Version:

v2011121053

Preview:

Value

Because the evolution of pharmacy traffic is symptomatic of specific health contexts, it is important to analyze these indicators as factors exogenous to your commercial performance:

  • Number of working days
  • Number of pharmacy tickets, all products combined
  • Number of items (volume) per ticket
  • On and / or off prescription
  • The area where pharmacies are located and their turnover

This module is for you if:

  • You want to better understand the exogenous factors in pharmacies
  • Create pro forma analyzes of your performance, excluding traffic trends and number of working days

Data sources

  • Data from pharmacies.

Geographic territories

  • Metropolitan France data excluding Corsica & DROM-COM

Market

  • Market definition 'all products' exclusively
  • Applicable to human medicinal products, veterinary medicinal products and non-medicinal products

Status

Objects found in the sheet

  • Functional cartridge
  • Time buttons
  • Measurement selector
  • Prescription selector
  • Geographic granularity selector
  • Analysis type selector
  • Filter of the type of days (possible exclusion of public holidays and Sundays)
  • Bar chart 'N / N-1 / Pharmacy CA'
  • Bar graph 'N / N-1 / Zone Pharamcy'
  • Table object 'Analysis of days, traffic and average basket'
  • KPI Measure N and N evol

Indicators

  • Total number of (working) days
  • Number of dispensations (traffic)
  • Number of dispensations / working days
  • Volume / dispensations
  • Volume
  • Volume / working days

Temporalities

The temporalities of this sheet must be taken into account in relation to the defined deadline.

Type of analysis period available:

  • Month (Mth)
  • Qtr (Quarter)
  • YTD (Year To Date)
  • MAT (Mooving Annual Total)

Versions

Current version:

Pharmacy Monitoring Details v2011121053

  • Change of the bar chart to adapt to the change in sectorization

Previous versions:

Monitoring target Details" v2007171423

  • Creation of the sheet

Limitations

We cannot do an analysis by crossing geographic data and the type of sign.

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