’ve set the context a little, let’s take a closer look at some of the ways leading tech companies are designing search UX in their products.
In this first section, we’ll explore how companies are innovating their search UX beyond traditional search capabilities by offering new ways to search, powered by LLMs, machine learning and other AI technologies.