If you’re a lead generation company, it can be difficult to understand the impact of your Facebook ads on your other channels.
When reporting to your team, they want to see numbers and the direct results of your Facebook ad campaigns. Yet those numbers are elusive depending on your attribution model and you don’t want to undersell the importance of your Facebook advertising efforts.
That’s why we’ve put together this information to help you understand this attribution conundrum and give you a formula to calculate your own Facebook ad impact.
FACEBOOK AD ATTRIBUTION: LAST-CLICK VS. HALO EFFECT
As a last-click channel, Facebook can be a valuable source of leads. The potential available audience on Facebook for online education, for example, is roughly 2 million people in the US. So, if you get your targeting right, you’ll have a strong pool of candidates to pick from.
But given that online education generally has a long consideration cycle, users may not be ready to fill out a lead form right away: Most people who are serious about their education choose to research and submit their info only after they have done their due diligence.
When this happens, it can make it ambiguous as to whether your Facebook ad may have introduced them to your school or it triggered them to get more serious about applying.
This makes attribution difficult if you only look at last-click leads. A user who took time to consider your school would be attributed to their last channel touch instead of the Facebook ad that may have actually launched them on their decision-making process.
In our experience, the last-click channel in this situation is almost always direct or organic search and Facebook ads contribute to what we call the Halo Effect.
HOW TO CALCULATE YOUR FACEBOOK AD HALO EFFECT
Determining the halo effect will never be an exact science but there are some simple tools we can use to estimate the channel’s added value.
Creating The Graph With Your Data
Here’s how to create a scatterplot that showcases the Halo Effect of your Facebook ads.
(1) From Ads Manager, export monthly Facebook spend, going back as far as your account has been spending.
(2) Pull monthly direct and organic conversions from Google Analytics
- Go to Acquisition > All Traffic > Channels
- Set the Secondary dimension to Time > Month of Year
- Export to CSV, and limit to Direct and Organic Search, and grab the total for each month
(3) Line up Facebook spend and Direct + Organic conversions
(4) Build a scatterplot like the examples below with spend on the X-axis, and direct and organic conversions on the y-axis
Once you have the scatterplot built you can add a trendline and view the relationship between monthly Facebook spend and your Direct or Organic conversions.
How To Analyze Your Data
Generally, the line should be sloping up and to the right, and the slope of that line tells us how much each additional dollar of Facebook spend is worth. The R^2 value tells us how strongly these two variables are correlated.
The higher the R^2 value, the stronger the correlation. An R^2 can vary from 0 to 1.
If the R^2 value were a 1, that would mean that the numbers are perfectly correlated and thus for every dollar spent, you earn an additional lead regardless of how much you spend.
If the R^2 were a 0, that means there is no correlation and an additional dollars spent have no bearing on predicting your leads.
We usually see R^2 range from 0.06 to 0.60 depending on the client. At the lower end of the spectrum, the 0.06 R^2 value means there’s virtually no correlation, while the 0.6 R^2 value indicates a fairly strong but not perfect correlation.
Clients with stronger brand recognition typically have a higher correlation. This makes sense since a Facebook ad from a more recognizable brand will likely be more influential than a lesser known one.
Example for Calculating Facebook Halo Effect
Say that you used that guide above to create your scatter plot of your direct, organic, and Facebook traffic for your EDU named Hazel University.
Using the chart below as the example of the scatter plot created from your data, let’s walk through how you would determine the Facebook Halo Effect.
First, let’s break down the equation of the line (y = 0.0041x + 2815.9). The x in this equation is the Facebook dollars spent and the y is the number of leads. Therefore, if you spent $0 towards Hazel University ads on Facebook, you’d expect 2,816 leads (technically, 2815.9, but obviously you can’t be 0.9 of a lead).
By replacing x with $10,000 in Facebook spend, you can calculate that you’d earn 41 incremental direct and organic leads. That means that for every $10,000 spent, you’d see an additional 41 incremental direct and organic leads each time.
Assuming Hazel University has a $200 CPL for their Facebook last-click leads, that means for each $10,000 in spend, they see 50 click leads, plus the 41 direct and organic leads explained above.
The reason this matters is because while you can easily account for the 50 click leads, without running this analysis you may not know about the 41 direct and organic leads. Since these 41 leads are an 82% increase off of your known click leads for Hazel University, this is a number you want to be aware of so you can attribute them correctly.
Don’t Put All Your Eggs In The Facebook Halo Basket
It may not only be Facebook that drives direct and organic traffic. There are a multitude of external factors that need to be considered such as TV, Display, or other branding ad spend.
In your own analysis, you can always adjust individual months direct and organic leads to remove incremental leads due to other efforts. However, if you’ve been running those branding efforts consistently over a long period of time, then their overall impact won’t affect the ability of this chart to predict your Facebook Ad Halo Effect.
How To Measure Your Facebook Halo Effect Conservatively
To make sure you don’t overstate the impact of your Facebook Ad Halo Effect, you want to measure it conservatively. There’s no scientific method for making your measurements more conservative, so the easiest way to do that here is to cut the incremental leads in half.
Using our example in the chart for Hazel University, that would leave us with 50 click leads and 21 direct and organic leads.
Your final estimate will also be related to the product of your R^2 value. If you see a higher R^2, meaning your numbers are more closely correlated, you may not have to discount as much. If you have a lower R^2 value, you’ll want to be more conservative since your numbers are less closely correlated. Remember, the more correlated the numbers, the stronger the relationship between your Facebook ads and their effect on direct and organic leads.
Attribution cannot be determined with 100% accuracy. However, to make sure you’re putting the right amount of spend into your Facebook ad campaigns, you want to able to calculate their impact as precisely as possible.
By using the formulas and reports above, you can gain a broader understanding of the true impact of your Facebook ads on the rest of your marketing efforts, even if they aren’t the last-click channel for your customers.