If you’re looking to make severe reductions in your advertising spend or optimise your overall campaign performance in Australia, you can’t go past Roy Morgan’s Live Audience Evaluation.
Live Audience Evaluation is an analytics platform from Roy Morgan Research, leveraging their Helix Personas segmentation. It allows you to get a definitive representation of how your website visitors and campaign audiences think, make buying decisions and various other psychographic information by tracking which Helix Personas are engaging with your site. The data you get from here can help you do things like optimising out of home advertising campaigns, reduce spend on your direct mail campaign or paid Facebook campaigns and various other paid advertising channels. Basically, it’s humanised Google Analytics.
Live Audience Evaluation currently does not track conversions out of the box, but with a little arithmetic you can work this out.
Without stating the obvious, identifying which Helix Personas are converting will allow you to optimise campaigns and ad spend to achieve a significant percentage in savings.
The reason we have found this so valuable is, although, say, 102 Smart Money may be a clear target audience for your new BMW Test Drive or latest Nike Running Shoe, the 201 Young and Platinums might be the ones actually signing up or physically buying your product.
Live Audience Evaluation has two types of pixels which it can create – campaign pixels (which we will use as the example here) and website pixels. The website pixel will be looked at in a future blog.
So, how do we track a conversion using Live Audience Evaluation?
- First thing you need to do is have (or create) a Campaign pixel. The reason behind this is we are going to create a conversion pixel which is tied back to a specific Campaign pixel. All calculations are based on a unique audience, and the Campaign Pixel will give us that audience.
Note: A conversion pixel is just a pixel purely used to track conversions.
- Following this, we need to create a conversion pixel. As there is no specific section to create a conversion pixel, I create this in the Campaign section of Roy Morgan Audiences and make sure I prepend the name with ‘CP – ‘ (where ‘CP’ = ‘Conversion Pixel’ in my world), which allows me to easily identify all the pixels I have set up for conversions.
- This pixel then needs to fire when a conversion happens. This may be when:
- a form is submitted
- a phone number is clicked
- a product is purchased, or
- another action occurs which is deemed a conversion
Ensure the conversion relates back to the original audience you are creating the conversion pixel for. By this I mean, if it is a BMW X3 Test Drive conversion pixel, then just fire it when someone signs up for the BMW X3 Test Drive. Sometimes this can be implemented easily using Google Tag Manager and other times you may need to get a developer involved.
- What we should have set up now is a Campaign pixel as well as a conversion pixel (in the Campaign Pixel area of Live Audience Evaluation). If this is set up correctly and you are getting daily conversions this should start showing data the next day.
Now you are ready to work out your conversions per persona.
What are we working out?
Before we jump into the numbers, we’ll just put some clarity around why we are calculating it and what to do with what is discovered.
Why are we calculating this?
Numbers can lie when aggregated – if you look at your data as a whole, things may look great or things may look poor but it may just be one thing dragging a campaign down.
For instance, let’s say you had a campaign which only targeted three Helix Personas and $100 was invested in each persona (we’ll ignore CPM and CPC in this case).
If you aggregate this you have spent $300 to achieve 1,700 impressions, 460 clicks and a conversion rate of 1.7% from click to conversion. This isn’t terrible but looking at the 101 Bluechip funnel in isolation it is performing around 30x better (eg 101 Bluechip is converting at 50% whereas overall the conversion rate is 1.7%) regardless of the poor click-through rate.
Having visibility of this conversion data in Live Audience Evaluation allows you to make data-backed marketing decisions on things like ad budget allocation, ad copy and imagery as well as overall campaign targeting.
What to do with our findings?
We want to do one of three things with our findings:
- Stop targeting an audience with a sub-par conversion rate to save money
- Re-allocate budget from a sub-par audience to a higher-performing audience
- Re-work ads to increase click-through rates for audiences with poor click-through rates but high conversion rates.
You could also add to this by re-working website landing pages for audiences with high click-through rate and a low conversion rate with a goal of rapidly increasing conversions, but we just want to focus on targeting for now.
By focusing on these three activities you can gain pretty large savings in ad spend and/or large increases in revenue from your paid media channel.
Firstly, ensure the time period for the Campaign and the Conversion pixel are the same – we need to compare ‘like for like’.
Now, what we need to do is look at the Impressions for the Campaign to get our ‘Initial Audience’. As seen below circled in red the Total Impressions is 276,483.
Once we have our Initial Audience, you then get the Clicks for the Conversion pixel. As seen below, the Total Clicks in this time period is 532.
Now we need to jump over to the Conversion pixel and get the total Impressions (we fire an impression each time a conversion happens). As seen below this number is 240, meaning we had 240 conversions. Just to clarify, this was a niche, timely offering for a free consult for a service-based business, hence the high conversion rate.
From here, Total Click Through Rate = (Clicks / Impressions) * 100, and in our example, this is (532 / 276486) * 100 = 0.19%.
Total Conversion Rate = (Clicks / Impressions on the Conversion Pixel) * 100, and in our example, this is (240/532) * 100 = 45.1%.
Overall, the click-through rate was quite poor, but the conversion rate was amazing.
Now, to check Persona conversion rates, do the same but just take the UA of one persona from the Helix Personas chart of the dashboard.
So, based on the screenshot below, 101 Bluechips and 603 Quiet Homelife looks like this:
Both are at the opposite end of the Helix Personas scale but were identified as our target persona. The landing page clearly didn’t resonate with the 603’s, achieving 0 results, and the 101’s loved it.
Now, say the conversion rate from free consult to a customer was 25%, and the average sale was $2k, this would mean that the 101 Blue Chips achieved $4k in sales and the 603’s $0. If we optimised the budget for the following month, we shift the budget for the 603’s to the 101’s and with no extra outlay make and extra $4k per month.
Likewise crafting a better message so the click-through rate for 101’s increased to 0.8% would also yield a $4k swing in revenue.
We can’t do this with Google AdWords or general Paid Facebook advertising segmentation options as both personas may be 25-34 year olds, from inner city suburbs with similar interests.
This is quite a big difference for only a single campaign, and depending on the budget, this could save you a large amount without reducing conversions. Or, if you are looking to grow revenue, this is an easy insight which tells you where to stick more budget.
If you need assistance in planning a strategy or implementing conversion tracking using Roy Morgan Audiences feel free to contact us or drop by for a chat if you’re in Melbourne.