Oh television. Sometimes I forget it even exists. The number of times I’ve watched something on an actual TV in the last year is probably lower than the number of kids I have (4 kids, to give you perspective). We do watch screens – but it’s all iPad or iMac based viewing.
So, when a digitally obsessed person like me thinks about TV ads there’s a tendency to think they are irrelevant. Not so. And I should know better. In reality, I have to remember that TV (broadcast, cable, and streaming forms) is still a very powerful advertising medium. That doesn’t mean its for everyone or that money isn’t wasted there. But then again, spending advertising dollars online doesn’t mean you’re immune from bad marketing investments.
What matters is measuring it. Know, don’t just hope. But how can you measure the digital impact of a TV ad? It’s hard, but not impossible.
I’ll demonstrate with an example and a couple key tools.
First up: you need a good case
An ad blitz that will create enough of a splash to create some waves in the sea of digital analytics data. Enter example: a really big sporting event? I dare not say the name I’m told… but you get the point.
Second: you need clean, clear data
If you throw a big rock into a raging rapids you’re not going to see the waves it makes. If you throw a pebble into a clear, calm pond, you’ll see every ripple. Enter example: Google Analytics Premium. For all you skeptics out there wondering why a paid-for version of GA is worth it, go look at your data. Is it the clear calm pond or the ranging rapids? The value of Premium rests mainly in the overall solution it brings – a hybrid of more capacity and capabilities along with insane service levels providing strategic guidance, implementation, training, support and account management to tie it all together.
I’ll stop before this turns into too much of a “go premium” commercial, but seriously, this is really important. Clean data = potential for insights. Messy data = few or no insights. No insights = no value. It doesn’t matter what your investment is unless the “R” is there in the ROI equation. If the “I” is $0 with a free tool and you get a Return, awesome. If the “I” is six or seven figures and the “R” is double or triple-digit percentages, is it worth it?
Third: you need an analysis tool that is awesome
By awesome I mean able to help pick what’s important out of the data. Even with a powerful tool and that pristine data, you still need to analyze what matters to the question at hand. Finding the ripples in the pond, to go with the analogy above, is hard. Enter the right tool for this job – something that can visualize multiple dimensions of data over time. And it exists right within Google Analytics.
It’s called Motion Charts. This feature was introduced all the way back in 2007 if my memory serves me correctly. Yet it receives little attention and I’m sure far less usage than it deserves. I’ll even say that I am guilty of not using it enough! But analyzing a TV ad is a great case for this.
Using a Motion Chart to analyze TV ad data
The video below provides a screencast of using the motion charts tool to analyze multiple dimensions of data over time. We’re looking at data based on the top Market Areas where the ad aired and the date range surrounding the ad run. The analysis process involves:
- Formulate question: in this case “did the ad work? Did it reach the intended audience and increase brand awareness and drive any response?” Also good to ask is “where some markets more impacted than others?”
- Determine your data: simple volume-based metrics like Visits by Market by Day are a good starting point, but absolute numbers can often hide more meaningful trends and patterns. Peeling back the layers of data to ratios will surface much more meaningful insights. So, in this case, I use Visits by Market and Day to get a baseline perspective, and then use % New Visits by Market by Day to see if any markets saw a higher response from new visitors. The implications of this data are many: prior market awareness, audience fit, interest level in the product, to name a few.
- Run the numbers. After determining your questions and data to use, run the numbers. Watch the video below to see how I did this.
Screencast Example of Motion Charts in Action
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This example shows the power of data visualization with a multi-dimensional data set. When you have a set of good input data you can often find interesting and meaningful trends and insights in it. Starting with defining your questions and then the data that will best answer them will set you up for success in analysis.
So, go check out the Motion Charts tool in your own Google Analytics account, dive into your data, and share some comments on the experience and insights!
Thanks for reading.