Capstone – Project

Pricing for Small-Dollar Houses in Small to Medium Size Cities

A Collaboration Between

Engagement Synopsis

There are no reliable pricing formulas for rental housing worth less than $100,000. For landlords, this means there isn’t a good rubric for pricing based on features and location. For renters, it’s an information asymmetry issue that makes it harder for them to know what a fair rental price is, something particularly salient for the lower-income customers in this demographic. Our business suffers from this as well, so we want to work with a MBA team to help address this issue. We want to work with them on an analytics and pricing project that involves understanding how actors currently make pricing decisions, researching channels renters use to find housing, analyzing existing pricing information to identify variables impacting rent rates as well as attractiveness for renters, and exploring better ways to value a rental for customers. This will help us develop tools to pull in data from the sources the team finds and use their insights to develop pricing models that are fairer to lower-income renters in cities where this housing is prevalent.

Company Information

Hiring PotentialN/A

Company Overview


Course Info & Engagement Details

Engagement Format -
Students EnrolledN/A
Meeting Day & TimeN/A
Student Time CommitmentN/A Per Week
Company Time CommitmentN/A

Relevant Topics

Growth Strategy


There are currently no students assigned.

Program Timeline

Touchpoints & Assignments Due Date Type
Collaboration request published. Companies may express interest in participating.

Collaboration request published. Companies may express interest in participating.

November 16th, 2020 Event na
Collaboration request published

Collaboration request published

Companies may express interest in participating.
November 16th, 2020 Event na

Key Project Milestones

  • March 23, 2021 - Identify channels used by prospective renters and landlords to connect low-income renters with opportunities for affordable housing in cities with high low-income housing density.

    Guiding question:

    • What are the channels landlords utilize to advertise rental properties for low-income households in cities with high low-income housing density?
    • What are the channels through which low-income renters learn about opportunities for affordable housing in cities with high low-income housing density?
    • What data do these sources provide on the features and pricing of the rental properties?


    Suggested Deliverable:

    Directory of resources/databases/listings low-income renters utilize to locate affordable housing and landlords advertise rental property for low-income households, including their respective characteristics/features, benefits, and drawbacks.

    In addition to supporting the work for milestone 2 of this project, the directory should be useful for informing future advertising and related tech support.

  • March 25, 2021 - Create prospective models for fair and affordable pricing of rental properties for low-income renters.

    • Utilizing data from the directory developed in the initial milestone:
      • What are they variables that significantly impact rent rates (e.g. location, square footage, seasonality)?
      • What are the variables that significantly influence renters perceptions of rental opportunities?
      • What strategies do landlords use to boost the perceived value of their rental property to prospective renters (e.g. including utilities, furnishings, appliances)?
    • How do actors currently make pricing decisions on low-income rental housing?
    • What are some suggested strategies for increasing the value of rentals for customers?
    • Keeping in mind that the principle of fairness is crucial to our enterprise, what should our strategies be for pricing these assets?

    Suggested Deliverable:

    • Financial model/rubric for pricing based on rental property features, values, locations (not expecting a formula or algorithm)
    • Presentation/demonstration and report of real-world application of rental house and how you would price that out using the rubric/financial model.

    Resources: Hurry Home will provide Zillow data, Craig’s list scraping records, appraisals of houses for information on others who have approached this problem in the past.

    Constraints: How is COVID-19 impacting the market, particularly given the eviction moratorium ends in 2020? What do you see in terms of the data? Can you confirm or validate some of the things we are hearing between the finalizing of this charter in January and the launch of the project in March?

Project Resources

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Industry Mentors

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Academic Mentors

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