Apartment Hunting Thesis
Investment thesis
The rental market is ready for innovation because the consumer has not been prioritized in terms of user experience. Zillow won by consolidating listings and building a marketplace that primarily monetizes the supply side. That made search more efficient, but it did not meaningfully improve the renter’s apartment hunting experience.
Renting is one of the largest financial decisions most people make in their twenties, yet renters are still left to navigate an expensive, stressful, and high-stakes process largely on their own. The opportunity is to build for the consumer: helping renters understand apartments, neighborhoods, roommates, tradeoffs, and lifestyle fit in a way that turns short-term search behavior into a long-term relationship.
The two hardest problems are that renters are fickle and rental search is naturally short-lived. The first can be solved with a dramatically better product. The second is the bigger opportunity: creating a product that stays useful before, during, and after the move.
Problem
In the last four years, I’ve moved five times across San Francisco and New York. Every move reminded me how broken renting still is. Photos are misleading in both directions, timing is chaotic, roommates complicate coordination, and in competitive markets like SF or NYC, broker fees and bidding wars create even more pressure.
Finding an apartment is one of the largest financial decisions most people make in their twenties, yet the experience is dramatically undersupported relative to its importance.
Current status quo
Renters do not have an agent to advocate for them when renting, unlike when buying a home. Despite rent being the largest percent of your income (up to 40%), the economics do not make sense to pay for a human to help you find an apartment. The money saved, or access given, is worth a few hundred to a thousand dollars per roommate. However, modern agents require a fee that is at least greater than $6k for their work.
The current product experience for renters is subpar. The modern companies have taken the experience for buying a house (where the average age is 35+) and applied it to the renting experience. Renters are seeking unique experiences for their home, wanting to know what’s around it, and instead are given scores on how well the local elementary school is rated.
Most real estate companies approach renting as a listing fragmentation problem. Zillow’s core thesis has largely been that the market is fragmented and that consolidating listings creates value for renters. While that is true, it’s actually the bare minimum that they do since the majority of their rental revenue comes from the supply side.
Opportunity
Renters are trying to answer questions that listings don’t solve:
- What is this apartment actually worth relative to alternatives?
- Is this neighborhood actually a fit for how I spend my time?
- How do I coordinate decisions across roommates?
- What’s unique about this apartment?
Whether it’s stained glass windows, a bodega around the corner open 24 hours with great reviews, or knowing the subway near your apartment is infested with rats, there is an opportunity to show more context around an apartment. Matches can be customized to a renter’s interests, and the experience can be built around the consumer.
Why now
AI lowers the cost of both collecting data about a listing and guiding renters through the decision-making process. An AI agent can offer services that an agent would do for a fraction of the price, even going beyond the capabilities of a real estate agent.
People are upset about how the housing market and landscape works in the country. Recently there was a pro-consumer ruling that no longer put the seller’s agent fee on the buyer. Similarly, New York released a law that banned rent increases and broker fees.
Exploration
In the past, the three main runner-ups in competition to Zillow were RadPad, StreetEasy, and Padmapper. RadPad was a mobile-first experience, StreetEasy used the context of the subway system and a source of truth of the price of an apartment, and Padmapper revamped a search experience that was much better than Craigslist. StreetEasy was able to outdo the competition and eventually focused on the supply side before getting bought by Zillow. Padmapper and RadPad were unable to convert short-term users.
My friend and I created ApartmentBuddySF to explore this idea. ApartmentBuddySF aggregates listings from Zillow, Craigslist, and AppFolio into one place, and uses AI to help people find apartments. Through creating this product, we’ve validated that the product solves the need for the user and is sticky in the short term. However, once users find an apartment they do not retain. To turn ApartmentBuddySF into a billion-dollar business, we’d need to retain users over the course of a year.