Data & Analytics

Using Location Insights to Uncover Untapped Markets

• by Jason Stanley
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Understanding Granular Attributes Crucial in Identifying Opportunities and Risks By Jason Stanley Single-family rental (SFR) is hardly a new phenomenon, but it has seen explosive growth recently. Occupancy in Q4 2021 was near 95%. According to CoreLogic’s Single-Family Rent Index, SFR has seen 13 consecutive months of record-breaking year-over-year (YoY) rent growth for all price tiers. In April 2022, the YoY SFR rent price growth was more than double what it was one year prior and over six times higher than it was two years prior. The increasing competition for deals also creates new challenges, including how to discover opportunity-rich neighborhoods that investors are ignoring. Most investors already have access to the same information about new homes coming on the market. But what about hidden opportunities similar to high-demand neighborhoods that have not seen a spike in SFR investment? Most investors would jump at the opportunity to identify these gems, yet they lack the granular insights needed to do so. At Local Logic, we are building products that help investors quantify street- and neighborhood-level insights to identify these opportunities and avoid critical risks. Below, we show how investors can use our insights to discover promising neighborhoods that are not on most investors’ radars. Identifying a point of reference Phoenix is a top destination for residential real estate investment. In the Phoenix metro area, Arrowhead Ranch in Glendale stands out as one that has seen strong SFR activity. On the one hand, SFR homeseekers like the neighborhood. On the other hand, investors are sufficiently aware of the neighborhood’s attractiveness to make competition for deals a challenge. Where can we find neighborhoods similar to Arrowhead Ranch that also elicit strong demand from SFR homeseekers but with less competition? Quantifying neighborhoods on key SFR variables First, we need to select the variables we will use to measure similarity. Local Logic has hundreds of location insights at the site, street, and neighborhood levels, so there is a lot of room to analyze which variables best predict success. For this analysis, we chose variables that often show up in SFR buy boxes:  »         Proximity to grocery stores  »         Proximity to high-quality schools  »         Proximity to interchange  »         Neighborhood wellness score  »         Household income // Example: percent of households with annual income between $40,000 and $59,999; percent of households with annual income of $60,000 or above  »         Employment level // Example: percent of the civilian labor force 16 years of age or older that is employed  »         Percent change in the size of the labor force // Example: percent change in the numberof people 16 years of age or older in the civilian labor force  »         Median rent cost  »         Median mortgage cost Scoring each neighborhood in the Phoenix metro area on each of the listed dimensions produces a dataset for subsequent steps. With rows in the dataset as inputs, we use a k-nearest neighbor algorithm to measure neighborhood similarity. We could use this to identify the similarity between any pair of neighborhoods in the area. For this analysis, we focus on similarities with Arrowhead Ranch. Identifying a promising alternative neighborhood To identify the most promising alternative, we first rank neighborhoods by their similarity to Arrowhead Ranch. Augusta Ranch stands out as the most similar neighborhood. Augusta Ranch is 42 miles from Arrowhead Ranch. Yet, our granular location insights show that it is very similar on the dimensions selected as key for investment and for eliciting homeseeker demand. How individual neighborhoods score on a few key dimensions shows why Augusta Ranch ranks as most similar to Arrowhead Ranch. The figure above provides heat maps for proximity to grocery stores, interstate access points, and schools. For any of these dimensions, Arrowhead Ranch is similar to many neighborhoods in the metro area. When combining the dimensions listed above, Augusta Ranch stands out as very similar. Augusta Ranch is slightly further from downtown Phoenix than Arrowhead Ranch, yet it is close to several satellite towns that are commercial and employment centers. That bodes well for homeseekers seeing it as a residential neighborhood with easy access to employment hubs, retail centers, and services. Examining the number of SFR units currently on the market in the two neighborhoods suggests that Augusta Ranch has lower market activity. That is promising for investors looking for neighborhoods that are similar in character to our reference point but with less competition. Risk avoidance Risk analysis is something most investors do, but not all risks are treated as importantly as they should be. Physical climate risks were long ignored because the effects were not large enough to matter for most investments. That is no longer the case as physical risks grow in more locations. According to Climate-Check, Arizona ranks as the riskiest state in the country when it comes to drought. The Phoenix region faces lower drought risk than some other cities in the state. But even within a single metro region, it’s important to drill down since different neighborhoods face different levels of risk. Plotting ClimateCheck drought risk data for neighborhoods throughout Phoenix, we see that Arrowhead Ranch faces a higher drought risk than Augusta Ranch. This is another reason that makes Augusta Ranch a solid investment potential compared to other areas. Our location insights help investors understand granular attributes crucial in identifying and measuring opportunities and risks. This is true for SFR. But it’s just as true for multi-family, for-sale residential, office, retail, and public sector services. Customers are already using our granular insights to assess incoming deals, measure risk for new and existing properties, and uncover hidden opportunities. Every site has its own set of specific attributes, each of which can be measured and monitored — if you have access to the location insights to make that possible.