Inside GrowthHackers.com’s Implementation of Algolia

We interviewed Dylan La Com, Growth Product Manager at Qualaroo & GrowthHackers.com, about their Algolia implementation experience.

What role did search play at GrowthHackers before the Algolia implementation?

When we launched our community site GrowthHackers.com in October 2013, search was admittedly an afterthought for us. GrowthHackers is a social-voting site where marketers, founders, and product-people can share and discuss growth-related content. At launch, it was unclear what role search would have on the site. GrowthHackers is built on WordPress, and with that comes WordPress’ standard search functionality. What WP search does is append an additional keyword or phrase parameter to its typical post query and load a new page with the results. WP search only indexed the outbound URLs of the articles our members submitted, and this made finding specific content difficult.

Why did you want to give search an update on GrowthHackers?

We started hearing about our lack of a solid search feature from some of our more active users. One of our members even put together a slide presentation to prove just how useless our search was [check it out here]. At the same time, GrowthHackers was becoming more than just a way to stay up-to-date on the best growth articles, it was becoming the place to get answers: an encyclopedia for growth-related information. Search volume at this time was peaking in the mid-hundreds per week. We needed a search feature that could support this evolving use-case.

Why did you choose Algolia?

We looked at several search solutions before trying Algolia, including Swiftype, WP Search (plugin), and Srch2. All are great solutions, but ultimately, we went with Algolia because they had the right mix of features: Their integration was simple, the documentation was thorough, and there were plenty of starter templates. I knew it was a good sign when, while looking their GitHub repository, I found they had a demo site built with search that worked very similar to how we hoped ours would work, complete with real-time results, typo-tolerance, and filters. The Algolia team was incredibly helpful getting us set up and was there each step of the way through the integration process, providing resources and best practices for creating a truly top-notch search experience.

Tell me a little about how the new search works.

Our primary use of Algolia is to store and index user submitted content, and provide real-time search in our growing database of growth-related articles, questions, videos and slides. The majority of what we index is article titles and URLs–strings which are generally small. Visitors to our site often come with specific growth-related questions and use our search to find answers quickly. For example, someone interested in learning best practices for running Twitter ads could type in “Twitter ad” and within milliseconds see dozens of articles and discussions related to maximizing ROI for Twitter ads. Using Algolia’s admin dashboard, we’re able to set ranking priorities based on the number of votes and comments of each article, and make sure the top results are the most relevant. So, the visitor who searches “Twitter ad” is shown articles with the highest mix of votes and comments. Algolia took the search ranking process and wrapped it in a clean and simple interface that allows anyone, regardless of their experience with search, to easily adjust and manipulate.

One of the challenges we faced during the integration process was understanding how to keep our main database synced and up to date with our Algolia index. User submitted content on GrowthHackers changes often as users interact with the content. Each post once submitted may receive upvotes and comments from members in the community. Each post also has a wiki-style summary field that can be edited by community members. Lastly, posts can have several states, including published, pending and trashed. In order to ensure our content on Algolia mirrored the content in our database, we set up a job queue and a cron process to periodically push updates to our Algolia index. This has been working quite well for us.

How has the new search impacted engagement?

We released the new search mid-February, and since the release we’ve seen search volume increase 4-5X. Of course there are several factors at play here, including increased traffic volume and better search bar placement, but it is clear that Algolia’s search features have contributed to an impressive increase in search engagement. On average, visitors who utilize search view 2-3X more pages per session and spend 5-6X longer on the site than those who don’t search. Algolia’s analytics dashboard provides us with an incredible glimpse of visitor intent on our site by showing us the queries visitors are searching for, and trend lines to show popularity over time. With this data, we’re able to better understand how our visitors want to use our site, and make better decisions about how to organize the content.

Moving forward, we’re hoping to implement Algolia’s search filters to provide even better ways to access content on our site. We’re excited to have such a powerful tool in our stack and hope to experiment with new ways to provide search functionality throughout GrowthHackers.