Hyperlocal social app Nextdoor has launched a big redesign. Known as the ‘new Nextdoor, ‘ this applies across its digital touchpoints, including web and apps. But beyond a facelift and redesigned layout, there are deeper functional refinements meant to align with the company’s broader evolutions.
This includes new sections for local news, real-time alerts, and a new AI-powered feature called “Faves.” The latter is a sort of discovery engine that’s meant to automate the intelligent and preference-aligned discovery of local businesses. And all of the above is dressed up in a more modern look & feel.
The company has also designed the experience to include more hyperlocal content and fewer ads. To help achieve this, the company has partnered with 3,500 local news publishers across the U.S., U.K., and Canada. Highlights include the San Francisco Standard, The London Standard, and The Toronto Star.
One big reason for this update is that Nextdoor was starting to become very spammy. Its pages were cluttered with ad density, and – anecdotally speaking – had a spammy vibe in the types of products being promoted (use your imagination). The UX and vertical feed were also starting to look very dated.
Moreover, Nexdoor started to become associated with user-generated content that was often offensive or contentious. That includes misinformation and even some racism. Besides not wanting to host such content for ethical and altruistic reasons, this content started to cause user engagement to decline.
Balanced Diet
Bringing in professional news content is meant to offset the dominance of all that user-generated content. Even when the UGC is good – peer-to-peer neighbor interaction has always been a staple of Nextdoor – it’s about a balanced diet. It wants a more even mix of news and social commentary.
Notably, this represents the first time in its history that Nextdoor is bringing in third-party publishers into its platform. And it’s worth noting that no money is changing hands, and Nextdoor isn’t hosting the content. It’s simply curating and displaying headlines that link to the source, a la RSS feeds.
Looking forward, news will be a model for other types of third-party publisher content that Nextdoor ads to the mix. The plan is to follow that up with content from schools, local organizations, and even SMBs. The way that this content is integrated will probably depend on what it learns from news integration.
Speaking third-party content, that brings us to the new alerts teased above. This will include real-time updates for traffic, weather, storms, wildfires, and power outages. This content is hoped to inspire user interaction and discussion – Nextdoor’s forte. Initial partners include Samdesk and Weather.com.
For these alerts, Nextdoor will lean into one of its key differentiators: hyperlocal context. Because all of its users are tied to a zip code or sub-zip (neighborhoods), it can segment alerts automatically to locations. For example, it will only send power-outage alerts to affected neighborhoods.
Lastly, the Faves feature is Nextdoor’s dive into AI. But unlike many knee-jerk AI integrations these days, it actually makes sense. It will be a typical chatbot interface to ask local questions (think: restaurant recommendations). But where it differentiates is 15 years of neighborhood-level chatter around SMBs.
That last part gives Nextdoor prime positioning in the world of AI, as it’s all about the data. All of the sentiment data in its neighborhood social and UGC feeds is unique to Nextdoor and isn’t indexed by Google. So that could be a gold mine for LLM training… if it can exclude the racist stuff of course.
The Hyperlocal Graveyard
Stepping back, this is a long overdue facelift for Nextdoor, which has been around for 15 years. In that time, it has defied common chicken & egg challenges that afflict local marketplaces apps, and become a widely used household-name app. It’s up there with the likes of Yelp in terms of name recognition.
This challenge shouldn’t be underestimated, as Nextdoor has defied the odds and avoided the well-populated hyperlocal graveyard. That list includes historical flameouts like Patch, Backfense, Judy’s Book, and others built around monetizing hyperlocal news and neighbor interaction. It ain’t easy.
One reason why this is so challenging is that you not only have to achieve typical milestones for marketplace businesses – reach network effect, supply/demand equilibrium, etc. – but you have to do it thousands of times. In other words, you have to replicate the model with even quality in every zip code.
These are the biggest reasons that Patch failed. It had come the closest to Hyperlocal nirvana, prior to Nextdoor’s ascent. It also had the benefit of big-money backing from owner AOL. But even with that advantage, it was unable to make the model work and then rinse/repeat in every zip code in America.
Nextdoor has somehow done that with fewer resources. But its declines have been noticeable in the past few years due to questionable content. We’ll see if the new approach is effective in cleaning that up and striking the right balance of high-quality fare and the genuine, sometimes raw, realities of local.
Header image credit: Avi Waxman on Unsplash
