A/B Testing Pricing for Multifamily Revenue Management

As the real estate data science team (currently 2 people, but still a team!) at Hello Data has been analyzing rent and time on market from apartments across the country, we’ve noticed an interesting phenomenon in some properties… they keep a few units on the market seemingly forever.

Usually, it takes a few weeks to lease a unit, sometimes less, sometimes more, depending on the market. But sometimes we see units listed for 90+ days, with continually changing prices. Here’s an example from a real unit in our database that has been on the market for 97 days and counting:

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At first, we wondered why anyone would do this. They’re missing out on revenue for that unit if it remains vacant, right? If they have a model unit, maybe it makes sense. But if prospective residents see that unit advertised and come in the door expecting to rent, that can’t be a good experience.

The Benefits and Downsides of Continually Testing Price Levels

Then we realized that some property managers are keeping units on the market to test different price points. It’s something we’ve seen only at larger properties – definitely not common for the average landlord, but we figured this technique might be used for a variety of reasons:

Daily Market Analysis

‍The manager might want to gauge how different price points impact demand. By listing the unit at various price levels, they can see how quickly they get responses, the quality of potential tenants, or the number of viewings they secure. This gives them a better understanding of the true market value of a unit, and helps them gather data on tenant preferences, price elasticity, and other market dynamics.

Data for Dynamic Pricing Models‍

Some property managers clearly use this technique to get data for revenue management solutions or dynamic pricing models. These models continually change rental rates based on factors like seasonality, local events, or overall market demand. Keeping a unit on the market allows them to continuously adjust and evaluate these models.

Promotion and Advertising

‍Sometimes, a unit might be kept on the market as a sample or promotional listing. Even if it’s not actually available, it can attract potential tenants to the property management company, who can then be directed to other available units.

Given these benefits, it seems like a smart approach. There are definitely some downsides and risks to this strategy though. Here are a few we thought of:

Lost Revenue

‍While testing different price points, the unit could remain vacant for extended periods, leading to a loss of potential rental income.

Reputational Damage

‍Continuously listing and delisting or changing the price of a unit could create a perception of instability or unreliability with potential tenants. If tenants find out a unit is being used as a test or isn’t genuinely available, it can create mistrust. If it’s an occupied unit being advertised, that could be even worse for the relationship between landlord and tenant.

Operational Overhead

‍Managing this kind of strategy requires more time and attention than simply setting a price based on market research and sticking with it. And today in particular, property managers have ZERO extra time to spend on these things.

So, while some property managers might use this strategy of keeping a unit on the market to test different price points, it helps to weigh the benefits against the potential risks.

A Better Solution for Dynamic Multifamily Pricing and Asset Optimization

At Hello Data, we think property managers are already being asked to do too much. They need to be market analysts, data scientists and pricing experts. They need to be talented sales reps, convincing residents to lease at their properties, and they need to be empathetic customer success reps, ensuring a positive experience for their resident base.

We’re building next-gen revenue management solutions to make life easier for property managers. We use AI to automatically identify your most statistically similar rent comps and expense comps, then survey them every day to recommend pricing and operational improvements that maximize your NOI.