Traffic study

Analyze pharmacy traffic

Written by Anthony Cabos
Updated over a week ago



Value proposition

The Traffic Forecast sheet is the sheet that allows you to make forecasts about officinal traffic.
This sheet is based on the OpenSource Python library Prophet made by Facebook. The PyTools 5.1 connector was integrated with QLIK to perform this decomposition. The decomposition method used in this library is based on the ARIMA calculation method.
This module is for you if:

  • You want to estimate the impact of an event on pharmacy traffic

  • You want to perform advanced analysis on a market

Data source

Geographic territories

  • Data for Metropolitan France


  • No limitation on market size

  • Applicable on human medicine, veterinary medicine and non-medicinal product





  • Functional cartridge

  • Dispensing/Volume/Volume per dispensing/GTIN per dispensing selector button

  • Dispense Mode Selector Button Additive/Multiplicative Dispensing

  • Learning period selector

  • Time period selector

  • Confidence level slider

  • Prescription type selector

  • Prediction curve

  • Supernumerary accumulation KPIs for volume and dispensations

  • KPIs of average supernumeraries for volume per dispensation and GTINs per dispensation

  • Supernumerary analysis bar chart


  • Quarterly and yearly forecasts do not have enough training data to be sufficiently reliable

  • It is imperative to choose a training period to get a visualization


Adding different temporalities, granularity to the product

Adding KPIs, changing bar chart sorting

First version

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