Smart Restaurant Operators Use Location Intelligence

During the past two years, restaurant operators have faced a bevy of challenges, which forced them to adapt to new service offerings and technology that many were not prepared to implement. One tool that has become of increasing importance in restaurant real estate is the use of location intelligence and data for growth planning. In order to be competitive, restaurant operators need to implement a data-driven approach in their development strategy.

From an individual market to a national analysis, location intelligence can provide restaurant operators in-depth insights to inform their real estate decision making.

What data does a restaurant need to begin?

Even if a restaurant brand doesn’t have performance or customer data, location intelligence can still be used for proactive real estate planning. Basic location information for a brand’s existing units is all that is needed to get started. This data can then be enhanced with consumer segmentation, massive mobile data and restaurant spend data. If available, performance metrics can also enrich the analysis. 

Getting started—Defining a customer profile and trade area

If a brand is looking to open locations using location intelligence, a first step is to create a core customer profile with behavioral segmentation. A customer profile identifies a brand’s core customer demographics and behaviors and is used to find new markets with similar customers.

Competition data can be analyzed either from a preferred-competitors list or an estimated comparison. Visitor traffic, restaurant spend data and performance data can also be applied to add another layer to the analysis. 

Once the data is defined, it is used to create trade areas and build a scoring index to evaluate new markets based on important variables such as time of day, population or income.

This exercise is critical whether you are looking to expand in a single market, regionally or nationally. Exploring a national expansion using only demographics, for example, is risky. Major metropolitan areas usually turn up as ideal markets, since they contain most demographic groups. A more thorough Market Optimization analysis can identify opportunities beyond the obvious. Similar insights can be provided at the local or regional level and can consider your potential proximity to direct competitors and whether that has a negative or positive impact on the site. 

Going deeper—Using analytics to estimate sales

Restaurant operators can obtain even deeper insights through more premium analytics such as peer comparison or predictive modeling.

Peer comparison analysis weighs similar existing markets and units against potential sites. It provides multi-factor scoring to support sales estimation and takes your real estate planning to the next level. When combined with market optimization, users can evaluate and prioritize markets across the country to produce a strategic roadmap for expansion. 

With at least 50 annualized restaurant brand units and a specified performance metric, predictive modeling can determine the unique factors that directly correlate to your existing restaurants’ performance. Restaurant-specific considerations like time of day, drive-thru, ratings, outdoor dining and catering are analyzed along with demographic and market factors to develop a solution that can be used to predict how new stores may perform. Using a variety of techniques, including machine learning, predictive analytics allow you to generate site forecasts to provide the information you need to make critical decisions.

Real-world application

Recently, a full-service luxury restaurant operator saw a national opportunity to grow, and they wanted to conduct their search using location intelligence. With an aggressive growth target, they sought the services of CBRE’s Advisory and Transaction team, seeking to lead with location intelligence to help them target the right markets.

While the brand wasn’t ready for a full predictive analytics platform, they could apply a data-driven approach to guide growth strategy and integrate it with their real estate transactions. CBRE’s Retail Analytics team worked closely with the client to develop and fine-tune a unique solution that would address their needs.

Customer segmentation, massive mobile data and competitor information were used along with the client’s unit location data to develop a correlation analysis and index scoring that focused on variables of importance to the client. The market scoring focused on income and behavioral variables to help determine the best markets for new locations,—including those outside major metropolitan areas.

The analysis was delivered in an interactive web app using CBRE’s Dimension technology, where the client can glean insights from heat maps, graphs and summaries. The dashboard provided one place for the operator to view their locations, top performers, competitors, correlation analysis and scoring results to identify general locations for new restaurants. The solution has helped the operator define their national growth strategy.

The bottom line

When it comes to applying location intelligence to real estate planning, there is no “one size fits all” solution. A customized and highly visual approach that considers client-specific requirements and data will have the best chance for success. 

Whatever the stage of growth or size of the brand, using location intelligence helps restaurant operators implement data and analytics to drive growth and help their business thrive.