<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ux on Harlan D. Harris</title><link>https://harlanh.tech/tags/ux/</link><description>Recent content in Ux on Harlan D. Harris</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>harlan.harris@gmail.com (Harlan Harris)</managingEditor><webMaster>harlan.harris@gmail.com (Harlan Harris)</webMaster><lastBuildDate>Mon, 20 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://harlanh.tech/tags/ux/index.xml" rel="self" type="application/rss+xml"/><item><title>Search Describes Solutions -- But What About Problems?</title><link>https://harlanh.tech/2026/07/search-describes-solutions-what-about-problems/</link><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><author>harlan.harris@gmail.com (Harlan Harris)</author><guid>https://harlanh.tech/2026/07/search-describes-solutions-what-about-problems/</guid><description>
&lt;p&gt;In a &lt;a href="https://harlanh.tech/2026/02/ize-revisiting-hierarchical-search-technology-pc-era/"&gt;previous post&lt;/a&gt; I said
that Search User Interfaces (UI) have two jobs -- helping people find things and educating them about the catalog's structure. (I'll use &amp;quot;catalog&amp;quot; here under the assumption that I'm
describing an e-commerce search system, but much of this post is relevant for
other search domains.)
The search results, facets, and other elements describe the catalog: the
solutions and products available.&lt;/p&gt;
&lt;p&gt;But there's a third job that's often not addressed and not always well defined: &lt;em&gt;helping users understand their problem&lt;/em&gt;, before they're ready to evaluate solutions.
Standard search UI patterns assume the user is already in the right mental state to evaluate what's on offer.
The design challenge that I want to discuss, then, is to figure out how best to support &lt;em&gt;problem education&lt;/em&gt; in search interfaces.&lt;/p&gt;</description></item><item><title>A Big Win from a Small Search UI Change and a Predictive Model</title><link>https://harlanh.tech/2026/07/big-win-small-search-ui-change-predictive-model/</link><pubDate>Thu, 09 Jul 2026 00:00:00 +0000</pubDate><author>harlan.harris@gmail.com (Harlan Harris)</author><guid>https://harlanh.tech/2026/07/big-win-small-search-ui-change-predictive-model/</guid><description>
&lt;p&gt;One of my biggest commercial wins was a seemingly small UI tweak
that led to a roughly 1.5% marketplace revenue bump.
&lt;a href="https://teacherspayteachers.com"&gt;Teachers Pay Teachers&lt;/a&gt; (TPT,
think &amp;quot;Etsy for Teachers&amp;quot; -- educational resources created by
and sold to other educators) was a
mature marketplace, where revenue wins from search system changes
were typically under 0.5%.
How we got this win is, I think, instructive, reinforcing the value
of a &lt;a href="https://harlanh.tech/2026/04/you-dont-need-a-search-engineer-you-need-a-search-scientist/"&gt;search scientist&lt;/a&gt;,
and of having a holistic view of search UI/UX and algorithms.&lt;/p&gt;</description></item><item><title>Design Decisions for a New Search Results Page</title><link>https://harlanh.tech/2026/05/design-decisions-new-search-results-page/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><author>harlan.harris@gmail.com (Harlan Harris)</author><guid>https://harlanh.tech/2026/05/design-decisions-new-search-results-page/</guid><description>
&lt;p&gt;One of my specialties as a freelance consultant is discovery systems for e-commerce
-- web pages and backend systems for helping users search for and find what they want or need. For
the last year and a half,
I've been working as a consultant for &lt;a href="https://designshop.com"&gt;DesignShop&lt;/a&gt;, a
company that sells materials samples for home renovations. Want to find
a countertop, cabinet, paint, and tile combo for your kitchen reno that looks great,
with samples shipped overnight? Check 'em out.&lt;/p&gt;</description></item><item><title>Post Query Refinement Suggestions in Search UX, and an Algolia Demo App</title><link>https://harlanh.tech/2026/01/post-query-refinement-suggestions-in-search-ux/</link><pubDate>Fri, 23 Jan 2026 00:00:00 +0000</pubDate><author>harlan.harris@gmail.com (Harlan Harris)</author><guid>https://harlanh.tech/2026/01/post-query-refinement-suggestions-in-search-ux/</guid><description>
&lt;h2 id="what-are-post-query-refinement-suggestions"&gt;What are Post-Query Refinement Suggestions?&lt;/h2&gt;
&lt;p&gt;One of my favorite search UX patterns is post-query refinement suggestions — buttons that appear between the search box and results, adjusting the query in various ways. See, for instance, these suggestions on Etsy, which recommend that I
filter by shipping speed, seller type, cost range, style, etc.&lt;/p&gt;
&lt;figure style="display:inline-block;"&gt;
&lt;img src="etsy_filter_suggestions.png"
width="600"
/&gt;
&lt;figcaption&gt;
&lt;h4&gt;Filter Suggestions on Etsy&lt;/h4&gt;
&lt;/figcaption&gt;
&lt;/figure&gt;
&lt;p&gt;PQRS is a mouthful of an abbreviation, but most of what I've seen as alternatives either
describes the UI element (&amp;quot;refinement pills&amp;quot;) rather than the function,
or is excessively vague (&amp;quot;guided search&amp;quot;). So PQRSs it is, sorry.&lt;/p&gt;</description></item></channel></rss>