Google Ads Experiments is a feature that allows you to test changes to your account on a portion of the auctions that your ads participate in.
It’s like creating a ‘trial run’ of your campaign to see how potential changes might impact performance.
In simpler terms, you can make changes without completely committing to them. Changes can be as simple as tweaking your ad copy or as significant as restructuring your entire campaign.
Why You Should Use Google Ads Experiments
You might wonder what the value of this ‘try before you buy’ approach is. Fair question. Why go through the extra effort of setting up an experiment when you could just enact the changes and see what happens?
The reason is that when we just make changes and see what happens, we lose a crucial component: control.
Less controlled testing can result in skewed data due to external factors. With Google Ads Experiments, you get a controlled environment where you can isolate specific variables.
The advantages of Google Ads Experiments are numerous – it enables segmented A/B testing, reduces risk associated with changes, allows informed decision-making, and lets you assess impact directly.
What You Can Test With Google Ads Experiments
Almost anything. Yes! You can test changes to bids, new keywords, different ad types, landing page effectiveness, or different ad schedules to name a few.
You can even evaluate how specific demographic audiences interact with your ads.
Here are some specific test ideas:
- Keywords: Try introducing new keywords or remove underperforming ones.
- Bidding Strategies: Experiment with different bidding strategies — for instance, see how cost-per-click (CPC) bidding compares to cost-per-thousand-impressions (CPM) bidding.
- Demographic Targeting: Try targeting different demographic segments.
- Ad Schedule: Test whether changing your ad schedule impacts outcomes.
Step-by-Step Guide to Running Google Ads Experiments
That said, how do you go about running an experiment? Here’s a step-by-step guide:
Step 1: In Google Ads, find your Campaigns page and navigate to the “Drafts & experiments” tab.
Step 2: Hit “+New Draft”, this is where your experiment will be born.
Step 3: Now, name your experiment and set a start and end date.
Step 4: Determine your experiment split. This is the percentage of your budget you want to allocate towards the experiment.
Step 5: Choose your experiment parameters. This could be a change in your bidding strategy, ad options, etc.
Step 6: Save and review your experiment settings.
Step 7: At the set start date, your experiment will automatically run.
And there you have it – your first Google Ads Experiment!
Tips on Running Google Ads Experiments
Experience is the greatest teacher, but here are some tips to get you started:
- Have a Clear Hypothesis: Your experiment should be trying to prove or disprove something specific. Document your hypothesis and the reasoning behind it. This makes it easier to evaluate the outcome.
- Experiment Run Time: It’s essential to run the Experiment long enough to gather sufficient data but not so long that it exhausts your budget unnecessarily.
- Statistical Significance: Expect some fluctuation in performance that is just down to chance. To make more accurate conclusions, ensure your findings are statistically significant.
- One Change at a Time: Multiple changes at once can make it impossible to determine which one caused the effect on your results.
Google Ads Experiments gives you an invaluable ‘try before you commit’ option. It allows you to make data-driven decisions minimizing wasted ad spend and maximizing ROI – and we could all do with more of that!
If you haven’t already tried Experiments in Google Ads, now is the best time. And remember to enter with a strong hypothesis, run experiments for a significant duration, consider statistical significance, and make changes one element at a time.
Try not to get overwhelmed. Google Ads Experiments is an advanced feature, but it’s entirely manageable. As you accrue findings, your hypotheses will become more targeted, and your experiment’s effectiveness will increase.
Good luck and happy experimenting!