One of the most common pain points I have experienced with clients is this question:
How can we increase the overall number conversions/purchases/leads/subscribers but not increase how much we are paying to acquire these customers?
Logic would tell you that if you want to chase a higher number of conversions, your cost per conversion would raise as well. That doesn’t always have to be the case though. Before you write off what’s possible and what’s not, ask yourself how much of your advertising budget is being efficiently spent. Are you, at all hours of the day, spending your money in the most impactful areas that you can? Most of us do not have the capacity to micro manage every facet of our ad accounts, and therefore are unable to shift budgets in real time. However, there is a tool that can do that for you. It can shift budgets using machine learning to spend money on audiences most likely to convert in real time. That tool is Facebook’s campaign budget optimization and it can help you maximize your ad spend.
So let’s get down to it, I am going to tell you how I was able to increase my conversions by 74% while decreasing my cost per conversion by 43% using campaign budget optimization.
For brevity’s sake, I won’t explain how campaign budget optimization works on a technical level in this article. You can read more on Facebook’s website here.
Campaign Set Up
In order to use campaign budget optimization, you need to toggle the option for it at the campaign level for conversion campaigns. You can do so during campaign creation or on an already built campaign. The tool also features a daily budget or lifetime budget option if you have very specific spend limits. For my case, I used daily budgets.
Ad Set Builds
This is the most important step for getting the most out of campaign budget optimization. It is crucial you set up everything correctly or else you may not see good results. Every ad set needs consistency across settings outside of audiences. Below I will detail some specifics that I used.
Conversion Event: Every ad set within the campaign needs to be optimized for the same conversion event.
Budget & Schedule: For my case, these settings went untouched. I added no min or max spends and had no specific ad scheduling.
Audience: This is the only place where my ad sets differed slightly. I had three audiences within my campaign, each with their own ad set. One lookalike audience, one interest based audience, and one behavior based audience. What is extremely important at this level is reducing audience overlap. That means having proper audience exclusions in place. For this last point, and I can’t stress this enough, do not include remarketing audiences in the same campaign as your prospecting audiences.
Placements: I opted into placements across Facebook, Instagram, Audience Network, and Messenger. Each ad set was opted into the same placements and I let the algorithms decide where to spend the budget per placement.
Optimization & Delivery: I utilized conversions for optimizations with a 7 days click or 1 day view window. I selected lowest cost bid strategy, charged for impression, and standard delivery type.
Ads Set Up
For the most part, you can use whatever creative you have found that works best for you. In my case however, I used a combination of single image ads, carousel ads, and slideshow ads to advertise to my audiences. The important part at this level is making sure that your ads are consistent across ad sets. Each audience should see the same ad(s). That means if I was running a single image ad and a carousel ad for my lookalike audience, then the interest and behavior audiences were being served the same ads during the same time. If your ads differ wildly between audiences it could skew your results.
Measuring Success
To see how effective this tool was, I used a pre campaign budget optimization window and a post campaign budget optimization window to compare metrics. My overall budgets for the campaign never increased or decreased during the test, they just went from ad set budgets to campaign budgets per the tool. Audiences, placements, and optimizations for delivery also remained consistent during the test. So the results? Well as stated earlier in the article I was able to increase my conversions by 74% and decrease the cost per conversion by 43%. When I broke down the spend per ad set pre and post tool use, I found I wasn’t spending enough budget on my best audiences and too much on inefficient ones when trying to budget manually. This account in particular was very large with many campaigns and ad sets. Micro managing ad set budgets manually was extremely time consuming and difficult to keep track of. So not only did campaign budget optimization yield great results, it also cut down on time I had to spend manually budgeting.
Oh and if you want to make sure I am not making up statistics here, you can check out our actual case study that Facebook published on their website. This article was focused on said case study.