Thesis Driven

Thesis Driven

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Thesis Driven
Lookalike Modeling in Real Estate
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Lookalike Modeling in Real Estate

Could real estate investing benefit from borrowing a digital marketing mainstay?

Brad Hargreaves's avatar
Brad Hargreaves
May 16, 2024
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Thesis Driven
Thesis Driven
Lookalike Modeling in Real Estate
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What’s the Bushwick of Chicago?

What’s the Mission District of Boston?

What’s the Brickell of San Francisco?

These kinds of questions fuel late-night debates among transplants and travelers of all kinds. But picking “lookalike” neighborhoods across different places is relevant for not just tourists but real estate investors expanding their geographic footprint and looking for the next hot neighborhood.

The concept of “lookalikes” will be familiar to anyone with a digital marketing background, as they’re a staple of social media marketing. In that context, a marketer would upload a list—say, their current customer base—to a social media platform. The platform will then produce a much larger list individuals who “look like” the initial group. The “lookalike” might be based on behavior, demographics, interests, or other factors. For marketers, it’s a proven and successful strategy.

Today’s letter apply that same logic to real estate, exploring lookalike modeling at a neighborhood level. We’ll do this by using i360’s new CENSAI tool, which includes a lookalike model. We’ll explore:

  • Why lookalikes matter;

  • How the lookalike model can be applied to real estate;

  • Test-driving i360’s lookalikes tool;

  • Using data to identify new target investment markets.

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