Case Study

How to ease the process of applying for a social housing in Paris ?

Paris Habitat is a social landlord for the city of Paris. To leverage their large dataset, they organized an innovation competition. Our team proposed to use their data to empower social housing applicants. Our solution is a website providing the estimated waiting time of a social housing application.


Paris Habitat




2 days


UX Designer


Two days and an heterogenous set of data, those were the contraints of the competition. The jury shared its selection criteria :

  • use existing data of Paris Habitat
  • propose a solution that can be immediately developed
  • solves Paris Habitat users and employees needs


We focused on the process of social housing application. We targeted both the current and futur applicants as users. From experience we know that this process is opaque and too long. One woman got a social house 17 years after her application ! It is a very frustrating process for the applicants, but also for Paris Habitat employees. That’s why we asked ourselves :

How might we bring transparency to this process, so that applicants can understand and follow their application ?


The data of Paris Habitat provides information on the social housing market in Paris in realtime. So we are able to display an indicative waiting time for a given request of social house.

The benefits for Paris Habitat are :
  • call center less overwhelmed
  • positive impact on the company image
  • better turnover of the social housing stock
  • no integration needed with governmental websites
The benefits for the applicant are :
  • instant estimation of waiting time
  • recommendation of similar request with less waiting time
  • free and anonymous


Nothing fancy, we had no time to waste !

01. A morning workshop to find our teammates

Participants of the competition attended a mandatory workshop morning to kickoff the event. We were three groups of twenty people from various background. A professional UX Designer led the workshop. Although I found it frustrating to postpone the start the « actual » work, this workshop turned out to be a very good starting point. We brainstormed the stakeholder map, an did some focus group interviews. After that, we made the teams. Myself and two other participants wanted to work on the process of social housing application.

1/3 social housing offers were refused in 2017 : among them 31 % due to the lack of answer from the applicant, 9 % due to a too high rent, 8 % due to a wrong housing typology and 5 % due to neighborhood issues.

02. Informal discussion and experience sharing

We had the opportunity to ask a few questions to the Paris Habitat Director and to the IT Manager. Thanks to their feedback, we understood that the social housing application is not a unified process across landlords in Paris. There is a unique entry point online, and a unique list of applicants for all social landlords. But the decision of attribution depends on the social landlord and seems to be secret.

We also discovered that Paris Habitat’s call center is overwhelmed by applicants looking for updates on their situation.

03. Journey mapping of an extreme user

As an extreme case, we took a user experiencing family changes over the years. We showcased how Paris Habitat could be an helpful companion in this person’s life.

04. Night prototyping

We spend the night prototyping a few screens and tested them with some participants. Participants were enthusiasts, which was motivating for us. I designed an interactive prototype, and my co-worker a functional prototype. In one night we managed to get two complementary prototypes.

Our proposal : Locaboost !

Here is a landing page to explain with simple words the purpose of the tool, sorry it’s in French ! We called it Locaboost.


Screen 1 - Applicant situation

The user is asked to give informations about his household : revenu, composition, type of request.


Screen 2 - Request parameters

The user can select the type of house he wishes, the location and other parameters.


Screen 3 - Estimation

Given the input, the tool is able to display immediately an estimation of the waiting time. Recommendations are made for similar combinations of parameters that lead to a diminished waiting time estimation.

Accomplishments & Learnings

We received the third prize, over 13 projects. We also received a « Coup de Coeur » special prize from a member of the jury. We received positive critics, and were the only group presenting a prototype.

I discovered that UX methods worked well under the pressure of short deadlines. Our process allowed us to dedicate time to prototyping, unlike other teams.

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