A Beginner’s Guide to Cross-Channel Advertising
Cross-channel marketing is about meeting your target audience with ads, content, and experiences that feel natural and intuitive to the consumer. Here's a guide to get you started.
In today's digital landscape, the cost per thousand (CPM) metric is crucial for businesses eager to maximize their return on advertising spend (ROAS). If your CPM is low, you can reach a larger audience at a lower cost. This presents an excellent opportunity to experiment with brand awareness campaigns and test the effectiveness of your marketing efforts. However, running tests and interpreting the results can be challenging, especially when dealing with multiple channels.
Before you start, here are some practical tips on running effective tests and reading the results across various channels to help you make informed decisions for your brand.
Cross-channel A/B testing is a technique that involves evaluating the effectiveness of two or more versions of a marketing campaign across multiple channels, such as email, social media, and paid search, to determine which performs better. Collecting and analyzing results from A/B tests allows you to make data-driven decisions about optimizing your business’ campaigns and user experiences to drive better results.
Cross-channel A/B testing has become a widespread and valuable practice for businesses looking to improve their conversion rates. In fact, a staggering 71% of companies working to optimize their websites are now conducting two or more A/B tests per month, indicating the growing importance of this method. Additionally, 60% of these companies believe that A/B testing is "highly valuable" for conversion rate optimization. This is because A/B testing allows businesses to test and compare different versions of their website or app to see which performs better in achieving their desired goal, such as increasing sign-ups or purchases. By identifying the most effective design, copy or user experience elements, companies can make data-driven decisions that improve their conversion rates and ultimately drive more revenue.
For example, a US-based streaming entertainment company increased viewership for individual titles by 20-30% after implementing an A/B test strategy to select the titles' cover images. Another company found success with cross-channel A/B testing by experimenting with color. The company experimented with over 40 shades of blue for its page’s ad links to find its consumers’ favorite, leading to a $200 million ad revenue increase.
Follow these steps to ensure you’re running an effective cross-channel A/B test:
Before running a cross-channel A/B test, it’s essential to define clear goals to ensure the test is focused and actionable. Without a clear purpose, it can be easy to get caught up in testing for testing's sake, wasting time and resources. One key consideration is to avoid testing irrelevant features. Instead, focus on components relevant to the business goals that you expect to impact your metrics significantly. Speaking of metrics, these also need to align with your goals. Select key metrics that are meaningful success indicators, reflecting the outcomes you want to achieve. By aligning your metrics with your goals, you can ensure you're measuring the right things and making decisions based on relevant data.
When you clearly understand what you're trying to achieve, you can more easily evaluate the results of your tests and determine whether they have been successful. This can help you make informed decisions about which changes to implement and which channels to prioritize, ultimately leading to better outcomes for your business. For example, you may want to improve your website's conversion rates, landing page or other digital assets. Perhaps you're looking to enhance user engagement and want to focus on metrics such as the amount of time users spend on your site, page views or click-through rates. Are you interested in upgrading your product marketing strategies? Use A/B testing to experiment with different variations of product features, such as pricing, packaging or functionality.
Companies executing diverse channel mix marketing strategies must remember that characteristics vary channel by channel, impacting the outcomes they drive. Focus your testing efforts on the channels that drive the most traffic or revenue, for example, and prioritize improvements that will impact your business the most. Channels also have different limitations and audiences. For example, some channels may have limited targeting options, while others may have strict ad policies that impact the types of ads you can run. Different channels may attract different kinds of audiences, which can impact the overall messaging and creativity you use in your tests. Tailor your testing strategies to each channel's specific limitations and audiences to ensure you're maximizing each channel's unique strengths and opportunities.
Creating different variations of your test is critical to successful A/B testing because it allows you to compare variables and determine which advertising elements are the most effective at driving your desired outcomes. Make sure to align your testing elements with your previously established goals. For example, if increasing your website's conversion rate is your primary objective, test different aspects of your landing pages to see which variations lead to the highest conversion rates. This can include headlines, calls-to-action, or images. To boost user engagement across social media, try different types of content and messaging on each platform.
Create as many variations of your test as possible for a more comprehensive analysis of the performance of each metric. This level of granularity is vital to helping companies pinpoint specific areas that need improvement or optimization. Testing multiple variations also helps to ensure that the results of the A/B test are statistically significant. If you only try a few variations, there may be insufficient data to draw accurate conclusions about which is most effective. By testing many variations, companies can gather a larger sample size, improving the test's statistical power and increasing the accuracy of the results.
Like all experiments, when creating your test, it’s also important to remember that your sample size needs to be large enough. If your sample size is too small, you risk introducing bias or other errors into your results, leading to inaccurate conclusions and ineffective marketing strategies. In general, the larger your sample size, the more accurate and reliable your test results will be. A larger sample size helps to minimize the impact of random variation or outliers, and increases your confidence that any differences between your A and B groups are meaningful and not simply due to chance. Successful ad testing also includes random distribution. Randomization helps to ensure that the sample is representative of the population, increasing the reliability and validity of the results and allowing for better decision making based on the data collected.
Now that you know the fundamentals of running a cross-channel A/B test, how do you ensure you’re interpreting the results in a way that can lead to positive decision making within your business?
Measuring the same metric across all channels in a cross-channel A/B test is essential to compare different mediums' effectiveness directly. Companies can determine which channel performs best by measuring the same metric, such as conversion rate, engagement rate, or click-through rate, and adjust their marketing strategies accordingly. If different metrics are measured, it can be challenging to compare their performance accurately. For example, if one channel is measured by conversion rate and another by engagement rate, it may be unclear which channel performs better overall regarding your company’s desired outcomes.
After conducting an initial review of the data collected, it can be helpful to group the data by channel, making it easier to compare and identify trends within or across channels. By doing so, you can gain insights into how different channels interact with each other and how changes in one channel may impact the performance of another.
For instance, if an A/B test reveals that a specific type of content performs well on social media and email, this could indicate an interdependence between the two. Use the insights to shift your marketing approach, such as incorporating similar content into other channels or increasing your integration between social media and email campaigns. Furthermore, identifying patterns across channels can assist you in establishing areas of weakness or opportunity within your marketing tactics. For example, if a particular type of content consistently performs poorly across all channels, this could indicate that the content needs reevaluation and that a different approach is needed. Similarly, suppose specific channels consistently perform better than others. In that case, this could suggest allocating more resources to those channels or reevaluating others.
Evaluating the impact of cross-channel A/B test results involves determining whether the test had a positive, negative, or neutral effect on key metrics. To assess the impact:
Compare the results of the winning variant with the control group to determine the degree of improvement.
Look for statistically significant differences between the two groups to conclude whether the improvement is valid or due to chance.
Use the concluding information to optimize marketing performance across all channels and improve overall ROI.
Evaluating the impact of a cross-channel A/B test also provides a baseline for measuring progress over time. By conducting regular tests and comparing the results to previous tests, you can continuously monitor your marketing performance and make adjustments as needed.
After analyzing the results, make necessary changes to your marketing materials and repeat the testing process across channels. A/B testing is an ongoing process and it may take several rounds of testing to identify the most effective marketing strategies for your business. You’ll find success if you stay focused on your goals, track your primary metrics, and be open to making changes based on your results.
Remember, cross-channel A/B testing requires careful planning and execution, so make sure you have the right resources to get the most out of your tests.
Last updated on March 3rd, 2023.