Why and How You Should Do A/B Testing for Apartment Marketing


December 7, 2020

There are a lot of best practices you can gather about digital apartment marketing before you ever launch your own campaigns. But the best campaigns are built on the foundation of testing and optimization. No two markets are exactly the same, so to learn what works for your real estate brand, you have to be willing to try, fail, and learn along the way. Luckily, A/B testing—AKA split testing—is a tried-and-true practice among marketers, and it’s built into many of the most popular advertising platforms. Plus, when done strategically, it saves you much more money than it costs, making it a no-brainer for most real estate marketing agencies and in-house apartment marketers.

So what exactly is A/B testing, how does it work, and how should you employ it for your apartment marketing campaigns? We’ll answer all that and more below.

What is A/B Testing?

A/B testing is a type of split testing in which two versions of a marketing element are run simultaneously to determine which performs better. For example, if you take an existing ad for your property, but swap out the headline for a new one, then run both the new and the old version at the same time (i.e. version A and version B) to see whether the new or the old headline earns better results, that’s an A/B test. While split testing refers to a test with more than one version, A/B testing is simply the term for a split test using exactly two versions. However, the term A/B testing has become so ubiquitous you might hear it used synonymously with “split testing.” In any case, the basic methodology is the same whether you’re using two versions or more.

Ad headlines aren’t the only thing you might A/B test. Email subject lines, landing pages, CTAs, and lots more can be A/B tested to fine-tune your approach to apartment marketing for your real estate brand.

Why is A/B Testing Important for Apartment Marketing?

We said it earlier, but it bears repeating: no two real estate markets are exactly the same. Your audience of potential residents might respond to one headline while another audience might ignore it. And while you might land on a decent marketing strategy by following best practices and common sense alone, you could be missing out on a lot of optimization if you never test your approach.

When real estate brands employ A/B testing, they give themselves the opportunity to understand how to put their marketing dollars toward the most cost-effective outcomes. For example, you might find that advertising “Get 2 Months Rent FREE” performs better than “Get Half-Off Rent for 4 Months,” earning you more leases even though the rent concession costs you just as much no matter how you phrase it. A/B testing can amplify—sometimes dramatically—the effectiveness of the same basic marketing campaign, simply by tweaking the messaging you use, the color of a CTA button, the header at the top of your landing page, or the subject line of your email.

How To Do A/B Testing for Apartment Marketing

Before you start A/B testing, though, it’s important to know some basic dos and don’ts. Otherwise, you can easily get results that are skewed, confusing, or just not very useful. There are a few essentials to keep in mind when setting up an A/B test.

First, it’s important that you pick only ONE variable to test at a time. If you run a version of a display ad with a different headline AND different photo selection, you won’t know whether the difference in performance is due to the headline messaging or the photo selection. Unclear results like this make it challenging to use what you’ve learned to optimize your results. While it can be tempting to test everything all at once in the hopes of expediting the learning process, you’ll actually slow yourself down because you’ll have to wade through unclear results that don’t offer actionable takeaways.

Secondly, it’s important that you split your sample groups evenly and randomly. Doing so ensures that one version’s higher performance isn’t simply due to it having more opportunity to excel than the other. For example, if one landing page is shown to prospects who have visited your site already and another version is shown to new visitors, you won’t know whether the difference in performance is due to the audience it was shown to or due to the landing page design itself. Randomizing and evenly segmenting the users who see version A vs. version B helps ensure that you can confidently attribute differences to the variable being tested and NOT to any variables that are not being tested.

On a similar note, avoid jumping to conclusions until versions A and B have both been shown to a good sample size. The sample size sufficient to draw reasonable insights can vary based on your goals and what’s being tested, but in general, the larger your sample size, the more confidently your can draw your conclusions and apply your learnings.

Finally, understand your KPIs (Key Performance Indicators) before you start testing. Since there will likely be a variety of measurable differences among factors like CTR, impressions, time spent on page, percentage of new website visits, open rates, and so on, it’s important that you know which are most important in measuring success. For example, if what you want is more traffic to your site, measuring CTRs and new visitors to the site (through Google Analytics) are your key metrics to look at. If what you want is to raise awareness, impressions and views may be more important barometers of your success.

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