To understand the consumer behaviour and choices for different products across different categories and regions
Develop a digital innovative solution for the enterprise of tomorrow. An intelligent analytics platform to have a better strategic vision and alliance across different geographical teams and regions. Empower the business with predictive capability based on the past behavior to fasten the decision making for future. Enhance the collaboration between different teams with the help of intelligent technology systems to drive revenue growth.
- A robust and highly resilient data framework is created to extract, transform, load & seed the data into the database using niche capabilities, as the tool’s success depends on the quality of data input and the analysis performed.
- Intelligent data categorization to run tests seamlessly, extract results and reports used in decision-making.
- The tool has built-in intelligence to ensure workflows and processes are performed exactly as designed with meaningful error explanations to help the users.
- Intuitive UI design to aid smooth user experience.
- The features of the tool are access controlled with multiple check-points to ensure right people have the right level of access via AD groups.
Highly scalable and configurable system to support the ways of working while ensuring 100% uptime.
AT A GLANCE
- Performance optimization
- Data quality and modeling
- Minimize the cost of operation
- Data management
- Build Intelligence into the tool
- MVP delivered in 5 weeks
- 30% Performance optimization
- Seamless user interaction
- Completion on-time in budget
- Savings worth 30K Euros annually
- Django / Rest framework
- Market Analysis
Market insights are generated in 15-30 minutes as compared to 4-5 hours. this allows the team to make real time decisions.
- Al Powered Analytics
A 40% boost in productivity for the team, streamlined ways of working bringing in IFTE worth savings weekly.
Digitization brings in saving worth 30K Euros from tools annually while increasing the future-fit score by 7%.