EQ launches Clearlake for Real Estate

Executive Summary

• EQ Inc. has launched "Clearlake for Real Estate," a new AI-powered predictive platform designed to assist companies with real estate site selection and network optimization.
• The company secured a multi-year agreement with one of Canada's leading quick-serve-restaurant (QSR) organizations, marking the initial engagement for the new platform.
• The contract covers five of the QSR organization's largest national brands, representing over 1,000 locations across Canada, to evaluate new market opportunities and optimize existing networks.

Key Details

• Product Launch: Introduction of "Clearlake for Real Estate," a predictive model leveraging proprietary data capabilities.
• Client Engagement: Multi-year deal with a leading Canadian QSR organization.
• Scope of Deal: Initial engagement includes five national dining brands.
• Scale: The brands represent over 1,000 locations across Canada.
• Platform Capabilities:
  • Integrates customer first-party data, geospatial and movement intelligence, transactional insights, and demographic/census data.
  • Uses advanced AI-driven modeling to forecast performance potential, estimated revenue opportunities, competitive pressures, and cannibalization risks.
  • Claims to enable decision-making three to four times faster than traditional processes with higher confidence.
• Use Case: The platform will be used to evaluate new market opportunities and areas for improved network optimization for the client.

Notable Quotes

• "This contract with one of Canada's most respected QSR organizations is a powerful validation of our decision to incorporate our data into the real estate sector," said Mark Ditkofsky, chief operating officer at EQ Works. "QSR brands face significant capital risk when choosing new locations. Every decision has a direct material impact on revenue and profitability, which is why by incorporating our powerful data sets into one predictive platform, we are helping our clients make location decisions with confidence and through data-backed analysis."