Portland Trail Blazers Use Cortana Intelligence to Better Understand Fans, Boost Ticket Sales

This post is co-authored by Ke Huang, Data Scientist, and Tao Wu, Principal Data Scientist Manager, at Microsoft.

To succeed as a business, a professional sports team must know its fans well. From ticket sales to merchandise to concessions, having a great understanding of the fans is critical to all aspects of customer engagement and revenue generation. In the age of big data, sports organizations are discovering the power of the Cortana Intelligence Suite to connect to fans and achieve higher sales.


The Portland Trail Blazers, an NBA franchise known for its passionate fans, is teaming up with Microsoft and using data-driven insights to increase ticket sales. With the big data and advanced analytics capabilities of the Cortana Intelligence Suite, the Trail Blazers are able to better identify leads and significantly increase their marketing efficiency.

A key challenge in this effort is to utilize the Trail Blazers’ diverse datasets to identify potential customers who are more likely to purchase season ticket packages. Most fans do not change their purchasing patterns year over year, which makes it all the more critical to understand customer behavior and identify those who will. With this information, the Trail Blazers can run targeted marketing campaigns resulting in a significantly higher lead conversion rate and increased revenue.

As a fully managed big data and advanced analytics product, Cortana Intelligence makes this end-to-end data experience easy to navigate. It allows data specialists from both our organizations to quickly ingest, process and analyze data and build operational machine learning models. Specifically, Python support in Azure ML allows us to easily incorporate feature engineering into model development and increase our development speed and productivity. The insights gained from the analysis using Cortana Intelligence Suite are useful in optimizing the marketing strategy. For instance:

  • There are significant differences in purchasing patterns among fans, and they are powerful signals in predicting season ticket purchase.
  • Attendance patterns with different opponents are also strong predictors of whether or not a customer is going to be a new season ticket holder.

Microsoft is working closely with the Business Analytics team at Trail Blazers to build several prediction models on the Cortana Intelligence Suite, including one that predicts changes in season ticket package levels through a four-class classifier. The operational ML model uses vital information about fans and home games at Portland’s Moda Center to create sales lead scoring and customized fan engagements. Outputs from this model are integrated into the Trail Blazers’ existing marketing plans.


End-to-end data pipeline using Cortana Analytics Suite and Azure

The Trail Blazers’ solution is realized using a pipeline consisting of three important components on Microsoft Azure: Azure ML, Azure SQL Database, and Azure Storage. The Azure SQL Database component stores various data attributes of customers. Azure ML provides the web services to consume the data stored on Azure SQL Database, extract marketing intelligence and make predictions. Azure Storage compiles large amounts of data during ML training and scoring. The Trail Blazers also use Microsoft Dynamics CRM to manage user data, which proves to be important in prediction accuracy.

By utilizing the analytics capabilities provided by Cortana Intelligence Suite, the Trail Blazers are able to maximize the use of their data assets, optimize their sales and marketing and engage better with their passionate fans.

Ke & Tao