Real estate development is like walking through a minefield with a 5-year-old map. It’s fraught with risks and unknown variables. Underwriting models do a great job of showing your assumptions, but how do you know your assumptions are right? Verify hard-to-make assumptions with tenant retention curves.
At Bullpen, I use customer retention curves to determine whether we are getting closer to (or further from) product-market fit. Applying the concept of retention to multifamily development, you can use tenant retention to uncover critical insights in your market.
Download the free excel template at the end of this article to see how I apply retention curves to multifamily data.
What is a retention curve?
The most important metric in a software startup is customer retention. A retention curve measures the percentage of customers who complete an action over a period of time. In many cases, it is the main metric used to find product-market fit.
In the case of Facebook, a retention analysis might measure the percentage of users who return to the app (action) daily (time).
Airbnb might measure retention as the percentage of guests who book stays (action) annually (time).
Your product will determine the action that you want to measure. Typically this is the “magic moment” when a product solves a person’s problem. At Bullpen, we measure company retention with monthly (time) billing activity (action) and freelancer retention with monthly (time) job applications (action).
Your time variable should be determined based on the expected use of your product by customers. This is typically daily, weekly, monthly, or annual retention.
Retention is typically tracked in cohorts. In other words, retention is most useful when measuring the behavior of a group of users. For example, LinkedIn might measure the retention of users who create new accounts in the month following their newest software update.
A good retention curve resembles the letter “u”. I’ve created two curves in the example below, one with good retention, and the other with poor retention.
What is a multifamily tenant retention curve?
A multifamily tenant retention curve measures the percentage of tenants who renew their lease annually (aka “tenant retention”).
Tenant retention curves are most useful when they’re used to compare different tenant cohorts. For example, you might compare retention in one neighborhood to another. Moreover, you could use the same analysis to gut-check your financial projections. Properties with less turnover typically have less operating costs.
In the below example, we show tenant retention curves for a stable neighborhood with long-term tenants and a more transient neighborhood where tenants turnover more quickly.
You can also use retention curves to make hypotheses about tenant preferences within a neighborhood. Perhaps you find that retention is higher in 1-bedroom units than studios and 2-bedroom units. You might use this information to build more 1-bedroom units into your next development.
In the below tenant retention curves, we’ve analyzed a property with various unit types.
You’ll notice the above retention curves don’t create a “u-like” shape. Unlike software retention, It is rare that a tenant retention curve would ever look like a “u”. An increasing retention curve would indicate tenants leave and return to the property at a future date (very unlikely). As such, I consider a good tenant retention curve one that slowly fades to the right.
How does this impact my development strategy?
Tenant retention in multifamily properties materially impacts the performance of the property.
High retention will result in less turn and leasing costs and might indicate that there is room to increase rents.
Strong retention in a neighborhood might indicate to a developer that there is a demand for more rental housing.
However, retention can also send mixed signals. High retention can be negative to investors in fast-growing markets with rent control. For example, San Francisco multifamily investors would rather own buildings with high turnover where they can regularly increase rents to market.
What about multifamily acquisitions?
In addition to development, retention curves can be used in multifamily, property-level acquisition analysis as well.
However, you’ll need to keep in mind that tenant retention curves require a significant amount of data to be useful. I typically won’t consider retention curves on properties with less than 50 units. The best retention data will come from properties with more than 100 units.
One of the most useful ways to use tenant retention in an acquisition is when considering whether or not a property can bear rent increases. A property with high retention, when compared to others in the neighborhood, might be an indicator that rents can rise. This analysis can also be done within a property, where you might find high retention and price upside in 2-bedroom units.
In the below example, I’ve compared retention curves for different units types. Perhaps A1 units can bear a rent increase?
Additionally, you can use tenant retention to inform your value-add decisions. Perhaps you’re considering adding laundry to your units. Use a retention curve to empirically determine if tenants favor units with laundry.
Where can you find data to create tenant retention curves?
A rent roll has all the data you need to create tenant retention curves. You simply need to subtract the lease start date from the current date to determine how long a tenant has been in their unit.
Ask your local property manager for anonymized rent roll data or leverage your current properties to get a big enough sample size.
What decisions can a tenant retention curve make easier?
As I explain above, tenant retention curves are best used when they compare variables within a property or market in which there are ample data points. I typically won’t consider a retention analysis valid unless there are at least 50 data points for each curve.
At the property level, tenant retention can help you answer questions like the following:
- Should I convert my studio apartments into one-bedroom units?
- Is it wise to add laundry to my units?
- Do my leasing and turn costs make sense?
- Does my vacancy assumption make sense?
- How long will it take me to finish a value-add strategy without ending leases?
- Do I have room to increase rents on my 2 bedroom units?
Tenant retention can also answer a lot of questions about neighborhoods.
- How transient is my tenant base?
- Should I build one-bedroom or two-bedroom units?
- Does this area cater more to young professionals or families?
- What amenities do renters in this neighborhood value?
- Does parking off-street parking matter to renters?
As in all real estate decisions, tenant retention curves should be used in conjunction with other analysis before making investment decisions. Add it to your toolbelt, and use it when you need answers to tough questions.
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