Post by Andy Edmonds of Surf*Mind*Musings
SearchMe is a seriously VC-backed implementation of Apple’s CoverFlow for search result pages — horizontal scrolling with a centered focus and perspective skew visual effect for thumbnail page previews. Looking to its heritage in hypertext work, it’s most akin to the WebBook from Xerox PARC. Since my original writeup the site has come out of invite-only beta and made a number of improvements.


The advantage of thumbnails for recollection of already visited sites has long been proven (Greenberg & Cockburn, 1999). But for new sites, the full thumbnail is not necessarily the best indicator. For highly designed sites, or perhaps sites that are favorite destinations, recognizability is strong, but typically the company logo or even textual excerpts would be better proxies.
The visual preview has value as a “storefront” — is the site in a good neighborhood? e.g. are the proprieters competent in design and technical execution? How big is the building? What schema does it fit?
But for this feature, Ask.com’s on demand thumbnail and other smaller thumbnail view UIs do a better job of lowering expectation violations, *after* the semantic match has been validated with human natural language processing of the result summary. A thoughtful post from eliottng explores this issue in the context of the separate tasks that search enables.
The remarkable thing about SearchMe is that, when the preview pane is maximized, the page rendering is largely readable, at least for headlines. In practice, this turns out to be more useful than previous thumbnail implementations.
Clustering and Query Refinement
SearchMe also offers a query filtering feature for choosing between clusters of content triggered by a keyword, named “Category Suggest”. These are an interesting set of filters, akin to site genres in this case. The Category Filtering Bar:
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While “recognition not recall” is one of the most profound of the commandments of usability, many implementations of query suggestion, without the time savings of auto-complete, cost more effort than their worth. This isn’t the case given polysemy, words with multiple interpretations. Disambiguation, especially for lower frequency senses, is a great use case for query suggestions or filtering operations. The technologists in search I’ve known have always been kind of embarassed that technical topics overwhelm the common IRL interpretations of words like java, but the problem is far more widespread.
“Category Suggest” is a nice spin on the historical query (re)forumulation UIs, notably by using something other than the standard log-mined query refinements. Broadly speaking, the query formulation part of the search task model has basically seen two major areas of experimentation: auto-complete and refinement suggestions / result clustering.
There has been more work in the academic industry and search construction UIs, for things like nested booleans. I don’t think this level of upfront user effort is the right approach for everyday search tasks. People are use to executing query refinement chains, and done right, suggestions of advanced query modifiers (like filters, as in category suggest, not simple keyword alteration) could really approach the fluency and generativity of a natural language UI without the gratuitous anthromorphism of conversational UIs.
Not every query needs this type of offering however. And it varies by user, and specifically user experience in the topic domain. Micah Alpern recounted some nice work on calibrating hesitation detection in query formulation for recent query assistance features at Yahoo in our SXSW panel for rapid detection of when to spend user attention on evaluating suggestions.
Prediction: Search UI Innovation Will Not Remain Slow
I’ve written a lot about how pagination affects the user behavior in search, and done much more proprietary investigations thereof. The process of result evaluation is super optimized by the user, though less so than commonly understood given the 30% navigational query percentage.
User engagement with SERPs will increase as innovations like the awesome bar in Firefox 3 take advantage of existing local persistence of routine navigation. A search engine’s ability to make more complex search problems fun and productive will become more critical.
Infinite scroll experiments (live search, humanized reader, etc) are one of the more gutsy innovations in search UI, but are really a move forward in pagination UIs that have some non-trivial challenges still to solve — notably how to suppport patterns other than simple feed forward.
Idea: Making SearchMe Better
Beyond the simple glitz of emulating the popular iphone, and other variants, coverflow UI, the core promise of the interaction style is more effective search that’s not simple read once, top down. Traditional search results pages (SERPs) make entertaining candidate choices and evaluating the relative value across candidates, prior to click, a very challenging prospect. Memorability for individual results is low, especially for novel topics, and can be improved with visual markers. This can help in both initial result selection and subsequent revisits to a result set for deeper exploration. More consistent deliberation and fluency in the result summary evaluation processes could really help users be more productive.
I’d add dwell time implicit feedback to the SearchMe UI, as well as keyboard shortcuts to nominate and demote result previews. This could directly impact the visual rendering of the results, reducing the real estate footprint of rejected alternatives and increasing the saliency of nominees. Visit status is also an obvious must have. There is a lot more potential for adding session state to search activities, but interface level state models for the SERP evaluation process is a good path of exploration.
Now, I really wonder what they’ve got under the hood! Index size seems pretty good in casual use, both phrasal recognition and the importance of phrasal integrity is rather weak. Given how critical this is in the first vanity query (e.g. their name) any geek tries on a new engine, this is not a work item to de-prioritize. Innovation and uniqueness can gather buzz, but usefulness is what makes a product successful.
















