Robust customer segmentation and attribute derivation to take your understanding of known customer lifecycle data points to new levels
Secure and easy integration with source systems and/or existing data infrastructures to reduce executional risk and accelerate time to value
Machine Learning powered Retention and Prospect scoring which leverage behavioral and
interest data points
Add transparency to sales and marketing activities with cohort performance analyzers so you always know what’s working
Portland Trail Blazers
The Blazers were selected to finish 30 out of 30 NBA teams by ESPN and the NBA's internal retention model projected an 85% season ticket holder renewal rate (well under the team's historic average). With StellarAlgo's leadership and imbedded Retention Module, the Franchise worked to exceed league projections and return their most loyal fans.
Using the past three seasons of ticketing CRM and Marketing Automation data the Blazers and StellarAlgo partnered on an advanced scoring and prioritization methodology to maximize fan retention.
With StellarAlgo leveraging an automated data feed, we were able to score and prioritize fans from day one of the season, right through renewal.
In addition, as the Franchise launched retention and service efforts to engage fence-sitters, StellarAlgo was able to monitor the impact of those touchpoint and re-prioritize the fence-sitter pool.
The automated and imbedded retention module resulted in a full season long retention campaign that increased renewal from a forecasted 85% to 95%.