Measuring Brand Awareness

While Brand Tracks are important to measure the brand health of consumer brands, it might not always be possible for early-stage brands to commission brand tracks But you can use freely available data to measure the strength of different aspects of your brand. Here is how👇 A Brand Track typically provides 3 things: a) Brand Awareness Metrics: Top of mind, spontaneous & total awareness b) Brand Funnel: Awareness to consideration to purchase to preference c) Brand Imagery/Associations: Emotional & Functional associations of your brand a) Brand Awareness In a Brand Track, the respondent will be asked, “Which are the brands in the category you are aware of” The first brand to be named will be the Top-of-mind awareness. All the brands mentioned by the respondent will be spontaneous awareness. And once the respondents run out of brands, the researcher will name all brands in the category and ask them, “Have you heard of this brand”. If they answer Yes, it will be aided awareness. Total awareness = spontaneous awareness+ Aided awareness. The proxies to measure awareness are: 1. Brand Search Volumes on Amazon: One of the best updates Amazon has made in recent years is giving the exact weekly search volumes on Amazon. Go to Brand Analytics in your seller platform and you will find weekly/monthly/quarterly search volumes. The increase in search volumes is directly proportional to the increase in brand awareness( See image attached) 2. Brand Search Volumes/Clicks on Google: Search Console gives you the exact clicks and impressions data for the different brand search queries on a weekly/monthly/quarterly basis. Again, increase in brand search volumes is directly proportional to increase in awareness 3. Share of Brand Searches: While the previous 2 metrics gives you a sense of how your brand is doing, share of brand searches in a category gives you an idea of the relative strength of your brand awareness vis-à-vis competition. On Amazon Pi, you can get the category bifurcation of keywords into generic, competition and brand. Share of Search= Brand Search volumes/(Brand Search Volumes + Competition Search volumes ) If this number keeps increasing, relative strength of the brand awareness is going up For the complete Brand Funnel and Brand Imagery metrics, go through the link in the first comment In addition to Brand Awareness/Funnel/Imagery, I also recommend the following metrics to be tracked quarterly/half yearly/annually to track long term strength of a brand 1. Performance Marketing/BTL Spends as % Of Sales: Should keep reducing 2. Discounts on MOP as % of Sales: Should keep reducing 3. Trade Schemes as % of Sales: Should keep reducing 4. Annual Price Increase: Should be higher than inflation/category So, yes while Brand Tracks are important, there are enough free data points brands already have to help them track the short term & long term outputs of the brand marketing efforts Use them to the fullest

𝐓𝐡𝐞 𝐬𝐢𝐠𝐧𝐚𝐥𝐬 𝐟𝐨𝐫 𝐰𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐦𝐚𝐭𝐭𝐞𝐫 𝐢𝐧 𝟐𝟎𝟐𝟔 𝐚𝐫𝐞 𝐠𝐞𝐭𝐭𝐢𝐧𝐠 𝐜𝐥𝐞𝐚𝐫𝐞𝐫. 𝐓𝐚𝐬𝐭𝐞 𝐰𝐢𝐥𝐥 𝐫𝐞𝐞𝐦𝐞𝐫𝐠𝐞 𝐚𝐬 𝐚 𝐦𝐨𝐝𝐞𝐫𝐧 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚𝐭𝐨𝐫. In a world saturated with generative AI, taste will matter. Great taste shows up in restraint as much as boldness. Leaders demonstrate discernment. They recognize quality, harmony, and originality in business ideas, language, and design. Competitive advantage will come from building systems rooted in taste that others cannot copy. 𝐈𝐭’𝐥𝐥 𝐛𝐞 𝐛𝐫𝐚𝐧𝐝 𝐀𝐍𝐃 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐧𝐨𝐭 𝐛𝐫𝐚𝐧𝐝 𝐨𝐫 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞. 2025 brought growing consensus that this is a false choice. Expect that thinking to gain momentum in 2026. Revenue growth will remain the headline KPI, but the dominance of performance marketing as the default lever will fade. The evidence is mounting. A TikTok and Tracksuit study found that high-awareness brands were up to 2.8x more efficient at driving conversions. LinkedIn’s B2B Institute makes a similarly compelling case for the role of brand in improving “buyability” in complex B2B decisions. 𝐋𝐢𝐯𝐞 𝐞𝐯𝐞𝐧𝐭𝐬 𝐰𝐢𝐥𝐥 𝐠𝐫𝐨𝐰 𝐚𝐬 𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐚𝐧𝐜𝐡𝐨𝐫𝐬 𝐨𝐟 𝐭𝐫𝐮𝐬𝐭. As AI-generated content accelerates, brands will respond with more intentional in-person experiences. More invitations. More rooms where trust is built face-to-face. Leaders will increasingly recognize the compounding advantage of networks and compete to build them with care and purpose. 𝐓𝐚𝐥𝐞𝐧𝐭 𝐚𝐧𝐝 𝐜𝐮𝐥𝐭𝐮𝐫𝐞 𝐰𝐢𝐥𝐥 𝐮𝐧𝐝𝐞𝐫𝐩𝐢𝐧 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠. Investment in tools and technology will continue, but the real advantage will come from teams that can adapt. Curious teams. Cross-disciplinary teams. Teams empowered to experiment. Expect renewed interest in Amy Edmondson's work on psychological safety as leaders recognize that progress depends on creating the conditions for people to grow into new ways of working. 𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐦𝐞𝐧𝐭 𝐰𝐢𝐥𝐥 𝐛𝐞𝐜𝐨𝐦𝐞 𝐚𝐥𝐰𝐚𝐲𝐬-𝐨𝐧 𝐚𝐧𝐝 𝐚𝐝𝐚𝐩𝐭𝐢𝐯𝐞. The question is no longer “How do we measure brand?” It is becoming “How do we measure it all the time?” Real-time visibility into shifts in perception, awareness, and consideration among key audience segments, and the ability to connect those shifts back to business outcomes, are becoming the standard. Tools like Tracksuit are gaining traction because they make continuous brand measurement more accessible and actionable. 💬 What shift do you see most clearly taking shape for 2026? Drop in the comments. #Marketing #Leadership #Partnership #Predictions

