Salary Fairy crowdsources salary predictions and had 9,000 users after three months, growing 10% weekly. Most users were curious, so the partners advised focusing on helping employees assess their market value and secure fair offers before expanding to an employer marketplace. They also urged the founders to track whether users acted on the information, returned, and recommended it.
Office Hours at Startup School NY 2014
Speaker
Y Combinator partners Sam Altman and Gary Tan hold onstage office hours at Startup School NY, advising Salary Fairy, PareUp, and a couples’ expense-sharing startup whose name is not stated.
PareUp aimed to sell food that shops might otherwise discard, at an average discount of about 50%. Its email test had around 350 subscribers, six or seven vendors, and 48% open rates; the founders later said interest had grown to about 2,500 people. The partners recommended getting a mobile app out quickly and starting in concentrated areas with proven items such as sandwiches and croissants.
The third startup syncs card transactions so couples can tap the purchases they want to share and keep a running tab. Its founder said the team had narrowed its product from couples, roommates, and travelers to couples after beta use showed that couples were the main users. The partners supported the focus and pressed the team to explain what made the product distinct and how it could acquire users.
The expense-sharing startup had about 40 beta testers, with around 25 using the product every few days. The partners called that activity promising, but advised the team to keep talking with users and build toward its first hundred or thousand people who truly valued the product. An app-store launch could smooth distribution, but the partners cautioned that it would not automatically bring traction.
Takeaways
- Find the behavior that shows users rely on your product, not just try it once.
- Focus on a narrow group and use case before expanding to adjacent markets.
- For local marketplaces, concentrate supply and demand in specific areas.
- Use beta activity and direct user conversations to decide what to improve.
- Plan how users will discover and invite others; growth rarely happens by itself.
Mentioned in this talk
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What was claimed 10
- featureSalary Fairy: Crowdsources salary predictions to help users learn their value in the job market.
“We help our users learn their value in the job market by crowdsourcing salary predictions.”
YouTube Unverified1 source· Talk
- metricSalary Fairy: 9,000 users
“We currently have 9,000 users.”
YouTube Unverified1 source· Talk
- metricSalary Fairy: 10% weekly growth rate
“Our weekly growth rate is 10%.”
YouTube Unverified1 source· Talk
- featureSalary Fairy: Planned employer platform for viewing professional profiles with predicted salaries and making offers.
“We're creating the other part of the platform, where employers can see professional profiles along with predicted salaries and make salary offers.”
YouTube Unverified1 source· Talk
- metricSalary Fairy: 30% return rate; time period unspecified
“We have a 30% return rate.”
YouTube Unverified1 source· Talk
- featurePareUp: Marketplace where vendors sell excess food inventory at a discount to users.
“What we're actually building is a marketplace that allows vendors to sell their excess inventory at a discount to users who are willing to buy it.”
YouTube Unverified1 source· Talk
- metricPareUp: Email proof of concept had about 350 subscribers, six or seven vendors, and approximately 48% open rates.
“We had a subscriber base of maybe 350 people and worked with six or seven vendors. It turned out they did: our emails had open rates of about 48%.”
YouTube Unverified1 source· Talk
- featurePareUp: Planned mobile app with alerts and location-based searches for live food listings.
“The mobile app will hopefully let us take that further with alerts and location-based searches.”
YouTube Unverified1 source· Talk








