How to measure aided brand awareness for reliable data
Imran Choudhary
Tracking brand awareness is a top priority for most brand marketers, and for good reason—if your target audience doesn’t know you exist, your brand might as well be invisible. We interviewed over 1,000 brand and marketing leaders, and the consensus was clear: aided awareness is the single most important metric to include in any brand tracker.
Measuring awareness for your brand and competitors has been standard practice for decades, and it might seem straightforward. But here’s what you didn’t know: most brands are getting inaccurate awareness results and they probably aren't even aware of it! This issue often stems from flaws in survey question design which leads to over or under inflated awareness figures, which can lead to poor strategic decisions. This problem is further compounded when you consider most lower funnel KPIs are asked to those aware of the brand, and if you get awareness wrong, you’re then impacting all of the subsequent findings.
At Latana, we've refined our approach to ensure the data you gather is not just accurate, but truly accurate. In this article, you’ll learn how to capture brand awareness accurately, even for small or sub-brands, avoid common pitfalls, and ultimately gain the trustworthy insights your brand needs.
The problem with how aided brand awareness is currently tracked
Getting your read on how many people are aware of your brand wrong can have major implications. For example, in large markets like the US, if your brand awareness was incorrect by 10%—, that translates to about 25 million people! This error not only distorts the quality of insights but also undermines the credibility of brand tracking efforts.
One of the key issues lies in how awareness questions are structured and the way brands are shown within the survey. Typically, respondents are presented with a long list of brands and asked to select which of them they are aware of. Our extensive testing reveals that this approach leads to a high cognitive workload for respondents. This list-based question format often causes them to focus on familiar brands while overlooking lesser-known ones, resulting in skewed data.
The number of brands on the list also makes a difference. For instance, increasing the number of brands from 5 to 20 in a survey can reduce the average reported awareness level for each brand by up to 15%. Furthermore, the composition of the list can significantly affect awareness measurements. A brand with medium awareness might show a 25% recognition rate when listed among well-known brands but could achieve a 36% recognition rate when placed with mostly lesser-known brands. Even highly recognized brands aren't immune; they might see their awareness reported at 61% when grouped with other well-known brands but jump to 76% when placed among lesser-known ones.
These errors have far-reaching consequences. Since awareness questions typically precede those on brand perception, purchase intent, and other key metrics, inaccuracies in the initial awareness measurement will skew all subsequent responses. This compromises the entire survey, leading to misguided business strategies. In large markets like the US or India, even a small error in brand awareness measurement can result in significant missteps in your marketing and brand strategy.
How can you ask brand awareness questions to get higher-quality insights?
Use brand logos, not just names
Incorporating brand logos into survey questions significantly enhances the accuracy of brand awareness measurements. Logos, as visual symbols, are more recognizable and memorable than brand names alone, aiding respondents in recalling brands more effectively. This reduces cognitive effort, minimizing the risk of overlooking or confusing brand names.
Logos improve the reliability of responses due to their frequent exposure in advertising, packaging, and digital media. This is particularly helpful in differentiating between brands with similar names and reduces errors from misinterpreting brand names or recall issues, leading to more valid insights.
Moreover, incorporating logos mirrors real-world interactions, where visual branding is crucial for recognition and recall. This method enhances data quality and supports informed decision-making and strategic planning based on reliable insights into brand perception.
Ask in silo, just one brand at a time questions
Our research showed that using siloed questions—where respondents answer about individual brands one at a time—tends to produce more reliable data. Although it may seem more time-consuming and costly, this approach reduces cognitive load and enhances data accuracy by minimizing distraction and focusing on one brand at a time.
Each question in a siloed format typically takes less than a second to answer, which helps maintain respondent engagement and reduces drop-off rates. This method also prevents the common issue of 'brand spillover,' where the presence of well-known brands in a list can skew perceptions and diminish the visibility of lesser-known brands.
Address social desirability bias with the "Not Sure" option
Social desirability bias is a common issue in survey research where respondents may inaccurately claim familiarity with a brand to appear more knowledgeable or socially acceptable. This can significantly skew the results of brand awareness surveys, leading to misleading data and inaccurate insights. When respondents feel pressured to give affirmative answers, they may overstate their familiarity with brands, distorting actual levels of brand awareness and impacting data reliability.
To mitigate social desirability bias and improve survey accuracy, incorporate a "Not Sure" option in the questions. This adjustment provides respondents with a neutral choice that acknowledges their uncertainty without forcing them into a binary "Yes" or "No." Allowing respondents to select "Not Sure" enables them to express genuine uncertainty about their familiarity with a brand, reducing the pressure to give a positive response they might not fully believe.
Including a "Not Sure" option can significantly reduce falsely reported brand awareness levels, with studies showing a decrease in inflated awareness reports by up to 10%. This approach builds trust with respondents by acknowledging and validating their honest responses, even if they do not align with a socially desirable narrative. Consequently, this enhances the overall quality of the survey data and provides more reliable insights into consumer perceptions and brand recognition.
Conclusion
In conclusion, accurate brand awareness measurement is crucial for effective brand tracking and strategic planning. Poor survey design can lead to significant inaccuracies:
Increasing the number of brands in a list from 5 to 20 can reduce reported awareness or usage for each brand by up to 15%.
Pairing well-known brands with lesser-known ones can lower the latter's awareness by up to 10%.
Excluding logos typically decreases brand recognition by about 20%.
Forcing binary choices can inflate reported awareness by around 8%.
Addressing these issues with refined survey techniques ensures more reliable data and better insights into brand performance. Latana’s advanced methodologies overcome these challenges, providing you with accurate and actionable insights. For enhanced brand tracking and strategic planning, book a demo with Latana today.
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