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Leave Bias Behind When Analyzing Data

As an industry, we have a difficult time analyzing performance data without inserting our own bias into the equation. But the data will speak for itself, if we let it.

Perception isn’t necessarily reality. But in multifamily, perception routinely drives decision-making. Apartment operators typically have a “feel” for what works and what doesn’t, based on years of experience with leasing and lead conversion. Unfortunately, decisions based on feel or perception are rarely supported by current data.

As an industry, we have a difficult time analyzing performance data without inserting our own bias into the equation. Operators review leasing and performance data with expected findings already in mind. But the data will speak for itself, if we let it.

Multifamily’s hesitancy to change is rooted largely in preconceived notions about the way things work. Operators regularly review data with the objective of confirming what they already believe to be true. They seek affirmation for whatever business model they currently think works best. When we attempt to feed our own bias through data analytics, we often miss the story actually being told by the numbers.

Operators may assume that they only need a chatbot or other AI services turned on after hours when the leasing team is gone for the day. However, 15%-20% of leasing calls come in outside of office hours, and overextended property teams don’t have the luxury of sitting by their phones during the workday. They’re often away from the office taking prospects on tours or handling other responsibilities and resident needs.

Anyone Home data shows the average property team misses 56% of its inbound leasing calls.

How many potential leads are lost without a solution that handles leasing inquiries when associates aren’t available?

Based on similar assumptions, office teams might only make self-guided tours available during weekends, when the office isn’t staffed for guided tours. Yet, some renters prefer to start with a self-guided tour and meet with a leasing agent afterward, or come back for an agent-guided tour.

Self-guided and agent-led tours convert at fairly similar rates, but Anyone Home data shows that lease conversion can climb as high as 38% for communities offering both options.

By not listening to the data and catering to the touring preferences of prospective residents, how much revenue is left on the table?

In multifamily, decisions on the operator side are too often made before the data truly has an opportunity to fully weigh in. Bias wins out over fact. Industry leaders frequently have inflexible ideas about the viability and efficacy of new solutions, and fail to recognize or acknowledge data that points in a new or opposing direction.

To maximize property performance and enable bias-free decision-making, operators require an analytics platform that delivers comprehensive, hyper accurate and up-to-date data. Data has to be reliable, trusted and used to make critical decisions at all levels of an organization.

Ideally, an analytics platform will utilize bi-directional integrations to tailor data collection and deliver completely customizable reports. Operators should be able to pull detailed metrics, including daily lead conversion percentages, conversion data by time of day, lead generation and conversion rates by source, and lead management results at each stage of the leasing process.

Customized analytics reports – whether run daily, weekly, or monthly – allow organizations to hone marketing and leasing strategies, and address areas of underperformance that negatively impact conversion. Management companies can further deploy customized reporting to assess individual property needs and execute specific leasing strategies to optimize site performance. Simply put, actionable data enables properties to operate more efficiently and effectively.

When we discard our personal bias and listen to what the data tells us, the message is generally very clear. The numbers never lie, so it’s time to stop lying to ourselves and go where the data leads.

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Leave Bias Behind When Analyzing Data

As an industry, we have a difficult time analyzing performance data without inserting our own bias into the equation. But the data will speak for

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