Brand Health Studies: What They Measure and What They Miss

A brand health study is a structured research programme that measures how a brand is perceived, recalled, and trusted across its target audience at a given point in time. Done well, it gives you a diagnostic baseline: where you stand competitively, which brand attributes are landing, and where perception diverges from the position you intended to own.

Done poorly, it gives you a deck full of index scores that look authoritative, cost a significant amount of money, and tell you almost nothing you can act on.

I’ve seen both. More often than I’d like, I’ve seen the latter dressed up as the former.

Why Most Brand Health Studies Fail Before They Start

The failure usually happens in the brief, not the fieldwork. A brand team decides it needs a brand health study, commissions a research agency, and the research agency delivers what it was asked to deliver: a tracker with awareness, consideration, preference, and NPS broken out by demographic segment. The numbers come back. Everyone nods. The deck gets filed.

Nobody asked what decision the research was supposed to support. Nobody defined what “good” looks like for their category. Nobody connected the outputs to the commercial model.

When I was running an agency and we were pitching for a retained brand strategy engagement, I’d always ask prospective clients one question before we discussed methodology: “What will you do differently depending on what the research finds?” If they couldn’t answer that, the study wasn’t ready to be commissioned. The question wasn’t designed to be difficult. It was designed to separate research that would drive decisions from research that would confirm a narrative someone had already written.

Brand health measurement is a serious discipline, and there’s a useful primer on how to measure brand awareness from SEMrush that covers the mechanics well. But mechanics are the easy part. The hard part is knowing what you’re actually trying to find out.

What a Brand Health Study Actually Measures

A well-constructed brand health study typically covers four layers of measurement, each serving a different strategic purpose.

Awareness

Spontaneous (unaided) awareness tells you whether your brand comes to mind unprompted when someone thinks about your category. Prompted awareness tells you whether people recognise your brand when shown it. Both matter, but spontaneous awareness is the more commercially significant metric because it reflects the mental availability that drives consideration without paid intervention.

The trap is treating awareness as the destination. I’ve sat in too many brand reviews where a high awareness score was presented as evidence of brand health. Awareness is table stakes in a mature category. It tells you you’re in the room. It doesn’t tell you whether anyone wants to talk to you.

Consideration and Preference

Consideration measures whether someone would include your brand in their shortlist when making a purchase decision. Preference measures whether they’d choose you over alternatives when the shortlist is established. The gap between awareness and consideration is where most brand problems actually live, and it’s the gap that brand health studies most frequently underexamine.

BCG’s research on most-recommended brands makes a related point: brands that earn genuine advocacy tend to outperform on both consideration and preference metrics over time, not because of awareness campaigns, but because of delivery. That’s a useful corrective to the instinct to solve a consideration problem with more media spend.

Brand Attributes and Associations

This is where brand health studies get genuinely interesting, and where the quality of the research design makes the biggest difference. Attribute tracking measures whether specific qualities, credibility, innovation, value, reliability, are associated with your brand versus competitors. When done well, this tells you whether your positioning is landing. When done lazily, it tells you that people think your brand is “trustworthy” and “good quality,” which is what people say about almost every brand they don’t actively dislike.

The attributes you track need to be category-specific and differentiating. Generic attributes produce generic data. If you want to understand whether your brand owns a distinctive position in the market, you need to be testing for the specific associations that would signal that position is working, not the ones that make the brand team feel good.

Net Promoter Score and Sentiment

NPS has become almost universal in brand health tracking, partly because it’s simple to explain to a board and partly because it provides a single number that’s easy to trend over time. Its limitations are well-documented. It conflates satisfaction with advocacy, it’s heavily influenced by recency effects, and it can be gamed by how and when you ask the question.

I’d use NPS as one signal among several, not as the headline metric for brand health. The more useful question is whether your promoters and detractors are changing in composition, not just in ratio. Who is promoting you, and who is detracting? That segmentation often tells you more than the score itself.

The Qualitative Layer That Most Studies Skip

Quantitative brand tracking gives you scores. It tells you where you are on a scale. What it doesn’t tell you is why you’re there, what’s driving the scores, or what would need to change for the numbers to move.

That’s the job of qualitative research. Focus groups, depth interviews, and ethnographic observation get underneath the numbers and surface the language, associations, and mental models that customers actually use when they think about your brand. This is where you find the perception gaps that quantitative data can only hint at.

Early in my agency career, I worked on a client whose brand health tracker showed strong awareness and reasonable consideration scores. The numbers looked fine. The qualitative research told a completely different story: customers liked the brand but didn’t trust it for high-value purchases. They saw it as a starter option, something you buy when you don’t know better yet. The quantitative data had no way to surface that. The qual work found it in the first two focus groups.

The practical implication is that brand health studies should include a qualitative phase, particularly when the quantitative data is ambiguous or when you’re trying to understand the mechanism behind a score movement, not just the direction of travel.

If you’re thinking about how brand health measurement fits into your broader positioning work, the brand strategy hub covers the full landscape, from positioning frameworks to competitive differentiation.

How Often Should You Run a Brand Health Study?

The honest answer is: more often than most organisations do, and with more consistency than most organisations manage.

A one-off brand health study gives you a snapshot. It tells you where you are today but gives you no way to distinguish between a structural brand problem and a temporary fluctuation caused by a recent campaign, a competitor move, or a news cycle. Tracking over time is what gives brand health data its analytical value.

For most mid-to-large organisations, quarterly tracking with an annual deep-dive is a reasonable cadence. Quarterly waves give you enough data points to identify trends without the cost of continuous measurement. The annual deep-dive is where you add qualitative depth, extend the attribute set, and test whether your positioning is evolving in the right direction.

