Joe Lee, Co-Founder & CEO Few technologies capture the essence of innovation quite like artificial intelligence (AI). Aligned with the digital revolution, numerous retailers are adopting AI as the cornerstone of modern technology. In this rapidly advancing scenario, the debate over whether or not to leverage AI in retail is fast turning the question of “if?” to “when?”
“The retail landscape is changing, and retailers need to figure out how to thrive in today’s volatile market,” begins Joe Lee, Co-Founder & CEO of LocateAI, as he touches upon how retailers strive to leverage AI to grow, set up shops, and enhance product and service cycles in this fast-paced digital era. As AI solidifies its role in automation and augmentation of retail processes, LocateAI, founded by three data scientists from Stanford University, is on a mission to utilize the cutting-edge technology to transform predictive analytics in the commercial real estate industry. With rich expertise in big data, AI, and geospatial analytics, and 70 years of combined experience in real estate and retail operations, LocateAI’s team is uniquely positioned to deliver a blend of science, technology, and real-time information to drive informed business decisions.
In the era of cannibalization, however, making apt business decisions is no cakewalk as retailers are often in the dark regarding the impact a new store will have on their existing stores across multiple locations. What retailers now need is an intuitive revenue model and detailed roadmap to guide them through selling products at different locations, seeking potential franchisees in terms of territory and the number of units required for steady growth. The traditional regression models demand an analyst or statistician tediously testing various attributes/data points correlating with sales models; the methodology involves a limited number of test variables and is prone to human error. Adjusting to cannibalization and re-calibrating revenue models on the fly to overlay business rules and definitions, and driving market routine optimization is precisely what LocateAI delivers best.
We combine traditional and proprietary AI algorithms to innovate retail sales models and real estate solutions for our clients 
LocateAI offers the first ever AI-powered location intelligence platform and machine learning (ML) revenue model for real estate professionals to optimize customer analytics and real estate strategies with comprehensive reports and location-based data points. “We combine traditional and proprietary AI algorithms to innovate retail sales models and real estate solutions for our clients,” says Lee. The company utilizes ML-driven models to eliminate underperforming sites, minimize financial risk, limit inefficient CAPEX deployment, and expand average unit sales volume with efficient data sharing while increasing model accuracy with prompt location and sales updates. As opposed to traditional models’ 5000 iterations with limited attributes, LocateAI’s ML model performs millions of model validation iterations over 160,000 attributes, exhausting “what if” scenarios to provide clients full visibility into their corporate objectives within six weeks.
LocateAI’s ML-driven model simplifies re-calibrating revenue models by centering its decisions on fresh market data, accommodating clients’ new locations and sales data into the portfolio. “We accumulate raw data from our vendors and display it graphically with customer behavior reports by individual locations, roll-ups to the market, and any geographic preference of the client. Typically we recommend our clients to re-calibrate their models on a quarterly basis, which prevents use of stale data sets and outdated models,” Lee adds.
Recently, a rapidly expanding QSR concept required real estate site selection and market planning forecasting solutions to fulfill aggressive development plans with a customizable, simple-to-use, easy-to-understand platform for complex information analysis. LocateAI’s ML-driven model accommodated new locations opened in 2018 and simplified the selection process with detailed ML reports, increasing unit sales volume by 25 percent.
Continuing the innovative streak, LocateAI leads the charge in retail site selection modeling and leverages its ability to process terabytes of data on an ongoing basis to establish itself at the top of the AI summit across the US.
