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When your goal is a long-term, successful PPC campaign that brings you a steady stream of qualified leads, you need to run A/B continuously.
Also known as split testing in digital marketing, this is the only reliable way to determine which variables contribute to higher conversions and profits.
Once you pinpoint the profitable ad variations, you can implement them across all of your campaigns for the best results.
In general, the idea is to run two or more simultaneous Google Ads campaigns that differ in small ways, both in your ad and your landing pages. You start with a main campaign as your control, and then create additional ads and landing pages with slight differences to see how well they perform against each other.
After a period of time, you’ll know which ads and landing pages perform the best. From there, you can analyze which variables are present on your high-performing ads and pages, apply them to all of your campaigns, and then start testing other elements to get even better results.
For example, you might run five campaigns with the same ad, but users are redirected to five different landing pages, each with a unique heading. Or, your landing pages might have a different format, colors, or typography. You can test any element, no matter how small, and sometimes it’s the small things that count most.
If you’re curious about split testing your PPC ads, this article will help you understand how this process works and how to apply it in your campaigns.
You can run an A/B test for just about any element you can alter in your Google Ads campaign. For example, it’s common for people to test the following:
There are two main elements that power A/B testing: time and structure. Let’s look at each of these in-depth.
Running digital marketing A/B tests is easy, but you need to set it up to extract actionable insights, and that’s where things can get a little challenging. If you follow these tips, you’ll have an easier time.
Your control campaign is the original, unaltered version. Always keep your control running alongside additional campaigns with changes. After your tests, when you find your highest performing campaign, that should become your new control to replace the old. From there, you’ll aim to beat your control once more by testing new elements.
Repeat this process indefinitely, and always remember to maintain your control so you can see what elements are performing better against your existing standard.
The first thing to remember is not to attempt to test too many variables at once. Testing multiple things at once will make it hard to know which change is responsible for an increase or decrease in conversions. Stick to testing a single variable until you’re satisfied with those results and then start testing the next element.
When running a test, you’ll need ample time to generate enough traffic, clicks, and sales to see what’s working between each version being tested. You won’t get results overnight or even in a week. Your A/B tests need to run long enough to create statistical significance in the results.
The suggested time period is however long it takes to reach 10,000 sessions, also known as the “10,000 experiments rule.” This is an alternative version of the concept that it takes 10,000 hours to become proficient in a given skill. The idea behind this is that deliberate experimentation is more valuable than deliberate practice. It’s true – if you don’t experiment deliberately, you won’t get the data you need to see what’s working in your PPC campaigns. However, 10,000 experiments (or 10,000 interactions) can seem like a bit much for smaller businesses.
Reaching this goal could take months for many organizations that don’t have a massive PPC budget. However, if this applies to you, set a goal to reach 1,000 sessions or put a cap on your tests at the 60-day mark. Either way, just wait until you have a decent amount of data to work with even if you don’t reach that 10,000 mark.
Running split tests without specified goals isn’t going to help you. It’s crucial to know exactly what you want to get out of your tests. For example, everyone wants more leads, but what does that look like beyond the surface? Would you feel like you achieved your goal if you got 500 new leads that never make a purchase? Or do you only consider it a success if you generate targeted leads that at least have the potential to buy in the future?
Getting targeted leads is just one example of a specific goal. You may want leads who will sign up for your email list and then watch a video or follow you on Instagram. For long-term success, you’ll want to align your A/B tests with your goals, otherwise you could spend years testing the wrong elements – the ones that don’t directly influence the actions you’re trying to elicit.
To get actionable insight from your tests, you’ll want to identify the metrics that denote success or failure other than just the number of leads you collect. These might include:
To make improvements, you have to know how your experiments are performing.
Figuring out if your tests are successful requires some serious data analytics. You’ll need to analyze a handful of metrics to see how people are reacting to the changes you’ve made and you can accomplish this with a visual form of behavioral analytics. According to Investopedia, behavioral analytics can support a number of different hypotheses at once, and makes it easier to evaluate your experiments.
When you have a visual data report of your tests, it’s easier to understand which elements are supporting your goals and if a certain version is good enough to apply to all of your campaigns and/or become your new control.
Also called session replays, this is where a user’s actions are recorded as they interact with your website. Mouse movements, clicks and taps, and scrolling are the most common actions recorded.
Implementing session recordings into your split tests can help you improve your PPC ad campaigns immensely. Not only will you have data, but you’ll have a real-time account of how users interacted with your page, which will give you some specifics you can’t get any other way. For instance, a user might start to fill out a contact form and then stop at a certain question. Or, they might abandon the checkout process at a certain stage and their mouse clicks might tell you why.
Session replays are an excellent way to improve your conversion rate, and when paired with A/B testing, they’re even more powerful.
Heatmaps can provide you with valuable insight into which parts of your web pages are performing well (or not). These maps will show you where your visitors are focusing most of their attention, where they’re clicking, if and how long they’re scrolling, and what might be distracting them from taking the desired action.
For example, a scrolling heatmap can tell you if users even saw your CTA. Perhaps many don’t scroll down far enough, and you’ll need to move the CTA higher up on the page. If you don’t use a heatmap, you won’t know that many of your visitors never even saw your CTA. All you’ll know is that you didn’t get clicks. This could lead in circles, causing you to test different CTAs, when your original one might be just fine when made more visible.
Sometimes, it’s your traffic source that supports a more successful Google Ads PPC campaign. Make sure you’re tracking where your visitors come from so you can determine which traffic sources lead to higher conversion rates. You might find some sources to be complete duds, and that means you’re either targeting the wrong audience within that PPC platform or the platform itself isn’t where your market spends time.
Many businesses run PPC ads on every platform they can find, like Instagram, Facebook, Twitter, LinkedIn, and Google Ads. However, some markets rarely (or never) spend time on certain platforms. For example, if you’re trying to reach a highly technical and scientific-minded market, you probably won’t reach many people on Instagram. Sure, there are plenty of science-related accounts, but they’re not usually scholarly. It just doesn’t attract that type of market. Instagram is more for entertainment and visual appeal than sharing scientific research, discoveries, and theories.
If you discover that some of your traffic sources aren’t producing conversions, reconsider if you’re on the right platform. If you think you are, then start adjusting your target audience. If that doesn’t generate more leads, consider abandoning the platform because it’s not worth wasting ad spend where you aren’t getting results.
A/B testing is a crucial component in your Google Ads PPC lead generating campaign. The key is to define your paid search goals before setting up your experiments, and only test one change at a time.
Be willing to wait for statistically significant results so that you can know for sure that you’re making the right changes. Keep your control clean and consistent but replace it when you find a new ad or landing page that consistently achieves a higher conversion rate.
Last, don’t stop split testing when you get your first taste of success because there’s always room for improvement and you can always do better. You’ll need to adjust your goals and hypotheses over time, but that’s just part of the process. Split testing should be a continuous endeavor and if you get stuck, you can always reach out to a professional PPC marketing company.
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