In Part One of this blog, we showed the importance of breaking experiential marketing data down into day-to-day detail. Doing this helps identify problem areas as well as best practices. In Part Two, we go into detail about common field staff performance problems and how to find solutions for them.
If you missed Part One, you can find it here.
Estimated reading time: 3 minutes
Averages and Benchmarked Ranges
In Part One of this blog, we used the example of a wine activation event across five states and identified average activation hours per day as well as average consumer interactions. For consumer interactions, New York placed slightly below average but close to the average.
To judge the position of the average, benchmarking reports like PortMA’s adult beverage sampling report are invaluable. Looking at the report, it becomes clear that average activations of 48 per day already place well above the industry average.
Those benchmarking ranges also confirm that the interactions for New York are not problematic. They lie within benchmarked ranges. However, the numbers for North Dakota are low enough to cause concern, and we need to drill down into them even further.
(You can listen to the full episode of the podcast below.)
Identifying Problematic Field Staff Behaviors
To help identify potential staff problems, we can look at further criteria, including:
- Sampling rate as a percentage of consumers engaged
- Samples distributed per consumer
- Samples distributed per day
- Bottles sold per day
In our North Dakota example, we started seeing a pattern by drilling down into the data like that. By doing that, campaign managers could see almost immediately that the data painted a different picture compared to that of other locations.
The sampling rate as a percentage of consumers engaged was lower than in other locations but field staff distributed more samples per customer. Staff are sampling more than everybody else but engaging fewer people. They are also selling fewer bottles than other locations. It looks like oversampling.
Because of the lower sales, it became clear that oversampling was not increasing their sales performance. Another figure to look at would be event attendance. In this case, it is much lower in North Dakota than in other places. Now, the picture becomes clear: staff is oversampling to make their quota despite lower attendance.
How To Improve That Campaign
Managing lower attendance can be tricky. At the same time, having fewer customers to engage with can lead to higher-quality, more immersive engagements driven by longer dwell times. It’s a way of taking advantage of lower traffic. Of course, it’s also worth considering the venue and the market itself. Perhaps different venues or a different market altogether would lead to better campaign performance.
Campaign managers can use benchmarking data to identify problematic areas in their campaigns early and then see how they can support North Dakota. Perhaps it’s time for brainstorming to see what’s happening. Maybe North Carolina has insights to share that will help North Dakota?
Drilling down into day-to-day data allows you to understand the performance of programs and to know where action is needed and where you don’t need to focus on additional action right now.
FOR EXPERIENTIAL MARKETERS
- Experiential Measurement Blueprint
- Event Impression Calculator
- Experiential ROI Benchmarking Reports
- Event Measurement Video Tutorials