SAS helps you to quickly respond when a customer says, "I'm not happy. My bill is too high, and I know I can get a better deal elsewhere. What can you do about it?"
We enable you to be prepared with an optimal offer in advance of this customer interaction.
Optimized data management based on industry standards.
SAS® Offer Optimization for Communications uses a customer-centric foundation data model (FDM) aligned with the TMForum Information Framework (SID), the most widely adopted industry standard data model. It uses data from billing, customer relationship management, order management and activity-based management. Flexible architecture helps ensure seamless integration with all these systems to extract the required data and information.
Precision in best-offer calculation.
A guided workflow allows you to select the target customers and then create meaningful offers using product catalogs and past invoices from billing systems. SAS Analytics help identify the best offers for targeted customers.
Resources maximized in the customer contact center.
Contact center staff members are able to get customers onto the right plan in less time. More accurate data is provided to all customer touch points. Prebuilt reports mean your staff spends less time gathering and presenting data from multiple systems.
Efficiency in designing, testing and performing best-offer calculations.
SAS Offer Optimization for Communications functions in two modes – design and production. Design mode enables a business analyst to efficiently configure and test the environment using sample data pulled from the FDM. Once satisfied, the configuration is saved and run against the entire customer base (production mode).
Ability to change direction in response to market conditions.
At each stage of the process, SAS Offer Optimization for Communications supports the business reporting features. These reports help decision makers to quickly strategize their business goals and take appropriate actions.
- Optimized data management
- Support for all price plans
- Use of existing analytical models
- Efficient design process
- Prebuilt reports and OLAP cubes
- Automated workflow