This solution provides the users with a recommendation or a best guess for the product likely to be sold at a store level. Store managers and other target personas (product team) can support their decision making based on this recommender engine. As a result, more informed decisions are expected regarding their respective product portfolios. The user can also take a stock of the most important KPIs of the selected shop.
For running the script in the python node, either have the Anaconda distribution installed or if using a standard python distribution do have:
- latests version of python 2
- pip installed
- Install sklearn, protobuf and pandas library by using pip
EXAMPLES Server: 60_Innovation_Notes/04_Recomendation_Engine_for_Retailers/01_Data_Preparation60_Innovation_Notes/04_Recomendation_Engine_for_Retailers/01_Data_Preparation*
Download a zip-archive
* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually