Manufacturers need punctual delivery of their goods and a successful placement of their promotional products on the sales floor. In order to offer companies a more efficient, effective and cost-effective way of carrying out promotions CHEP has created a new service in collaboration with Deutsche Telekom as its technology partner. The service is based around a long life low-cost-tracker of which the basis has been developed by Deutsche Telekom.
It can track the correct placement, location and condition of the product on the sales floor. To design the software used in the tracker, Deutsche Telekom has used the Data Intelligence Hub and leveraged its expertise and capabilities in the fields of data science, machine learning and artificial intelligence.
To develop the machine learning model that is used in the low-cost-tracker a range of different tools were utilized that are part of the Data Intelligence Hub (platform).
Databricks, Databricks’ MLflow and JupyterHub were important tools used in the design and implementation of the Machine Learning Model.
This model gives companies the ability to track promotional activities along the entire life cycle, optimally use sales potential by understanding the time spent on the sales floor and give detailed insights for the evaluation of campaign success and more reliable forecasting of order quantities.
Companies now have the tools to
- Precisely time digital campaigns
- Get valuable insight that allows to easily differentiate promotional activities based on different regions to better target separate audiences
- Improve sales potential by understanding the time spent on the sales floor and the customer traffic going inside the store and next to the product
The Data Intelligence Hub is ideally suited to manage such complex problems and to filter the important trends from your company’s data and use them profitably. With its flexibility and the wide range of analytical tools and data providers, the Data Intelligence Hub brings the resources your business needs to make better, more profitable decisions.
Acknowledgement: This article was written with support of Sean Bäker during his time as a dual student within the Telekom Data Intelligence Hub.