Addressing Declining Game Attendance
It’s not a shock to those in the industry that game attendance has been at a steady decline. With many ways to enjoy game days, consumers are spreading themselves across multiple mediums and locations. At Jurich however, we believe that adding statistics and multiple touchpoints will encourage the crowds to return. Our solution is three fold:
- Overall scanned attendance per game
- Individual STH scan rate per game, which games did they attend or not attend
- RPI (rank) and record for each team played – our RPI (rank) and record at the time of the game
- Game time, date, and day of the week
- Was the game televised – if so, what network
- Conflicting local events
Comparative Analysis & Regression Modeling On Found Data
Using this data set we will do a comparative analysis and regression model to identify what variables are highly related. Based on these findings, we can create a predictive model to forecast attendance for future games. With the knowledge gained from the predictive model, you will be able to anticipate attendance, as well as what seats will likely be open.
Influence High-Risk Accounts With Geo-Framing & IP Targeting
Using Geo-Framing technology, we are able to identify the digital footprint of specific high-risk accounts and season ticket holders. Our system is able to identify their Device ID’s home address and then use it as an entry point for advertising. This influence can be in the fashion of IP Targeting technology, mobile targeting or even direct mail.