Joybird is taking the furniture industry by storm through a combination of built to order furniture and dedication to the complete customer experience. Many products are custom built with different fabric options available to ensure everyone finds their perfect piece. Having good insights into their users’ behavior and patterns is critical for delivering superior products.
At Joybird, product analytics used to be managed in a large spreadsheet with different tabs for property groups.
“This started with my own onboarding experience. When I was new to the team, it was overwhelming to understand what events and properties were firing or accurate or complete. I needed to get control over the spreadsheet monster.” - Brett Trani, Director of Data and Analytics
There was a lot of back and forth to understand what each event or property meant, how it was instrumented, and whether it was working. After joining the team, Brett quickly led the charge in an overhaul of their current product analytics.
At Joybird, Avo sits between a React web app and their downstream tools. Data flows downstream to Snowflake, marketing tools and product analytics platforms.
Having left their spreadsheet days behind them, analytics tracking at Joybird is much simpler. It starts with a new feature they’d like to implement and how they should track it. The product and data teams work very collaboratively. “We use branches almost religiously in Avo to implement and validate,” Christoph Anderson, Senior Technical Product Manager, reports. From there events are put into production and they utilize the Avo webhook to get updates in Slack. This has also streamlined communication with the engineering team and allowed Joybird to get new events into production faster.
Besides a better workflow, Joybird highlights a few features that have made a big impact. “Something that really pulled us to Avo was the ability to have nested properties. The UI is very clean, as well.”
Using Avo’s debugger, there’s also much more self-serve capabilities in their analytics. “Anyone can look at the debugger and know what events are present, ” says Brett. “It’s constantly QAing events, so we know there’s a very high bar for data quality.”
Since Joybird’s analytics overhaul, there have been no new tickets for misfiring or wrong event data. That’s a milestone we can all get behind!