Effect of Deep Predictor Implementation: Prediction of Customer Visits
Forecast the number of customers considering weather and event information. Eliminate waste in shifts and inventory, and improve store profit margins.
One of the challenges that our no-code AI predictive analytics service "Deep Predictor" addresses is the "forecasting of customer foot traffic." By utilizing AI to collect data on past customer visits, weather information, holidays, and other external factors, we model historical patterns. This allows us to make accurate predictions of customer numbers that account for the complexity and variability of the data. Using AI to predict customer foot traffic enhances competitiveness in business and contributes to improved efficiency and customer satisfaction. 【Required Data】 ■ External Factors - Information on how external factors such as weather data, holiday calendars, and local event schedules impact customer numbers. ■ Competitor Information - Sales data and event information from nearby competitors. *For more details, please download the PDF or feel free to contact us.
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Our company actively engages in technological innovation and creates efficient communication infrastructure based on predictive models utilizing machine learning, thereby generating new value in communication.