Drupal developers: raise your hand if you’ve ever been in this situation. You’re ready to deploy your app. You’ve developed a beautiful site, leveraging Drupal to its max. You’ve plugged in site search through the Drupal “Apache Solr Search” plugin.
But there’s trouble ahead. Just before you deploy you suddenly realize your search isn’t all it could be. The default Solr settings don’t quite return results you expect. Results aren’t relevant. Maybe your site is a news site and older news items are popping up before newer/more popular articles in search results? Maybe you’ve implemented a name search, and matches on non-names (the occupation Smith) crop up much higher than actual name matches? Whatever it is your users will certainly notice — and leave in droves.
It turns out search is a huge part of our lives, and often a massively undervalued component of our sites. Users raised in the age of google expect highly relevant site search, or they’ll leave. Do you want take the risky route of ignoring search results quality, silently driving away frustrated users? Or do you want to be in the same class as Drupal sites like Duke Health — a recent Drupal Client of ours now with extremely smart & regularly maintained search?
At OpenSource Connections, we have a long history of helping Drupal clients take their search relevancy from dud to money making. Many clients come to us with an extensive set of specific problems–failures to capture specific use cases. They want our help to try and figure out how to capture these use cases and thus improve relevancy.
The problem is: how do we capture all of their use cases — all the requirements we hope to get out of search–multiple, overlapping, even conflicting requirements like incorporating variables like product profitability, document recency, and popularity? Most search developers fail at this — able to perform spot fixes on one or two relevancy problems — unable to get a holistic solution in place that captures all requirements.
We have a product, Quepid, that can transform your search experience. Quepid captures search feedback & requirements in one place — in the form of tests. This lets search developers provably make progress over all your important use cases. We call this test driven search relevancy and its the core of our search relevancy practice. Let it be at the core of yours! You wouldn’t write code that you can’t test, why would you try the same with your search?
With Quepid’s Test-Driven Relevancy approach search developers can stop and measure at every step. Did the tweak to improve the effectiveness of name search negatively impact our ability to return other search results? How good are we at all the requirements we’re trying to meet? Are we making forward progress, or did the latest tweak break important features?
Armed with this information search developers can quickly get at the root of your relevancy problems. Quepid takes snapshots of your search at important milestones, allowing it to diff what’s currently being worked on vs what’s deployed. This lets search developers check in on your search, gathering intelligence and performing health checks on how your search is doing.
When this product is coupled with our search services, it gives us a competitive edge other search consultancies. With Quepid, we have an ability to check in on your search, efficiently find troublesome patterns, and resolve issues quickly — while provably testing against preexisting use cases. Most importantly you’ll be able to say very directly whether our search services have been helpful or not — something not easy to get from other search companies.
So, are you stuck with poor search relevancy? Feel like you’re going in circles trying to make your search relevant?
We hope you’ll find us at DrupalCon to discuss your search needs and how Quepid products & services can help you make search the star of your Drupal app! You’ve already built something amazing with Drupal, don’t fail your users by ignoring search relevancy!