2D One-Pager

HousingHero, by Streamline Realty 

“With college students struggling to navigate through housing hunting, we have the opportunity to make housing hunting a stress-free experience for students”

Problem Domain

College students struggle to: 

  1. Understand the apartment-hunting process
  2. Learn how to prepare documentation and payments
  3. Find housing & roommates efficiently

Landlords struggle to:

  1. Trust properties to students due to financial risks and property misuse risks
  2. Reduce time/money spent on screening out unqualified tenant candidate

Example Customer Study & Customer Benefits

Daniel, a freshman at UC Berkeley, is beginning to consider where to live next year. Daniel discovers HousingHero, downloads the app, and sets up his tenant profile. “With no experience renting, I was anxious about finding housing near campus, but HousingHero guided me through the entire housing process, from filtering through housing options, to finding a roommate, to actually securing housing! The whole process took me only two weeks!” By using this app, Daniel reduced time spent on apartment hunting and roommate searching by 40% and 50% respectively.

Amy, a new landlord, is looking to rent out her apartment in Berkeley. Amy discovers that Streamline Realty is providing a new product geared towards students, so she downloads the app, fills in eligibility criteria for tenants (e.g. financials, cosigner), and posts her apartment for lease on the app. “In a week, I received several tour requests and applications from potential tenants, all qualifying my screening criteria! I successfully leased my apartment soon after. I feel secure renting out to students as HousingHero is guaranteeing my rental income! Plus, HousingHero’s recommendation led me to lease to 3 students, boosting my rental income—something not feasible with non-students who are typically reluctant to share a room!” By using this app, Amy raised her rental income by 20% and reduced her time spent on screening by 50%. 

Areas of Uncertainty & Risk

Top three areas of uncertainty, ranked by value of reducing uncertainty:

  1. Would landlords be willing to give us a 3.5% transaction fee per month in exchange for guaranteeing their rental income for shared student housing?
    • This would help us learn more about optimal pricing and would directly impact our strategy and revenue model.
  2. Would students be willing to rely on the services we provide (personal information for more suitable listings) remains untested
    • This knowledge would help us determine the system’s viability and potential user adoption rates.
  3. Would the users see ongoing values of our platform after getting familiar with the rental process? How to ensure the user retention rate?
    • Users might perceive the platform as a means to an end (finding a rental) rather than a continuous resource.  Without ongoing user engagement/ retention campaigns, users might forget about the platform when the need arises again.

Current plan to explore those areas of uncertainty:

  1. Utilize a two-step-landing page to (1) track the number of landlords who showed interest in the guaranteed rental income program (who clicked “next page”) and (2) track the number who then showed disinterest (who did not click “next page”) once the pricing info is introduced. If the majority showed interest in (1) but showed disinterest in (2), consider lowering the pricing.  
  2. Conduct a marketing campaign for our platform’s key features, such as the advanced housing recommendation algorithms. Measure user acquisition and engagement rate, including new sign-ups, visits, and interactions with the features. Analyze the campaigns’ impact on our user acquisition and engagement metrics, and compare the marketing campaign for other features common to other platforms.
  3. Conduct A/B tests on several user retention strategies, like community building and engagement incentives (discounts/rewards). Monitor metrics such as forum interactions, login frequency, and participation, and track whether the users continue renting through our platform.

Prior research & Opportunities

  • Competition: Zillow, Facebook Marketplace, Craiglist, Apartments.com, University Page
  • No competing player focuses on inexperienced college students’ needs
  • No central location for college housing
  • Currently, students struggle to
    • Find roommates online
    • Find relevant listings they are eligible for
    • Understand housing process
    • Understand pricings/fee
  • TAM: $1.1B, Max Lifetime-Value: $12.8B
  • Expect to be market leader → 40% market share
  • In 10 years → $75 million annual revenue

Leading signals

  • DAU on the HousingHero app/website 
  • Number of lease contracts signed per week
  • Number of transactions made on the platform 
  • Average time between setting up tenant profile and signing a lease contract
  • Percentage of users who sign lease contract
  • Retention rate of students from year to year
  • Retention rate of students after graduating

Other considerations

  1. Targeted online ads 
    1. Pro: Additional revenue source
    2. Decided against:
      1. Negative sentiment around ads among college students
      2. Product is not currently tailored to ad-revenue business model
  2. Premium Subscription Service
    1. Pro: Higher quality features
      1. More empowered roommate matching
    2. Decided against:
      1. Target market has high price elasticity
      2. Larger available market if everything is free

Why now?

  • 78% of college students live off campus
  • Students in competitive housing markets (e.g., UCs) continue to be denied housing
  • Student quote: “You have to sign a lease at least a year before if you want decent housing.”
  • Rarely find such a large market in real estate with no specialized player in this segment
  • Lifetime value of acquiring college students is substantial: $12.8 billion.
  • Launch before real estate mogul establishes themselves in this market

Summary of technologies involved

  • MERN stack for web & mobile dev.
  • AI-powered roommate matching algorithm & Housing GPT
  • Filtering technology to only show relevant listings
  • Analytics tools for leading metric

Time frame 

  • 1-3w: Test our assumptions in more detail
  • 1-3m: Finish initial HousingHero for HousingHero MVP
  • 1-3q: Test MVP at a handful of UCs
  • 1-3y: Refined prototype, launched at all UCs and additional colleges
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