HISTORY: Ticketmaster is the leading ticketing agency in Australia, who along with Ticketek in 2005 controlled 90% of tickets sold.

This is the story of analysis I performed within the company ..


MISSION: While I was employed as a Client Marketing Manager, I also performed all marketing analysis. As the internet/ email campaigns were the most efficient and provided the best margins I concentrated on analysis of their sales data.

  • I analysed Ticketmaster’s first online survey, which had over 30,000 respondents. When answers were correlated and graphed on a 3D matrix it became clear which of the three distribution points (internet, phone, ticket box) required what actions.
  • Analysis was performed on six months of sales data on the websites three ticket purchase portals: Highlight (main central image), Spotlights (six smaller images) and the ‘Latest News’ and ‘Hot Tickets’ (text menu bar)
  • From my reports, the event managers were able to negotiate the most effiicnet use of advertising space to maximise sales.

Mapping scoping project 

The demographics of the highest advance ticket sales suburbs for the Grand Prix were baselined with demographics for the average Greater Metro area.

One potential application of such a study is to feed into targeted campaigns at suburb level in such promotion tools as local newspapers (including non-English specialty papers), direct mail or local signage (such as bus shelters etc). Any suburb demographic information that varies significantly to the average ‘Greater Melbourne’ values can be anlysed further.

For instance, consider that the 2005 Grand Prix F1 Grandstand sales were highest in suburb X, and census statics suggest that this suburb has a higher than average number of white collar high income earners predominantly from English speaking ancestry (at least second generation Australian, UK / Irish ancestry). This information could dramatically assist the client in creating a targeted local campaign that would more efficiently reach this specific consumer group.


Many companies have a mass of data locked up in their Sales data. The key to unlocking this data and turning it into useful campaigns is sometimes knowing what the key success factors are in other industries and efficiently using that knowledge.