Dr. Pfleger – Automatic Analysis of Online Product Reviews for Mail-order Pharmacies

download case study

Challenges

Product ratings, which are perceived as the neutral and independent experience of other consumers, play an increasingly important role in online purchasing decisions. This also applies to pharmaceuticals, which are being bought online with growing tendency. This digital communication provides pharmaceutical manufacturers with important information on their own products as well as competitor products from which they can draw valuable conclusions to increase their product success. Dr. Pfleger Arzneimittel GmbH planned to conduct a central analysis of the top 20 German mail-order pharmacies according to product ratings and was looking for a qualified partner in this endeavor.

Client

Dr. Pfleger Arzneimittel GmbH

Partner

  • Qlik

Technology / Service

  • QlikSense

Topics

  • Qlik Sense

Benefits for the client

  • Gain a significant amount of information through fast, centralized, and easy-to-use proprietary & third-party product analysis
  • Save time with automated data extraction from any public source
  • Increase product performance by uncovering correlations and reacting to them in a target-oriented manner

Solution

Using a programmable Webscraper, fme AG extracted information such as prices, availability, and product ratings for selected pharmaceutical products from the top-selling mail-order pharmacies in Germany on a daily basis. In the process, fme determined the product perception of the comments using modern data science methods such as natural language processing (NLP). The Qlik Sense data analytics platform gives users access to their own product reviews at any time. What’s more, they can effortlessly analyze competitors and identify trends over time. The associative Qlik Engine makes it possible to filter the data according to different dimensions and to analyze specific properties of the selected products. The analysis integrates seamlessly into the existing company design thanks to Qlik’s modern embedded analytics technology.

Technology

  • Qlik Sense Enterprise on Windows
  • Python
  • BeautifulSoup, SpaCy, TextBlob
  • Note: Option of serverless implementation with Azure Functions or AWS Lambda
»Social proof and rating play a central role in product research and customer decisions to purchase products online. The Webscraper from fme automates the data extraction process and combines it with advanced analytics methods to evaluate textual data. This provides us with valuable insights into our own products as well as those of competitors. We are pleased with the results as well as with our collaboration with fme.«
Jochen Meyer - Head of Marketing OTC/OTX & Digital Health
Dr. Pfleger Arzneimittel GmbH
Case Study | Dr. Pfleger – Automatic Analysis of Online Product Reviews for Mail-order Pharmacies

Contact

I’m here to help
Do you have any questions about our services or would you like to request additional information? Please feel free to contact me to find out how we can assist you.

I’m looking forward to your request.

Gudrun Isensee
Sales Manager
g.isensee@fme.de
+49 151 40219695
contact form