Could you imagine being able to detect and prevent a health scare with a resident before the event occurs? Alternatively, imagine responding to shifts in occupancy with a high degree of agility.
Data Science can create operational efficiencies, improve resident’s health, drive staffing decisions, or any number of initiatives. This is the power of data science when applied to marketing and the resident acquisition process.
Command your community’s data and continue reading to learn:
With accurate inquiry KPI tracking, your senior living marketing team can adjust its strategy to increase inquiries for a specific service line with a cost-effective advertising channel. Applying data science to marketing during this event answers the following questions:
1.) Where are we generating quality inquiries?
2.) Is our team fielding all inquiries appropriately?
3.) Is our community reaching our desired audience?
During the initial inquiry, a prospective resident and/or ACI’s interest was piqued and they’re now aware of your community’s offerings.
The next goal becomes encouraging the prospective resident or ACI to visit your community’s campus. During this stage in the resident sales life cycle, data science can provide insight into the following KPIs:
Senior living marketing and sales teams have approximately 30 days to entice a prospective resident after a tour to move into a community. After that, the likelihood sales teams will convince the prospect to move in drastically diminishes. Given that reality, your team can use a data science model to gain clarity into the following questions:
1.) Is our team being proactive in arranging visits?
2.) Is our team engaging with high-value inquiries quickly enough?
3.) How can our community improve its conversion rate?
With the initial inquiry crossed off, your sales team is one step closer to impacting identified gaps in occupancy levels. Using data science for marketing, your community can stay in step with the resident journey by actively adjusting to changes in campus tour KPIs:
Your community can identify where efficiencies can be made after analyzing its data through the lens of the KPIs and questions above. Additionally, data science for marketing and sales will shed light on questions such as:
1.) Are tours driving conversions as expected?
2.) Has our community forecasted conversions accurately?
3.) Why are some prospective residents not converting?
A prospective resident became a move-in. Now, your senior living marketing team can assess the effectiveness of its cumulative efforts. An investment in data science for marketing purposes will provide feedback into these move-in KPIs:
With insights from the questions and KPIs above, your senior living marketing team will have data-driven clarity into the following move-out questions:
1.) Are residents switching service lines?
2.) How long do residents typically stay?
3.) What is our community’s resident average lifetime value?
To clarify, a “move-out” is defined as the untimely passing of one of your community’s residents, or the event where a resident elects an alternative living option. Resident retention is a challenge for providers across the continuum of care. Assisted by data science, your community can strategically plan for these occupancy shifts.
By deploying a data science model, your team can impact these move-out KPIs:
Data science for marketing can be leveraged to narrow the timeframe from initial inquiry to move-in, while proactively preparing for the event of a move-out. Our team created a data science model exclusively for senior living providers to help them methodically influence their desired outcomes.
To learn more, contact our team. We’ll help your organization use its existing datasets to transform operations, marketing and occupancy levels.
