Marketing Analytics
Strategically plan investments and measure their impact on brand performance
Enhance your marketing strategies and generate the maximum return from each investment
Axtria’s marketing analytics offer
Axtria’s Marketing Analytics offering helps you quantify the effectiveness of marketing investments and provides insights into making the right investment decisions across products, therapeutic areas, and regions. Its AI/ML models run throughout the year and give you opportunities to modify marketing strategies more often and hence optimize your investments. This real-world intelligent modeling empowers even your newest resources to resolve complex business problems efficiently. Axtria’s Marketing Analytics offering lets you analyze the return on investments (ROIs) for each marketing channel and its overall business impact so you can measure success against campaign objectives.
Axtria’s marketing analytics capabilities
Data processing/Integration
Data quality management:
Maintain and improve high-quality data for analysis and business decision-making and automatically generate rules to validate data based on the data types in the pool.
- Visually configure simple or advanced data quality rules
- Consume the outcome through self-service
- Store outcomes as a library asset
Catalog and lineage:
Self-service data discovery allows you to discover the right data sets easily.
- Explore data lineage without IT involvement
- Comprehend and visualize data flow from origin to destination
Analytics workbench
Model library:
Standardized pre-built library of reusable commercial Life Sciences components that can be leveraged across business uses cases.
- Utilize the ready-made library of commercial analytics assets, including multiple modules across broad categories (Marketing Analytics, Sales Analytics, etc.)
- Save time, effort, and resources with reusable business assets when building analytic solutions
Workflow management:
Monitor, optimize, and approve steps in model creation from the application interface.
- Efficiently create, store, and disseminate models
- Reuse and modify past work rapidly to meet current requirements
Data visualization
Data exploration:
The initial stage of data analysis is to understand data configuration and uncover insights.
- Discover and analyze data patterns or anomalies through an interactive interface
- Explore and understand data set variables and their relationship with visualizations
Designing models:
Include architectural model requirements to iterate and generate large modeling scenarios.
- Learn from data patterns and outcomes while you create models
- Leverage the saved models without starting from scratch for future scenarios
Testing models:
Evaluate the performance of testing datasets in the modeling process.
- Hypothesize and test your data with numerous inputs and custom settings
- Achieve the best outcome with each testing iteration
- Select your favorite model for future use cases
Execute modeling:
Implement machine learning programs to reach successful analytical outcomes.
- Run and implement the best scenarios saved during the iterative modeling process
- Reuse the saved models for new brand initiatives
Optimization/Prediction:
Make effective marketing channel predictions that drive brand strategies.
- Enhance sales impact by optimizing your spending tactics
- Choose from the best-guided actions to course correct more often
Personas
Direct Users
- Data Scientist
- Data Engineer
Capability Consumers
- Business Analyst
- Analytics Leader
Customer success stories
Data Analytics-Driven Roster And Alignment Optimization ...
A Biopharma Acquisition: Axtria SalesIQ™ For End-To-End ...
A Sales Strategy Solution For A New Life Sciences’ ...
Resources
Data sheet
Axtria SalesIQTM – Commercial planning and operations platform
Driving a high performance sales team is a real challenge in the life sciences industry. Powerful forces have shifted the landscape, with the purchase and sale of drugs becoming more competitive and centralized.
5 Step Guide
Technology proofing your commercial operations
Case Study
A Sales Strategy Solution For A New Life Sciences’ Product Launch
Case Study