As the baby boom generation ages, the demand for high-quality senior living facilities is expected to rise dramatically. However, the costs of constructing and operating senior living developments are rising, too. As a result, choosing the most productive locations for your communities is absolutely essential, whether you’re offering independent living, assisting living, memory care, or a combination of all three.
As a senior living operator, there are two key questions you should be asking yourself right now: “How well should I be doing at a particular community?” and “Where should my communities be located to achieve the best performance?” Ultimately, both questions can be answered using customer analytics.
The problem with traditional analyses
For years, senior living operators have made decisions based on analyses that are rudimentary at best and misleading at worst. They use very basic demographic information – including age, address, and income levels – to analyze performance and recommend new locations. As you might imagine, this often yields few insights and leads to less-than-stellar results.
In-depth customer analytics means better decision making
At Buxton, we incorporate many more variables into our analyses, making our models much more accurate and reliable. Just as a retail store attracts certain types of customers, your senior living communities will attract particular types of residents, depending on your cost, amenities, and location. We can help you examine the nuances of the different types of residents, allowing you to see true demand and potential. Together, we can identify the specific attributes of your typical residents, then find many other individuals who share these characteristics. This not only helps you predict demand and analyze performance – but it can also boost the efficiency and effectiveness of your marketing program.
Considering the X-factor: adult child influence
As people age, they will often move closer to their families – an event that will obviously affect the senior living facility they choose. Unlike traditional analyses, Buxton data models take this major factor into account. We add a geo-spatial element to the mix by considering where adult sons and daughters of potential residents live, allowing you to better understand your target market. We also look at other important factors that can impact occupancy, including the proximity of your senior living centers to health care facilities specializing in geriatrics.
Answering the two key questions
Through better data analytics, you can answer questions about current performance and future locations with much greater confidence. If you have communities with lower-than-expected occupancy, is it the location or the quality of the operations driving these results? You can evaluate the performance of your entire portfolio in this manner. You can also find prime locations for future construction and determine whether or not to acquire a competitive facility.
The senior living space is in a bit of a lull right now, but demand is expected to pick up significantly in the coming years. Senior living operators who get ahead of the “silver tsunami” and make the right decisions for the future will be better set up for success.