How Franchisees Use Predictive Analytics for Site Selection

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How Franchisees Use Predictive Analytics for Site Selection

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In this episode, Lucas and Luna explore how top franchisees are using predictive analytics to choose locations—moving beyond traffic counts and demographics to data models that forecast revenue within 5 percent. They break down a real case: a multi-unit franchisee in the quick-service segment who used machine learning to evaluate 40 potential sites, cutting the search time from 6 months to 6 weeks and boosting average unit volume by 12 percent. They discuss the key data points (foot traffic patterns, competitor density, local income growth, even weather), the software tools available (from Placer.ai to CIVIQ Smartscapes), and the cost-benefit for franchisees with 5 or more units. Lucas explains how predictive models have shifted site selection from 'art and science' to 'science with a dash of art,' and Luna questions whether smaller franchisees can compete without access to expensive data. The conversation includes a donation segment supporting the ad-free podcast at buy me a coffee dot com slash fexingo. #PredictiveAnalytics #SiteSelection #FranchiseLocation #QuickServiceRestaurants #MachineLearning #PlacerAI #CIVIQSmartscapes #FootTraffic #Demographics #MultiUnitFranchisee #RevenueForecasting #BusinessGrowth #DataDriven #FranchiseStrategy #Business #FexingoBusiness #BusinessPodcast #FranchiseConversations Keep every episode free: buymeacoffee.com/fexingo

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