Smaller organisations with tighter research budgets often do biannual studies. That’s workable if you’re disciplined about keeping the methodology consistent. The cardinal sin is changing your question set between waves because someone decided the old attributes weren’t interesting anymore. Consistency is what makes tracking data useful. Changing the questions resets the baseline.

There’s also a case for pulse surveys between formal tracking waves: short, low-cost quantitative checks on a handful of key metrics that give you an early warning system without the cost of a full study. These work best when you’ve already established a baseline and you’re monitoring for significant shifts rather than trying to diagnose the full picture.

The Competitive Framing Problem

Brand health studies that only look at your own brand in isolation are half a study. Brand strength is relative. A consideration score of 40% looks very different if your nearest competitor is at 35% versus if they’re at 65%.

Including competitors in your tracking set is non-negotiable if you want the data to be commercially useful. The question is which competitors to include. Most organisations default to their obvious direct competitors, which is fine as far as it goes. The more interesting question is whether there are adjacent or emerging competitors who are beginning to compete for the same mental real estate, even if they’re not yet competing for the same purchase occasions.

I’ve judged the Effie Awards and reviewed hundreds of brand effectiveness cases. The ones that stand out almost always include a clear competitive frame in their measurement approach. They’re not just asking “how do customers perceive us?” They’re asking “how do customers perceive us relative to the alternatives they’re actually considering?” That’s a harder question to answer, and it produces more useful data.

The risks of getting brand positioning wrong in a competitive context are real, and Moz’s analysis of AI risks to brand equity touches on one of the newer dimensions of this: how brand perception is being shaped by sources you don’t control, including AI-generated summaries that may not reflect your intended positioning at all.

Connecting Brand Health Data to Business Performance

This is where most brand health programmes break down. The research gets done, the scores get reported, and the data lives in the brand team’s corner of the business without ever connecting to the commercial model.

The question that should be driving every brand health study is: what is the relationship between these brand metrics and the business outcomes we care about? That requires building a model, even a rough one, that connects brand perception to commercial performance. Does an improvement in consideration correlate with a reduction in cost per acquisition? Does a strengthening of a specific brand attribute predict an increase in average order value or retention rate?

When I was growing the agency, we made a deliberate decision to connect our own brand positioning work to measurable commercial outcomes. We weren’t just tracking whether clients perceived us as a strategic partner versus an execution shop. We were tracking whether that perception shift was correlating with higher-margin briefs, longer retainers, and lower cost of sale. When you make those connections, brand investment becomes a commercial argument, not a faith-based one.

The HubSpot framework for comprehensive brand strategy components is a useful reference for thinking about how brand health metrics fit into a broader strategic architecture. The measurement layer only makes sense in the context of the strategic objectives it’s designed to track.

One practical approach is to build a simple dashboard that sits alongside your commercial reporting, showing brand health metrics alongside revenue, margin, and acquisition cost data. It doesn’t need to be sophisticated. What it needs to do is put brand performance and business performance in the same room, so the relationship between them becomes visible over time.

What Brand Health Studies Can’t Tell You

Brand health studies are a measurement tool, not an oracle. There are things they’re genuinely good at and things they’re structurally incapable of answering.

They can’t tell you whether your brand will be resilient in a crisis. Twitter’s brand equity collapse, examined in detail by Moz’s analysis of the platform’s brand equity, happened faster than any tracking programme could have predicted. Brand health scores in the months before the decline showed a brand with significant equity. What the scores couldn’t measure was the fragility underneath: the extent to which that equity was contingent on platform behaviour that was about to change dramatically.

They can’t tell you whether your customers are loyal because they love your brand or because switching is inconvenient. That distinction matters enormously for strategy. Loyalty built on switching costs is structurally fragile in a way that loyalty built on genuine preference is not. The research on brand loyalty during recessions from MarketingProfs illustrates this clearly: when economic pressure increases, loyalty built on habit or convenience erodes faster than loyalty built on genuine brand preference.

They can’t tell you whether your brand is building long-term equity or depleting it. A brand can show strong health scores while simultaneously running campaigns that are eroding its distinctive assets, training customers to wait for promotions, or narrowing its appeal to a shrinking demographic. The scores look fine until they don’t, and by then the structural damage has already been done.

These limitations aren’t arguments against brand health studies. They’re arguments for understanding what the data can and can’t do, and for building a measurement programme that acknowledges its own blind spots.

Building a Brand Health Study That’s Worth the Investment

If you’re commissioning or redesigning a brand health study, the practical checklist looks like this.

Start with the decision. What strategic or commercial decisions will this research inform? If you can’t answer that question specifically, the study isn’t ready to be scoped.

Define your competitive set. Include at least three to five competitors, and include at least one that you consider an emerging threat rather than an established rival.

Choose attributes that are differentiating, not just positive. “Trustworthy” and “high quality” are not differentiating attributes in most categories. Work with your brand strategy to identify the specific associations that would signal your positioning is working.

Build in qualitative depth. Even a small number of depth interviews alongside the quantitative fieldwork will dramatically improve your ability to interpret the scores.

Commit to consistency. Don’t change your question set between waves unless you have a compelling strategic reason to do so, and if you do change it, maintain a bridge question set so you can track the transition.

Connect to commercial data. Build the reporting infrastructure to put brand health metrics alongside business performance data from the start, not as an afterthought.

The BCG perspective on agile marketing organisations is relevant here: the organisations that get the most value from brand measurement are the ones that have built the internal capability to act on what they find, quickly, rather than waiting for the annual planning cycle to respond to what the data is telling them.

Brand health measurement is one piece of a larger strategic picture. If you’re working on how your brand is positioned, differentiated, and built to last, the brand positioning and archetypes hub brings together the strategic frameworks that make measurement meaningful.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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