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At R17 Ventures, we understand that the key to sustained success in digital advertising lies in creating compelling, high-performing ads. With the competition heating up and customer preferences constantly evolving, having a solid creative strategy isn’t just smart—it’s essential. That’s why we’ve put together a straightforward creative testing framework to help you fine-tune your content and get the most out of your ads. Our creative testing framework is designed to help you find your winners and maximize your ad performance effectively.
Why Creative Testing Matters
Combat Ad Fatigue: Regularly refreshed content keeps your audience engaged and prevents ad fatigue.
Creative Testing Framework: A Step-By-Step Guide
In this phase, the goal is to find the best of the best winning ad and duplicate it to your scaling (core) campaign. You will combine the top-performing creative and ad copy, and create different variations of the creative to test. Watch the video above to find out more about what your creative kill point should be and what a winner looks like.
The goal in this phase is to find the winning audience segment. Now that you know which creative and ad copy is the top performer, you can test different audiences until you find the winning formula of ads from Phase 2.
As you would probably have noticed by now, keeping track of your tests and results can be a tedious and difficult task. To make your life easier, we're giving you access to our FREE Creative Testing Tracker!
A Bit More On Hypothesis Testing
In the context of creative testing, a hypothesis is a clear, testable statement about how a change in your ad content is expected to impact performance metrics. It’s your educated guess about what will make your ads more effective. A good hypothesis helps you focus your tests, measure success, and make data-driven decisions.
Here’s a simple framework to help you craft hypotheses for your creative tests:
1. Identify the Problem or Opportunity
Start by pinpointing what you want to improve or explore. Are you trying to boost click-through rates, increase engagement, or reduce ad fatigue? Understanding the core issue or goal will guide your hypothesis.
Example: "We suspect that changing the call-to-action (CTA) from 'Learn More' to 'Shop Now' will increase click-through rates."
2. Formulate a Clear, Testable Statement
Your hypothesis should be specific and measurable. It should outline what change you’re making and what outcome you expect. Use the format: "If we [change X], then we expect [outcome Y] because [reason]."
Example: "If we test a new video ad with a more vibrant colour scheme, then we expect an increase in engagement by 15% because brighter colours tend to capture more attention."
3. Define Your Success Metrics
Determine how you’ll measure whether your hypothesis is correct. Specify the metrics and benchmarks you’ll use to evaluate success. This might include metrics like click-through rates, conversion rates, engagement rates, or cost-per-acquisition.
Example: "We will measure success by comparing the CTR of the new CTA against the original CTA. A 10% increase in CTR will be considered a successful result."
4. Consider the Variables
Identify any variables that might affect your test results. This includes both controllable variables (like different ad designs) and uncontrollable ones (like seasonal trends or audience behavior shifts).
Example: "We will control for variables such as audience segment and time of day to ensure that any change in engagement is due to the color scheme, not other factors."
5. Plan for Iteration
A good hypothesis also accounts for future testing. If your initial test proves successful, think about how you can refine or build upon it. If it doesn’t work, consider what adjustments you might make for further testing.
Example: "If the new CTA improves CTR as expected, we will test different variations of the 'Shop Now' CTA to find the most effective wording."
