Gen Z is shaking up the status quo when it comes to traditional student housing marketing strategies. Meanwhile, new predictive leasing technology enables better approaches for savvy owners and operators ready to shift toward more insightful, data-driven marketing attribution methods.
One doesn’t need to be a marketing expert to see the vast differences between Gen Z and its predecessor cohorts in everything from consumer behavior and expectations to the media channels they frequent. “There is a view in the marketing world that Gen Z ‘broke’ the marketing funnel, and that is exactly what happened,” says Martin Stein, chief analytics officer at Conversion Logix, a full-service marketing technology company.
The classical marketing funnel involved creating awareness, both offline and online, to generate interest, desire and, eventually, drive action. Business Vogue has described this new model of marketing as an infinite loop of inspiration, exploration, community and loyalty. “We have to take this evolving landscape into account to come up with a marketing strategy that caters to the changes in behavior and technology,” says Stein.
What it boils down to is that reaching the Gen Z renter is more complex. The message has to be more than just, “Here’s the unit, and here’s the price.” Property owners and managers have to be more inclusive in terms of the content they are putting out, and they have to be active across many channels. It’s important to rethink marketing messages that resonate with Gen Z renters, such as highlighting amenities, opportunities for social engagement and services, as well as where those messages are placed.
That marketing shift requires more insight into what works and what doesn’t in order to develop more cost-efficient marketing strategies. Predictive leasing allows human experts within marketing teams to wrap data science around marketing strategies to provide insight into the effectiveness of marketing activities. “By leveraging analytics you can create highly tailored personalized campaigns rather than a one-size-fits-all spray and pray approach,” says Stein.
Gaining a Holistic View
The purpose of predictive leasing is to determine the probability of move-ins based on past customer journey patterns. By tracking those individual customer journeys at scale, Conversion Logix is developing machine learning and AI-powered analytics that identify patterns and relationships to help marketers understand what has the greatest impact on leasing results at a specific property.
Predictive leasing needs to have a fundamental measurement technology, which is where unified attribution comes into play. Unified attribution is a form of marketing attribution that takes into account ad impressions, clicks and realistic customer journey data across multiple sources to provide marketers with accurate attribution.
Predictive leasing combines data from the different touch points where prospects leave their digital footprint, such as TikTok, YouTube and search engines, among others. It then unifies that individual data along with microdata, such as how much an owner or operator spent on marketing and how many impressions were generated.
The unified attribution component of predictive leasing is a crucial piece of the puzzle that enables marketers to quantify what works and what doesn’t work in terms of marketing channels. This allows student housing marketers to gain deeper insights into customer behavior, optimize their campaigns and identify the most effective ways to spend marketing dollars. “The number one thing about predictive leasing is the holistic view that we’re creating. Better assessments enable greater effectiveness, helping to optimize marketing spend,” says Stein.
Additionally, unified attribution works with many channels and provides a very clear picture with far less historical data, which is ideal for the highly seasonal and fast-moving student housing sector. Concerns about data privacy and a move away from cookies to collect browsing data have spurred the rise of unified attribution as a new way to aggregate data.
Proactive Marketing
The second key component of predictive leasing is aimed at increasing leasing conversion rates by using data analytics and AI to identify probabilities to forecast leasing demand, student preferences and the likelihood of a conversion to offer a more proactive approach for marketers. These models predict the next likely step and most probable way to get to conversion for a user by looking at all of the data and analyzing the patterns.
“It provides a sharp and clear picture, not only on a channel side but even on a campaign level people have not had before,” says Stein. “We’re the first one implementing and building it, and we are super excited with what we have seen so far in results.”
Driving Better Outcomes
Predictive leasing is replacing heuristic or “good enough” methods of relying on past results with statistical models and data-driven probabilities. The new modeling allows users to consider a variety of different scenarios. What if I changed my marketing message to focus more on the community aspect of a property, or what if I shifted more of my marketing spend to TikTok?
For example, Google ads tend to score high in last-touch attribution, but if a marketing team knows through predictive leasing that combining Google ads with TikTok ads drives even more conversions, then they can allocate the appropriate funds to these two solutions and maximize the return on investment by splitting the budget accordingly.
Predictive leasing using unified attribution gives property owners and managers a precise look into conversion probabilities, which, in turn, allows for a more targeted approach to marketing and better resource allocation. “Those are all things that can be achieved if we better understand what motivates people and what inspires people,” says Stein. The technology also allows for real-time optimization, meaning that marketing teams can more quickly shift strategies and tactics to drive better results, he adds.
Proactive management of leasing activities driven by probabilities leads to better outcomes, and the future benefits go beyond marketing and lease-up to include operations, property management and development. “I believe marketers will have a much stronger business impact in the future because they’ll have a better understanding of the market-driving factors, the competitive landscape and what sets them apart from their competition,” says Stein. “If you understand all of that information when you connect supply and demand, you can build much better marketing programs that give you an edge over your competition.”
— By Beth Mattson-Teig. This article was written in conjunction with Conversion Logix, a content partner of Student Housing Business.
To learn more about Conversion Logix, click here.
For more information on becoming a Student Housing Business content partner, contact Rich Kelley, publisher, or Tim Tolton, media advisor.