Advertising can be a costly-if not risky- business. While great ads can skyrocket a brand to success, bad advertisements can similarly define a company-just, not in the ways they’d like.
Some exceptional ads have resonated with such a large audience they went viral- think Wendy’s “Where’s the Beef” commercial. And others can get all of the components right but still miss the mark: the controversial Pepsi and Kendall Jenner ad of 2017.
But how can you tell for sure if you've struck advertising gold? Or instead just across a low-quality ad concept? Advertising testing is the solution.
Why You Should be Testing Your Ads
David Ogilvy, known globally as the father of advertising, once said, ”Never stop testing, and your advertising will never stop improving.” Ogilvy credited his incredible success to his meticulous research on consumer behavior. That's because he never underestimated the value of using insights to improve his process.
In the current advertising landscape, brands are constantly competing for a share of voice. Consumers are always engaging with advertisements- whether it's through Google, social media, streaming services, or TV Networks, the list goes on. This makes it crucial to understand who your brand's audience is, what they like, and (most importantly) why.
The process of ad testing enables brands to do just that by providing direct consumer feedback to implement into the development cycle. It does this by collecting insights from your chosen audience, allowing your team to hone in on the best visuals, copy, placement, and more. It also provides a level of certainty by giving you consumer data to back up your decisions.
What to Test
There are many aspects of your advertisements or campaigns that your team can test. Depending upon the chosen medium, the variables can range widely, to include:
- Ad Messaging: Is the copy relevant and engaging? Is the Call to Action (CTA) clear?
- Ad Creative: Are the visuals appealing? Does the creative vision come across well to consumers?
- Ad Placement: Which placement of an online ad results in the highest Click Through Rate (CTR)?
- User Device: Which types of ads display and perform best across devices?
Additionally, brands can use ad testing to find their most receptive consumer segments for a given campaign. Using the data collected, automated analysis can reveal new personas based on behavioral and psychographic data-see our blog on consumer segmentation to learn more about this process.
While there are many more that could be included, overall ad effectiveness is our focus for this piece. Ad effectiveness studies can encompass many ad measurement metrics. By testing nearly any combination of the items listed above, you can walk away with a better understanding of what your most effective ad would be and who your target consumer segments likely are.
When to Run Ad Testing
Ad testing is quite flexible in that you can test at any stage of the process. When you choose depends on your goals.
Pre-testing allows your team to analyze and integrate audience feedback beginning early in the development cycle. There are numerous tests you can run from early-stage ad concept testing to later ad effectiveness research. Pre-testing will, without a doubt, give you the highest level of confidence going into an ad or campaign launch.
Ad tracking takes place concurrently, collecting ad effectiveness data via ad measurement tools in real-time. There are various methods you can employ and metrics you can track-it simply depends on the type of ad and the platform it is running on. Ad tracking is most often used by digital advertisers, empowering them to optimize their ads as they run.
At the tail end, post-testing can be done periodically or continuously to monitor brand awareness, brand usage, brand preference, and other metrics to understand the combined effects of all of your brand's advertising. Post-testing also works well to dissect ad effectiveness and campaign success after the fact, to help your team avoid mistakes and replicate what went well.
Ad Testing Check-List
To get the most out of your ad pre-testing, make sure to keep in mind a few best practices:
- Set Objectives: What are your ultimate goals for this advertisement? Is it to raise brand awareness? Drive product sales? Whatever it may be, make sure your team chooses the specific ad measurement metrics that reflect these goals.
- Choose Your Approach: For pre-testing, ad effectiveness surveys are a common way to measure audience feedback. The two most popular survey methodologies are monadic and sequential monadic testing (our blog on Concept Testing digs into this topic a bit deeper). For ad tracking, you can utilize tracking URLs, pixels, cookies, and more to keep an eye on your ad's performance in real-time.
- Analyze the Results & Apply the Feedback: Utilize automated platforms to integrate both quantitative and qualitative insights. Apply the feedback you receive, repeat the process when needed, and launch your ad with confidence.
- Test Frequently: Test and track your ads before, during, and after launch to understand the performance throughout the ad's lifecycle.
Avoid These Common Mistakes
One big mistake to avoid in advertising is making too many assumptions. Just because you have always used a certain “brand voice” or copywriting style, why not test something new? Maybe your previous copy has been too “salesy” for many potential consumers. Or, perhaps the language you use to describe your brand’s offering is not the same language your customers use. And the same can be true for the imagery- just because your team may love the colorful and brightly designed option consumers may just see it as distracting or loud.
Additionally, make sure your “call to action”, or CTA, comes through loud and clear. Don’t ask too much of your audience, and definitely don’t send mixed signals. As a general rule, use one CTA per ad- something like “Learn More” or “Book a Demo Today”.
Running a comprehensive ad testing program on all of your brand’s concepts can pay dividends by way of ROI. With automated platforms, like SightX, brands can launch research projects and receive responses within a day. Automated data cleaning functionalities sort out low-quality data, giving you the time back to focus on the results. Similarly, the automation of quantitative data analysis and Natural Language Processing (NLP) for text analytics provides unmatched insights.
If you’re ready to launch your next project, we’re ready to help!