Restaurant Market Planning Sotware
Plot Your Growth With Confidence
Whether a franchised restaurant system, corporate-owned, or a hybrid, Borne was built to empower CDOs and Directors of Development for restaurant brands with the intelligence and insights necessary to thrive. Borne MPS is for multiunit restaurant brands and franchise systems looking to grow with machine-learning data informed real estate intelligence.
1
Market Overview
Take a bird’s eye view of any market in the United States to zero in on high potential areas and regions for growth.
2
trade Area
Zoom into custom or predefined trade areas to get down to the neighborhood level including amenities and more.
3
Site Report
When you’ve identified locations of interest, zero into their details with site-specific reports to get the full insight.
Restaurant Concept Data Categories
Categories of data in the Borne System
Borne already touts the nation’s largest restaurant concept dataset, and that would be power enough to grow and scale a multi-unit restaurant brand. But we take it even further and add your brand’s data into the machine-learning models to fully customize the system unlocking powerful insights into competitive analysis, cannibalization reporting, and more.
Traffic
Foot, vehicle and transit traffic forecasting helps identify potential revenue for a restaurant location.
White Space
Where are the opportunities to open a new restaurant location? Where will it reach maximum results?
Social
What are people searching for and what are they talking about? What are the impacts on your brand?
Sales
Forecast potential sales and revenue from various influences in market based on historic and current data.
Historic Trends
See what restaurants have come and gone from national and regional powerhouses to mom-and-pop concepts.
Forecasting
Look ahead at what to expect from various data points to help influence decision-making at the local level.
Customer
Get inside of the behaviors and demographic information on key audience segments.
Competitive
Know who's competing in the area and how prevalent their footprint is. Find the space to compete with unique insights.
01
Explore Markets
Using our dynamic maps, teams can explore the United States* to find geographic areas that are highly ranked for success based on the nuances of concept-specific data, mixed with Borne’s proprietary machine learning system.
Easily toggle your direct competitors and their locations to analyze the landscape’s saturation and reveal potential white space.
Each market reveals study area grades based on Borne’s massive data repository mixed with your brand’s data to create highly accurate grading.
Teams can select up to four total markets empowers teams to evaluate the strengths and challenges of each market with data that’s unique to you brand.
02
Analyze Trade Areas
Borne divides Markets into unique neighborhoods or Trade Areas. At this level, greater detail within the data is revealed opening the door for teams to zero in on a specific area that’s primed for concept success. Trade Areas are a powerful level of data that immediately shows areas of opportunity based on numerous factors within our machine learning software.
Draw your own trade areas based on United States Census borders to home in on neighborhoods of interest.
Within the Trade Area analysis, you can zero in on demographic data, behavioral nuances, and the details of what comprises the Study Area’s grade.
You can easily compare multiple Trade Areas of interest to evaluate the nuances between them helping you identify the optimal area for your brand.
03
Evaluate Site Locations
Once a Trade Area has been identified as a prime opportunity, teams can collaborate with their commercial real estate partners to find specific locations that are available. With those addresses, teams can use Borne’s Market Planning Suite to run site specific reports to realize the power of their own data and the rich repository of restaurant concept data within the Borne System.
Understand how much revenue to expect at a location based on our machine learning and predictive analytics.
Review yearly weather from month-to-month to help understand ideal months and months that have weather-related challenges.
Analyze optimal lease budget based on your concepts revenue potential to ensure you don’t enter into lease-related challenges.
