With the growing complexity of marketing campaigns, and increasing amount of different marketing channels, the accurate measurement of ad spend has become an almost impossible task. In the simpler days, a marketer could run a Facebook ad in minutes and be able to track the messaging, creative, target and spend amount from a basic dashboard. Fast forward to today and marketers are running a combination of ads and sponsored posts across a variety of channels, demographics, ad campaigns and budgets. The changes in ad serving platforms, and the advent of sponsored posts, have created a major disconnect between how paid, earned, and owned media (both impressions and clicks) are tracked and managed. The information and data is no longer in one place, let alone on a single platform.
Let’s face it, there are times when marketers run a single ad across four or five different channels, targeted at three different audiences, optimized around nine keywords, and paid for by two budgets from two different marketing sub teams. It’s enough to make your head hurt from an execution perspective. If the execution isn’t already complicated enough, imagine what you have to go through to pull the metrics you need to measure the ROI across all of those variations and combinations of the ads you’re running individually.
This is what a normal ad campaign today looks like:
Why link ad spend to message level data?
Optimizing Spend is Simple
“Yes, my ad campaigns have gotten a bit complex over the years.” you say. “But why is it such a big deal?” you might ask. Well, this growing complexity in measuring the paid, earned, and owned impressions or clicks you garner from your ads and content not only affect the accuracy of your reporting, but your bottom line as well. Most marketers who run cross channel ad campaigns in multiple regions with multiple targets tend to report on the overall spend without being able to analyze which individual messages, demographics, regions or ads are performing the best.
For example, when we sponsor a post across four channels, in five countries, in two ad campaigns targeted at men and women, our metrics become much more complex and the performance data lives in a number of different places. Not only can we not find the cross channel data in one place, we can’t dive into whether or not ad campaign A, running on Facebook, targeted at men in France between 25 and 35 years old, cost us $3,560 but outperformed all other variations of the ad targeting by 35%. These are the kinds of insight we need to know when optimizing our ad spend across hundreds of different paid campaigns. When all we see is one big number, how can we determine which messages, sponsored posts, creative, keywords, or demographics delivered the most ROI?
Optimizing Messages Becomes Infinitely Easier
With a unified data collection system that can link your ad spend to each individual message or sponsored post, you can determine what messaging and creative works best on each channel, for each target audience, in each region and with what keywords. This gives you, the marketer, the power to determine exactly how much budget is invested into each variation of your ad campaign. Not only can you adjust your spend accordingly, you can customize your messaging based on your audience to maximize the amount of spend you place into each ad variation.
The end result you should look like this:
As I mentioned before, when posting ads on Facebook was simpler, finding out which piece of ad creative performed the best was really quite easy. We opened up our dashboard, found the single ad we were running and compared it to the other paid promotions we were running. That’s how we decided which messages and visuals worked best. Nowadays, the birth of the sponsored post has made this incredibly difficult. The creative and content is no longer linked to the amount of spend we place behind each post we push out. This is especially true if we take the same post and sponsor it across multiple channels and regions. We spend so much time wrangling our spend data from different social networks and ad serving platforms that we barely have time to compare the message level data for optimization.
What can you do with this linked data?
Measurement is king when it comes to the life of a marketer. Simply linking your spend data to your organic and paid ad campaigns can bring new insight to the surface that you and your team may not have been aware of. Here are just a few examples of the kind of queries and metrics you can run with your data properly linked:
Calculating Spend and ROI by Demographic – This may seem simple but you’re not just calculating your ROI by demographic for one or two channels, you’re analyzing the amount you spend on each demographic. With properly linked spend and message level data, you can calculate your ROI by demographics across all channels, all ad campaigns, keywords, and multiple budgets if that is the case.
Calculate ROI between Creative – Again, not only can you precisely determine which individual messages or graphics are generating the best ROI, you can do this across channels, campaigns, regions and any other elements you need to analyze.
Individual Spend on Each Variation – We work with customers who run over a hundred different ads on a single post or piece of content. Not only do they run over a hundred ads, they do this across the globe with varying target audiences and keywords. The most important metric for these customers is the spend to ROI on the individual variations they create. This lets them determine which variations perform the best, which ones are not worth budget and how they can allocate additional fund towards their top performing ads.
How can this be done?
There really is no easy way to manage this on your own. As marketers, we tend to be spread pretty thin in terms of the time you have to spend wrangling and analyzing data. That’s why we created Origami Logic, to automate this level of data collection, cleansing and analysis for you. As you can understand, it isn’t humanly possible to analyze, on a granular level, your hundreds of ads and messages, sponsored across multiple channels, in multiple regions, to dozen of target audiences, in real-time and still have brain power left over to make educated decisions based on the output. This growing spider web of marketing data has become unmanageable by marketers and companies. We’re here to help.