Residences for the elderly have become a popular solution to address these issues, though these opportunities aren’t equally distributed across Quebec. For a savvy real estate investor, it’s essential to identify where the future demand for these residences will be.
Challenges
This is the core challenge for a real estate investor before using Civ.GEO. When an investor considers building a new residence for the elderly, several challenges arise. First, they must identify the regions or neighborhoods where demand for this type of housing is highest. This analysis should factor in the demographics of the local population, income levels, the availability of medical and social infrastructures, and real estate market trends.
Next, the investor must assess the potential competition in the target area, taking into account the existing elderly residences and their service offerings. It’s critical to ensure that the local market can accommodate a new residence without oversaturating the supply and risking the project’s financial viability.
Finally, the investor must consider local regulations and zoning constraints that may influence the site selection for the residence’s construction. These regulations may address issues such as building density, safety standards, or accessibility requirements for people with reduced mobility.
Solution
CIV.GEO Supporting Real Estate Projects
To tackle these challenges, our investor used advanced tools and analytical methods to make informed decisions. One approach involves examining elderly residences on Google Maps, demographic data from Statistics Canada, and analyzing hospital capacity through public data from Integrated Health and Social Services Centers (CISSS).
This process can be labor-intensive as it’s not limited to one or two specific locations. It involves comparing distant areas at a granular level, often across an entire municipality. The goal isn’t to build a facility that’s only relevant today; it’s to construct a building that will be beneficial in 3–5 years and remains so over the next decade.
On Civ.GEO from Civision, the investor could do exactly that. They began by comparing populations by density of people aged 55–64 (future retirees) and those aged 65–75 (current retirees who may soon need more support). For example, they found that Trois-Rivières has a higher density of people aged 55–64 per square kilometer compared to Sherbrooke, Drummondville, Saint-Jean-sur-Richelieu, and Lévis, making Trois-Rivières a more promising area to focus on initially.
Our AI also estimates future population growth by evaluating various factors, including past population growth, immigration, birth rates, and job creation projects. This allowed the real estate investor to forecast the market landscape in the coming years.
Finally, they were able to compare property prices across each city, the income levels of the elderly population, competition, and the health status in each region.
Outcome
The real estate investor identified the optimal areas in Quebec to establish a new residence for the elderly.
Civ.GEO enabled them to maximize their investment. Our client’s goal wasn’t just to invest in a profitable location but to optimize ROI to reinvest quickly into a new real estate project. By providing reliable, precise data, we helped them maximize their return on investment.
Social Impact
This solution ensures that an aging population is better served with social services without needing to relocate to access healthcare. By clarifying Quebec’s demographic, social, and economic landscapes, we also highlight the most underserved areas. Without data, the precarious situation of these elderly individuals would only be revealed once conditions become unbearable, at best.
Together, we’re enabling the preparation and implementation of solutions just as these populations will need them, instead of relying on emergency measures.