Microsoft Marketing Optimization

With thousands of marketing campaigns performed across the world each year, with varying tactics and metrics, executed by a variety of suppliers and internal teams, the Microsoft Azure marketing team needed to gain a more precise understanding of its activities’ impact on revenue. 

On top of this, any individual prospect could be ‘touched’ by the Azure sales and marketing teams literally hundreds of times before making a purchase.  

Azure needed Calligo’s help in untangling this enormous puzzle of data volume, variety and quality.

We saw they needed to go one step further than viewing each campaign in isolation. They needed to pinpoint which combination of different types of marketing activities was the most powerful and delivered the greatest opportunity soonest.

Our team worked with Microsoft to create an unusual data science initiative that prioritised commercial impact instead of focusing on the traditional machine learning metric of mathematical accuracy.

Our model optimisation didn’t focus on gaining fractions of a percent in accuracy, but on making sure that the model was intelligently selecting the most commercially-indicative criteria to base its findings on. In other words, Calligo used an ROI-focused application of data science.

Once Calligo and Microsoft had discovered the winning combinations of marketing activities, including the early indicators of success and metrics for these campaigns, these needed to be communicated to the team and translated into a framework of action.

Ultimately, Calligo and the Microsoft analytics team were able to inform: 

• The combination of marketing activities most likely to impact ACR the most and soonest. 
• Metrics and expectations for each type of campaign. 
• Function-specific objectives that feed into each campaign’s success. 

Individual-level objectives for each team member’s contribution to the campaign.