Nirav Tolia on Growing Nextdoor and the Path to Monetization
Nirav Tolia on Growing Nextdoor and the Path to MonetizationInside are 5 insights from former CEO and co-founder of Nextdoor, Nirav ToiliaHey, Nick here! In this newsletter, I curate insights and timeless principles on how to build great products. You’ll improve your product skills with every issue. Here’s a video for you today… Nirav Tolia on Growing Nextdoor and the Path to Monetization Nirav Tolia started his career as one of the first 70 employees at Yahoo and more notably is a co-founder and former CEO of Nextdoor. He had several other startups with varying success that helped develop Nextdoor. Here are 5 insights from his conversation in the Blitzscaling series. 1. Confusing Coolness and Market Size Nirav discussed how one of the biggest mistakes is getting enamored with the “coolness” of an idea. Great ideas occur every day, but that doesn’t make them sustainable businesses. A problem founders run into is overselling their company because of their grand plan. They’ll raise money at a valuation of $100M thinking they are participating in a multi-billion dollar market when the market size is actually $100M. This disconnect is how poor decisions are made by trying to fit the company into something it’s not. They are playing catch up to their overstated valuation. 2. Learning from Down Cycles Nirav has been around long enough to ride the internet boom of the early 2000’s and see it all come down. He was at Yahoo, which was the most valuable company in the world for a time. He says there is a right way to run a company and it doesn’t change much between an up or down cycle. The best companies take their learnings of operating in a bust and then use them during the next boom. 3. Quality Not Growth There are an estimated 165,000 neighborhoods in America. In Nextdoor’s first year, they signed up 176 neighborhoods to their platform. At that signup rate, it would take them over 900 years to get America signed up. This methodical start was intentional. They were focused on quality, not growth. They wanted to make sure they were building communities with an identity. Contrary to popular belief, they created friction in the signup process. In order for a neighborhood to be created, there needed to be at least 10 individuals to sign up in the first 21 days of a neighborhood being registered. If 10 people didn’t sign up, then the neighborhood was put on a waitlist. Employees from Nextdoor would also manually verify addresses. They understood what it took for a valuable neighborhood to be brought online. There needed to be a strong sense of community from the start or it wouldn’t work. This is why they made sure there was commitment from the users who were signing up. Because Nextdoor set a high bar for quality at the start, they didn’t need to scale the experience. Their challenge was to scale the number of neighborhoods when the time was right. 4. Framework for Managing Nextdoor Nirav created 5 buckets on where to spend his time. They are Growth, Engagement, Monetization, Infrastructure, and People. Depending on where Nextdoor was in its lifecycle, time allocation would differ between the buckets. At first, it was all about engagement. The goal was to get very active neighborhoods started to prove there was a business to be built. After their thesis was proven, then it was time to turn to growth. How would they get more neighborhoods signed up? Once the growth happened, their infrastructure wasn’t in a place to support the hypergrowth, so they needed to catch up. Now that they are stable, they can turn their attention to how to monetize the platform they built. 5. Thinking about Monetization Nextdoor is a free service. Their goal was to create active communities and then they would turn to how to monetize. They thought about monetization in two different ways: demand fulfillment and demand generation. Demand fulfillment is when you search for “best TV” and Google provides ads that are purchased by companies selling TV’s. Demand generation is scrolling on Facebook and seeing ads provided to you for TV’s even though you aren’t actively searching for one. A large percent of the conversation on Nextdoor is around local recommendations for doctors, contractors, etc. This would be demand fulfillment. Nextdoor can help a person find a doctor based on what others are saying. An example of demand generation would be for real estate agents trying to let a homeowner know how much their house is worth so the homeowner would sell. Check out the full interview with Nirav here! End Note Thank you for reading! For bite-sized product tips in your Twitter feed, follow @ProductPersonHQ. Have a great day, Nick Enjoyed this? Please share it with a friend or two. |
Older messages
The Rise and Fall of FTX – Part Three
Monday, December 26, 2022
FTX's presidential tokens, FTX.US, Serum, Blockfolio, and Alameda's risky bets in 2020.
The Rise and Fall of FTX - Part Two
Tuesday, December 13, 2022
Building a crypto exchange, the early days of FTX, the magic beans token (FTT), and Binance vs FTX.
The Rise and Fall of FTX - Part 1
Thursday, December 1, 2022
A history of FTX, from inception to disgrace.
The Lean Startup
Thursday, August 25, 2022
Inside are 5 key insights from the New York Times Best-Selling Book, The Lean Startup.
7 Habits of Highly Effective Product Managers
Thursday, August 4, 2022
Hey, Nick here! In this newsletter, I curate insights and timeless principles on how to build great products. You'll improve your product skills with every issue. Here's an article for you
You Might Also Like
Daily Coding Problem: Problem #1647 [Medium]
Tuesday, December 24, 2024
Daily Coding Problem Good morning! Here's your coding interview problem for today. This problem was asked by Square. In front of you is a row of N coins, with values v 1 , v 1 , ..., v n . You are
Sentiment Analysis, Topological Sort, Web Security, and More
Tuesday, December 24, 2024
Exploring Modern Sentiment Analysis Approaches in Python #661 – DECEMBER 24, 2024 VIEW IN BROWSER The PyCoder's Weekly Logo Exploring Modern Sentiment Analysis Approaches in Python What are the
🤫 Do Not Disturb Mode Is My Secret to Sanity — 8 Gadgets I Want To See Nintendo Make
Tuesday, December 24, 2024
Also: The Best Christmas Movies to Watch on Netflix, and More! How-To Geek Logo December 24, 2024 Did You Know Their association with the Christmas season might make you think poinsettias hail from a
😱 AzureEdge.net DNS Retiring Jan. 2025, 🚀 Microsoft Phi-4 AI Outperforms, 🔒 Microsoft Secure Future Initiative
Tuesday, December 24, 2024
Blog | Advertise | View Online Your trusted source for Cloud, AI and DevOps guidance with industry expert Chris Pietschmann! Phi-4: Microsoft's New Small Language Model Outperforms Giants in AI
Mapped | The Top Health Insurance Companies by State 🏥
Tuesday, December 24, 2024
In 13 US states, a single company dominates the health insurance market, holding at least half of the total market share. View Online | Subscribe | Download Our App Presented by: Global X ETFs Power
The Stanford Grad Who Forgot How To Think
Tuesday, December 24, 2024
Top Tech Content sent at Noon! Boost Your Article on HackerNoon for $159.99! Read this email in your browser How are you, @newsletterest1? 🪐 What's happening in tech today, December 24, 2024? The
The next big HDMI leap is coming
Tuesday, December 24, 2024
Sora side hustles; Casio's tiny watch comes to the US -- ZDNET ZDNET Tech Today - US December 24, 2024 Ecovacs Deebot T30S Combo robot vacuum and mop The next big HDMI leap is coming next month -
⚙️ Robo-suits
Tuesday, December 24, 2024
Plus: The data center energy surge
Apache Tomcat Vulnerability CVE-2024-56337 Exposes Servers to RCE Attacks
Tuesday, December 24, 2024
THN Daily Updates Newsletter cover The Data Science Handbook, 2nd Edition ($60.00 Value) FREE for a Limited Time Practical, accessible guide to becoming a data scientist, updated to include the latest
Edge 459: Quantization Plus Distillation
Tuesday, December 24, 2024
Some insights into quantized distillation ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