Marketing is entrusted with communicating the value of our company’s products to the people who can benefit from them. All of the hard work of designers, engineers, manufacturers, product managers, and the many teams responsible for creating goods and technologies is ultimately in our hands. The best product in the world will not succeed without effective marketing letting customers know it exists.
Given this responsibility, marketers have developed a toolkit of techniques and technologies to help them test the messages they are creating. Marketers especially love tactics that come with cut-and-dried data to support decision-making. However, it’s important to choose techniques that give you the right data, at the right time.
One way that marketers commonly take a data-based approach to optimizing campaigns is through A/B testing. This has become a standard operating procedure for demand generation marketers. For example, an email marketer will create two slightly different emails, launch them to an initial group of recipients, and see which one performs better. The higher-performing email will then be sent to the rest of the recipient list. A/B testing is commonly used on websites, landing pages, and display ads.
This is a highly effective technique for tweaking messages, but it comes with two key limitations:
- By launching two creatives and accepting that one will under-perform, a marketer has already accepted that they will be “wasting” some of their audience on a less effective communication. This is already a suboptimal outcome.
- Because this is a launch-and-learn technique, the A and B creatives must be very similar so marketers can get a signal from one of them. For example, the color or position of a button may change OR the language used in a call-to-action (CTA) may be altered. An A/B test using completely different email designs, messages, and CTAs would yield no actionable results. Any one of those aspects might have led to an increase or decrease in engagement. The marketer simply can’t know what specifically worked and what didn’t.
While A/B testing is a great way to refine an already-launched campaign, it does not reduce the risk of messaging that doesn’t resonate with your target audience. It simply comes too late in the campaign process to prevent going down the wrong creative path.
Let’s say a marketer has two very different creative options they would like to test. A/B testing would be the wrong technique to use, because it relies on comparing results between very similar creatives. This is where agile research can help. By rapidly putting the two different concepts in front of real people, they can quickly get feedback to decide between the two different paths. Better yet, agile research does not rely on having a fully executed creative campaign before testing. You don’t have to design, program, and launch an email to get the data you need. Just put together a simple image mockup--or better yet, use a platform like Feedback Loop that provides quick mockup services--and put it in front of people to see how they react.
Not only does this approach reduce the risk of failed messaging, it eliminates the high material cost to the launch-and-learn approach. Think of all the stages of developing even a simple email: brainstorming, reviewing the text, designing and resizing the images, segmenting your target list, programming the email, and finally sending it. The internal person-hours add up quickly. This is all before the potential impact of a failed message is taken into account.
Launching and learning is a good strategy when you’re certain you’ve nailed down your core message. But nailing down that core message is incredibly difficult when people’s attitudes are constantly shifting. No matter how smart and creative our teams are, there’s just no substitute for getting our ideas in front of real people. We can think we know what will resonate with them, but until we actually put our ideas in front of them, we simply can’t know for sure.
Check out our explainer to learn how Marketing Professionals use Feedback Loop to optimize their marketing campaigns.
