Comprehensive data connection for dynamic pricing
Initial
situation
Our client, Klingel Mail Order, wanted to automate their pricing process with an external machine learning system for dynamic pricing, based on product life cycle and stock numbers. The main challenge lay in the dispersion of critical data across various sources, and the efforts to establish the necessary data connections had been going on for almost two years.
Recognising the urgency as a final deadline loomed, our client entrusted us with this task and the responsibility of leading it to success.
DURATION
June 2022 – August 2022
TEAM
2 Developers
1 Team & Product Coach
INDUSTRY
E-commerce
Fashion & lifestyle
SCOPE
- Requirements engineering
- Project management
- Data engineering
- Test-driven SQL development
Our
approach
Evaluate assumptions early.
We initiated the project with a comprehensive two-week analysis of the requirements and diverse data sources, which laid the foundation for a well-structured plan. Our dedicated team then crafted a pragmatic proof of concept, enabling early testing and evaluation by users. Remarkably, this initial MVP performed so impressively that only minor refinements were required in subsequent stages.
Solution &
results
Cost savings through automation.
Our software solution not only achieved a high degree of automation, but was also implemented with very low operational costs and delivered substantial monthly cost savings amounting to a six-figure sum.
Technologies used
Amazon Athena
Akka
AWS Lambda
Kubernetes
AWS
Terraform
