---
title: "Multi-Unit Real Estate & Site Selection Advice - More On Brokers & Data"
url: https://burnaze.com/article/87d6e935-3872-4a8d-8b1b-539ae46d46a3
source: "Franchising.com"
original_url: https://www.franchising.com/articles/multiunit_real_estate__site_selection_advice__more_on_brokers__data.html
author: "Multi-Unit Franchisee"
category: "Franchise Industry"
industry: "Franchise Industry"
topics: ["Development & multi-unit","Operations"]
published: 2019-07-23T09:00:00.000Z
modified: 2026-11-01T02:35:04.064Z
image: https://imgs.franchising.com/art/articles/4702_plate.jpg
---

# Multi-Unit Real Estate & Site Selection Advice - More On Brokers & Data

**TL;DR:** Multi-unit franchise operators and real estate experts share insights on site selection and real estate challenges, highlighting the importance of local brokers and data. Local brokers and data analysis tools, such as those provided by LocateAi, can aid in identifying great sites for franchises.

*By Multi-Unit Franchisee, originally published in Franchising.com on 2019-07-23. [Read the original](https://www.franchising.com/articles/multiunit_real_estate__site_selection_advice__more_on_brokers__data.html).*

## Story

Earlier this year, contributing writer Sara Wykes interviewed several multi-unit franchise operators and some real estate experts about how they handle site selection and real estate challenges in today's market. Those she spoke with talked about finding that perfect franchise location, one that augments the odds of success and reduces the risk of failure. Here are some insights culled from her interviews: Brokers, Data, AI, and The Local Touch Identifying great sites can be aided by local boots on the ground.

Local brokers often carry historical knowledge that hasn't yet been incorporated into the advancing state of data collection. Navin Bhutani is director of development for LocateAi, founded five years ago by three Stanford University computer science graduates who wanted to take artificial intelligence-driven data collection and analysis to a higher level. "But we don't want to take away the local market knowledge.

Data might say, for example, that one location in a Los Angeles neighborhood is better than another, but a local broker can tell us that there is customer traffic for a certain franchise type that flows in one direction toward another, but not in the reverse. For our AI to pick that up we would have needed to co-mingle sales data," Bhutani said. And the real world does produce behavior that might not be anticipated.

"Unless you see real life examples, you can't imagine the various possibilities of things that impact performance," he says, "like how the number of trees planted might correlate to public transit stops." Some agents can act as master brokers for franchises who want to roll out across the country, says Emily Durham, partner and director of hospitality services for Waterman Steele Real Estate Advisors. "But we don't do anything without local people.

Nothing compares to someone who lives across the street. You may have all kinds of resources, but we get local folks involved, especially because while there are patterns and correlations, it's not the same in every market."

## Entities

- Franchising.com (publication)
- Franchise Industry (sector)
- Multi-Unit (company)
- Multi-Unit Franchisee (person)
- site selection (topic)
- data analysis (topic)
- Contributing Writer (person)
- real estate challenges (topic)
- local brokers (topic)

---
Originally reported by Multi-Unit Franchisee, Franchising.com (https://www.franchising.com/articles/multiunit_real_estate__site_selection_advice__more_on_brokers__data.html). Summarized by Burnaze (https://burnaze.com/article/87d6e935-3872-4a8d-8b1b-539ae46d46a3).