Digital Lab. Opera North. It’s Raining Stats and Blogs.

Over the past few years, Opera North’s digital advertising budget has increased significantly – from around 6% for autumn 2016 to around 22% for autumn 2019. 

We know our customers live in a multi-channel world, engaging in non-linear interactions across several channels and devices. For our first Digital Lab experiment, we wanted to try and better our own understanding of our growing online audience, the digital journeys they embark on each season, and specifically, the value of each channel on this pathway. 

Here are the first three steps we have taken to realising these ambitions: 

Goals 

To begin to effectively measure the value of each of our digital advertising channels we needed something that could be effectively measured. Therefore, we set up three goals in Google Analytics:

1. ‘Video plays’, 
2. ‘Book Now’ button clicks, and ‘
3. Winter Season’ transactions 

Channel Grouping 

To understand how each of these goals were impacted by each of our digital advertising channels we explored the Channel Grouping function in Google Analytics.  

We found Google Analytics’ default Channel Grouping to be extremely limiting; most of our digital advertising activity (with a medium of ‘cpc’) was being sorted under the one channel: Paid Search. Therefore, we created our own custom Channel Grouping. This allowed us to filter down to the individual digital advertising channels we employed. Below, see a comparison of Google Analytics’ default Channel Groupings and our own custom Channel Groupings: 

Multi-Channel Funnel 

We want to develop our understanding of our customers’ full digital journey’s. Google Analytics by default reports on a ‘Last Click’ basis, and so only attributes a conversion (in our case a goal being achieved) to the last touchpoint a customer has before completing the desired action. But as we know, there are often a range of different channels and touch points that work together to influence and nudge a customer along the conversion pathway which also deserve credit.   

For example, a customer often won't just click on a Facebook advert and immediately make a purchase. They might see the Facebook ad on their feed but not click, then receive an email which they open and read, and then later use a Google search to visit our website and finally make a purchase.

The Multi-Channel Funnel report is very valuable as it allows us to measure just this. We can now see not only the value of each digital advertising channel on our three goals, but also how our channels are interacting together over the course of a customers’ digital journey. 

Note: Currently, we are unaware of a way to apply a custom Channel Grouping to the Multi-Channel Funnel Report in Google Analytics. Therefore, we’re using Google Data Studio to work around this problem, pulling in data from Google Analytics and applying our custom Channel Groupings manually.  

What next?  

Heading into our next season, we anticipate we’ll be using our custom Multi-Channel Funnel report to regularly review our digital advertising activity, measuring the value of each channel on our goals, and developing our understanding of our online audiences.  

In the future, we would like to take this a step further and look at the value of each digital advertising channel for different types of opera, e.g. popular operas, unfamiliar and challenging operas, or concert stagings etc.  

Roll on Experiment two… 

Tom Morris (Marketing Officer) and Lily Ackroyd-Willoughby (Web and Digital Officer), Opera North