Improving B2B Message Testing
Read time: 4 minutes
Before discussing how to improve message testing in B2B marketing, let’s start with the basics: What is a message?
A message can be as simple and as short as a logo, name, or tagline. Or it can be longer, such as a short paragraph or a combination of images, text, and other elements. Messages can take many forms, from text to visual elements to audio or video or some combination of all of these. At GLG, we study all kinds of messages, including multimedia messages, in which the visual and print elements often are tested separately.
Why Test Your Messages?
Message testing is important for any business that wants to reach their target audience in a way that best resonates with them. The wrong message has the potential to wreak havoc. The classic example of this, which may be apocryphal, is General Motors’ marketing of the Chevy Nova in Latin America. While “nova” in Spanish and English both have a celestial connotation, the pronunciation of the word in Spanish is “no va,” which means “doesn’t go” — hardly a great name for a car. The story goes that this resulted in poor sales in Spanish-speaking countries.
Webcast: B2B Message Testing
This GLG Applied webcast was recorded on March 1, 2022
Another mythic case involves laundry detergent. To market its brand universally, Procter & Gamble supposedly used pictures, not words, to depict a dirty shirt going into a washing machine, detergent being added, and the shirt coming out clean. The pictures, of course, were arranged left to right. But in countries that read from right to left, such as Hebrew- and Arabic-speaking countries, the ad was interpreted as showing a shirt getting dirtier.
These examples, despite their questionable provenance, persist because they are stark — and humorous — reminders of how messaging can have unintended consequences. Often, real-world message failures are as simple as a missing letter or word. But bigger misses are always possible. Message testing can spot these misses before launch.
Perhaps more importantly, testing can help you determine whether your messaging will help achieve your desired goals. It also can provide a better understanding of how to talk to customers.
Goals that may drive message testing include:
- Developing a new message. You can use message testing and other types of research, such as focus groups and individual interviews, to develop new messages that later can go through the improvement stage.
- Improving the message. If you’re using several messages, or different messages are up for consideration, each can be tested against benchmarks or norms. You can perform other tests to determine why a message is performing the way it is — and which elements to tweak to create a different perception.
- Selection, or determining the best message. In addition to testing several messages against one another, you can test a specific message to determine whether it meets agreed-upon goals.
Types of Message Testing
The type of message testing performed typically varies with where a product or service is in its development cycle. Early on, you can test the ideas behind a message to help you create an effective strategy. Later, testing often focuses on specific message elements to determine if they resonate with the target audience. Finally, as a product/service goes to market, you can test to validate its messaging, perhaps to determine which of several messages work best.
In B2B survey research, the most common measures used to evaluate messages are affect, clarity, associations, and behavioral intent, with additional tasks, such as highlighter activities, used to identify which parts of the message drive impact.
- Affect. These measures involve how people feel about a message. Do they find it appealing, compelling, useful, unique, or innovative? Often, these attributes are measured using “agree/disagree” questions or semantic differentials.
- Clarity. Message clarity is particularly important in testing taglines, logos, and names to assess a message’s effectiveness in communicating its intended purpose or function. Common measures include ease of understanding, ease of recall, and match to intended meaning.
- Associations. These measures provide understanding of the positive and negative associations messaging triggers in clients, customers, or prospects. Commonly measured positive associations include attributes such as premium, easy-to-use, efficient, productive, and affordable. Testing for negative associations that one wishes to avoid, such as cheap or inefficient, is also prevalent.
- Behavioral intent. Behavioral intent questions measure the self-reported likelihood that someone will take a particular action, such as wanting to learn more, recommending a product or service to a colleague, or purchasing/using a product or service. The simplest message tests sometimes focus on behavioral intent measures alone, excluding the others. Here, the data set collected often comes from responses on a “likely” to “unlikely” continuum.
- Highlighter activity
Ultimately, message testing can answer a few key questions that can help your business create more successful messaging:
- Does your target audience have a positive perception of the message (e.g., is it positive, appealing, compelling, and easy to understand?)?
- Does the message communicate information that matches what your customer wants and needs?
- Does the message lead to customer behaviors that will benefit your business goals?
Answering these questions can provide a holistic understanding of your messages and assist you in making data-driven decisions about your marketing language. All things being equal, a good message is more likely to result in a sale or lead a user to recommend your product or service. In short, message testing can have substantial rewards.
About the Authors
Christina Tworek is Director of Advanced Analytics at GLG, leading a global team responsible for executing quantitative methods. She holds a PhD in psychology from the University of Illinois at Urbana-Champaign, where she researched human behavior and decision making. Her expertise is in research methods, survey design, and statistics. Before joining GLG, Christina was Vice President of Data Science and Advanced Research at HarrisX, a boutique research firm with a tech/telecom focus.
Max Wartel is a Senior Director on the GLG Research Team working with enterprise technology clients. Max holds a PhD from The University of Texas at Austin in the study of human communication. He has more than 12 years’ experience in survey research and has studied message effects and psycholinguistics in both academic and market research settings. Max has an extensive background helping clients improve their messaging and select the messages best aligned with furthering their goals.
This article is drawn from a GLG Applied webcast, part of GLG’s content series where seasoned GLG employees provide strategies and best practices from their areas of expertise, helping clients understand how to best gather and apply insight to their most challenging
You can also download our ebook, Message Testing: Best Practices.
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