Sometimes it is how you use data that makes a difference. Learn how we helped a top cloud provider build a sales intelligence model that increased sales.
“Trying to manage a complex cloud solution without a proper telemetry infrastructure in place is like trying to walk across a busy highway with blind eyes and deaf ears”. You have little to no idea of where the issues will come from, and no chance to respond to mitigate issues.
Cloud telemetry is essential to make educated decisions on things like cost and efficiency analysis, capacity planning and operational excellence, but how can we leverage it to empower the field?
The telemetry datasets generated by the top public cloud providers are large and well beyond the scale of traditional data warehouses and cubes. But is there a way we can do more with them than simply mitigate issues?
Our client, one of the top three Public Cloud providers, wanted to explore just that. They wanted the data to provide real insights to the sales and field personnel.
- Public cloud telemetry data is extremely large - well beyond the scale of traditional Data Warehouses or Cubes
- No existing algorithms or shorthand to measure these emerging data resources
- Sales force has limited visibility into usage patterns of enterprise customers
- Worked collaboratively with client marketers and data scientists to build and test hypotheses
- Trained the machine learning model across top 100 customers
- Employed modern Massively Parallel Processing (MPP) Data Platform for data aggregation
- Machine learning model that can be re-ran at scale across all accounts
- Cluster analysis can be used to calculate new KPIs that were previously obscured by data scale and complexity
- Field personnel will have a new per-account usage and health metrics to drive sales conversations