Neighborhood Favorites is a way for neighbors to discover the best local businesses in their communities. It's an annual program that gets people to share recommendations on their local favorites. With enough votes, each neighborhood produces its own unique list of best businesses and the winners are celebrated both online and offline. Nextdoor recommendations are especially powerful because they all come from real, verified neighbors. I designed the survey itself which is what generated over 32 million recommendations over 3 years — this more than quintupled the total number of recommendations on the entire platform.
Recommendations forms one of the pillars that support Nextdoor's value proposition as a hyperlocal network. It powers the business section, enhances search and serves as the most important element of Nextdoor's business acquisition strategy. Increasing the number of recommendations creates bandwidth to build more meaningful products and directly contributes to engagement. Whether it's figuring out the best preschool in the area or finding a trusted handyman, your neighbors are the best people to answer those questions.
Members can quickly recommend dozens of businesses without leaving where they were.
Surveys are pretty simple but this one is not so simple. The product spec asks neighbors to share not just a few recommendations, but literally as many as they can provide. They survey would be very long and can include as many as 30 categories. Of course people would drop off or quit at the first sight of this task, so my challenge was to design an experience that was dead simple, performant but most of all delightful. Here's how I made that happen:
The user only ever sees one category to vote for at a time, is asked one question and provides one answer. Users can swipe to skip irrelevant categories or to review past answers. It's a simple way to break up a 30 step survey and requires no additional navigation.
Each category is designed to be immediately recognizable. Luckily there was already a color and icon scheme used to distinguish business categories. I expressed gratitude at how scalable it was and sampled this visual identity in the survey. It felt consistent, on brand and added depth to the layout.
I aligned the survey to existing color and icon systems to make it feel familiar and consistent.
Voting on a business immediately moves advances the card to the next category so it's a one-touch voting experience. The team really wanted to celebrate each new recommendation so I worked on a motion study to explore an animation that was fun but didn't linger too long.
Neighborhood Favorites was extremely successful and blew our expectations out of the water. Before the launch there was 5.5 million recommendations in total on Nextdoor. Neighborhood Favorites tripled this number in its first year. By 2019 it has directly added 32.2 million recommendations to the platform — a 5.6x increase. This resulted in enriching every corner of the product with local insights, dramatically improving offline awarness and most importantly fuelling our business acquision strategy.
• Directly contributed 32 million new recommendations
• ~9% of MAU participated with an average of 12 recs per member
While this was probably the most successful project I've worked on at Nextdoor, in a way it was also the most disappointing for me. There was some major engineering roadblocks that lead us to changing the scope from building in native iOS and Android to using a very janky embedded webview that was superimposed on a native newsfeed. Yes it worked, and yes we got results but it still sucked because it could have been so much better. There was also a change made by the PM at the last minute to ask for a comment after each vote. This changed the rapid fire interaction model and if this was part of the original brief, I would have produced a different design. I wasn't able to stop these changes because I worked on this as an intern and only later returned to find out about the modifications. After this experience I learnt how absolutely critical it was to align with engineering and to be absolutely clear with product management in order to ship a consistent vision.
James Wang © 2019