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Borne

BORNE provides restaurant location intelligence through a machine-learning powered software system that analyzes over 60 data sources to identify optimal real estate opportunities. The platform enables restaurant brands to assess market viability and location feasibility, reducing the risk associated with launching new concepts.

San Francisco, United StatesFounded 2020121K+ followers
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Product

Problem

Restaurant chains face significant risk when expanding, often relying on limited data and intuition to select new locations. Inaccurate market assessments and poor site selection can lead to underperforming stores, wasted capital, and stunted growth.

Solution

Borne provides a restaurant location intelligence platform that leverages machine learning to analyze over 60 data sources, enabling data-driven decisions about real estate opportunities. The platform helps restaurant brands assess market viability, analyze trade areas, and generate detailed location reports to identify optimal sites for expansion. By providing insights into sales and traffic forecasting, competitive profiling, customer segmentation, and potential cannibalization, Borne empowers restaurant leadership to scale with confidence and launch new concepts in locations poised for success. The system offers both market planning software to identify promising areas and a location reporting engine for in-depth analysis of specific sites.

Target Audience

The primary target audience includes Chief Development Officers (CDOs) and development leaders at multi-unit restaurant chains responsible for market planning and real estate site selection.

Features

  • Market planning software to identify viable new markets and trade areas.
  • Location reporting engine providing on-demand analytics covering competition and traffic forecasts.
  • Analysis of over 60 data sources relevant to restaurant performance.
  • Sales and traffic forecasting using a proprietary machine-learning algorithm.
  • Competitive profiling to understand the existing competitive landscape.
  • Customer segmentation analysis to identify areas with the target demographic.
  • Cannibalization analysis to assess the impact of new locations on existing stores.
This profile is AI-generated and may contain inaccuracies.