Introduction
Recently, the team at Rise Marketing Group has done some expert ad testing work for two new clients. We’d like to share with you our processes and their effectiveness. If you are interested in seeing what Rise can do for your advertising campaigns, read below!
Overview of the Testing and Optimization Framework
Our team has been implementing a testing and optimization framework used to increase metrics on ads primarily sent through Meta platforms. With the rising popularity of AI usage for ad campaigns, messaging and creative assets have become crucial for better targeting. Due to this, we have been using a framework with clients just starting out their Meta campaigns that tests copy, headlines, descriptions, calls to action, images, and videos. We initially start with treating primary text as our independent variable and sending out a few campaigns to see which style receives the best metrics.
Testing Methodology and Key Metrics
Our methodologies revolve around going down the list of campaign assets until each one is well optimized for the company’s targeted demographic. We test one variable at a time to accurately assess its performance and know that no other factors influenced its performance. We run traffic campaigns for 24 hour periods to very broad segments. This is typically done with three separate advertisements (A B C). If ad C uses a less wordy text style and pulls better metrics than the other campaigns, we choose that style to take precedent.
Multi-Round Testing Process
The ad testing process begins with an initial phase dedicated to testing primary text variations. The goal here is to identify “losers,” which show little to no potential, “chasers,” which are promising variations that show potential, and “winners,” which are the top-performing primary text options. Losers are instantly thrown out, chasers are reworked to see if they perform better, and winners are compared against each other to find the best options. The winning primary texts from this first phase are then advanced to the second round.
In phase two, the focus shifts to testing various creative assets. Subsequent rounds systematically address other crucial ad components, including headlines, descriptions, and calls to action. The overarching objective of this multi-stage testing is to pinpoint the best-performing elements across all variables. The reasoning behind this is that with so many advertisements utilizing AI for copy and graphics, most campaigns become repetitive and hard for Meta to differentiate. This change in marketing has caused us to get into the nitty gritty of what makes users engage with campaigns. That means stripping down advertisements to their core components and optimizing each one separately rather than as a whole.
Development of Super Ad Variations
Once our preliminary trials have been completed and we know which text, headlines, and creative elements are excelling with customers, we begin to form “super ads”. These are amalgamations of various elements that are data proven to work; super ads are then strategically deployed in conversion campaigns with the ultimate aim of boosting overall conversion rates.
[Client A] Results
We have been implementing this method into campaigns for two separate clients. Client A, a telemedicine company for individuals suffering from sleep apnea, approached us for assistance with their advertising. For their testing, we used our methodology to see if Meta users responded better to ads to address their symptoms, risks, or treatment. Once our data came back and we saw that messaging focusing on symptoms performed best, we implemented this into their campaigns. This led to a significant decrease in cost per lead from around $16 to $6 along with an increase in other KPIs.
[Client B] Results
For client B, a political magazine, although CTRs remained low due to their niche audience and contextual factors like global events, the implementation of new proven assets after testing resulted in a return to conversions during a period of low performance. We noticed that as global events requiring clarification occurred, new users would flock to our ads and client B’s website. Despite this fluctuation in their traffic, we noticed a general increase in their metrics even during times when they typically expected low performance. It was nice to see that this form of ad testing could result in an overall increase in traffic for companies who typically experience dry periods.
Impact and Effectiveness of the Testing Process
This new methodology was prompted by a major dip in conversions we were seeing in our clientele. We noticed that as the digital landscape was changing, our campaigns were slowing down. We quickly developed this new ad testing campaign to stand out amongst those primarily using artificially generated campaigns. As soon as we implemented it and revised our campaigns, we began getting conversions again and at a much steadier pace. This method’s impact reminded us of the importance of adaptability in the marketing field, and how if something isn’t working it isn’t a bad idea to return to the drawing board and revise.
Conclusion and Key Takeaways
Our system of ad testing has adapted significantly to the changing landscape of digital marketing, especially when considering the prevalence of artificial intelligence. As the world changes, so should our methods and we are happy to share this system with your brand and help you stand out among the competition. Contact Rise marketing group today for a free consultation!