The trust economy is replacing the attention economy.✅ Marketers have long treated data as their superpower- the more you collect, the sharper your targeting. But as privacy laws evolve, that mindset is hitting a wall. New regulations are redrawing the boundaries of what’s fair, ethical, and legal in data use. Hyper-personalisation still matters. It drives relevance, loyalty, and conversion. Yet creating these experiences while respecting privacy has become the new balancing act. The line between helpful and invasive is thinner than ever. The smartest brands are already adapting. They’re moving from surveillance to service - collecting less, but using it better. They’re making consent experiences simple, data use transparent, and value exchange visible. Instead of chasing clicks, they’re building credibility. Here’s what that looks like in practice: 👉🏻 Audit every data point you collect. If it doesn’t add clear value to the customer, drop it. 👉🏻 Be upfront about how and why you use data. Transparency builds confidence. 👉🏻 Trade access for value - early previews, useful insights, or improved recommendations. Privacy is no longer just about compliance. It’s the foundation of modern marketing trust. The brands that will thrive aren’t those who know the most about their customers but those whose customers choose to share more with them. #futureofmarketing

Text will become the new battleground for brand trust. For decades, brands have invested heavily in the language of emotive visuals, from video and audio to influencers and fast-scroll storytelling. But in 2026, the real power shift will happen somewhere far less glamorous: in text. As more buying decisions are shaped directly inside large language model (LLM) systems, the written inputs that feed these models will determine which brands are surfaced, recommended and ultimately trusted. The buying journey is a complex trust loop, not a straight line. Buyers move fluidly between Google, LLMs like ChatGPT, review sites, peer communities and vendor websites. Distributed trust, not brand awareness, has become the real funnel. In this world, what a brand writes and what is written about it will matter as much, if not more, than how it looks or sounds. Peer influence already outweighs top-down brand control. For example, buyers trust peer recommendations far more than company-produced content. Third-party reviews, newsletters, chat threads, niche forums, blogs and community conversations now carry more weight than ‘official’ brand campaigns. This shift of influence to text-based networks will spark new roles inside organisations. Brand linguists, LLM editors and text reputation managers will ensure a company’s written footprint is clear, consistent, credible and machine interpretable. And as text-led communities become the new trust networks, brands will have to learn how to shape their narrative within the crowd rather than try to control it from above. In short: the next frontier of brand trust will be linguistic. ✍ Rachel Botsman, Author of Who Can You Trust? 📷 Getty Images 💡 This is one of a several ideas LinkedIn News is highlighting in our annual list of predictions. Read it here: https://lnkd.in/BI26UnitedKingdom Join the conversation in the comments or share your own prediction in a post or video with #BigIdeas2026.

Three conversations from yesterday's Skai Shopable panel that I haven't stopped thinking about. One from Microsoft. One from Amazon. One from Tinuiti. All pointing in the same direction and what it means for brands. CP McBee from Microsoft Advertising introduced a framework I think every marketer needs to internalize right now. We are not navigating one web anymore. We are navigating three: the Human Web (how consumers have always browsed, the "blue line web"), the LLM Web (where AI is synthesizing and answering), and the Agentic Web (where agents act on your behalf). Most brands are optimizing for the first one and largely invisible in the other two. Sue Oh from Amazon Ads shared something I had not fully processed yet: Rufus and Alexa+ are merging into a single experience called "Alexa for Shopping." That is a significant moment. One AI assistant, drawing on purchase history, voice conversations, and browsing behavior across every surface. Sue's advice for brands was direct: start with content. If your product pages do not answer real consumer questions, you will not show up in the conversations that matter. Simon Poulton from Tinuiti said something that has stayed with me: "Brands that aren't afraid to expose the negative are actually winning." In an era of AI-led discovery, consumers are more informed before they transact, and brands that own that conversation openly, including the tradeoffs, are seeing fewer returns and higher trust. The thread connecting all three: the brands best positioned for the agentic future are not waiting for the playbook. They're writing it now. What's the most important thing you think brands are overlooking as AI reshapes discovery?

💪 David v Goliath.... ... How to compete using a Smart Data Strategy... The biggest brands in the category can often easily outspend competitors when it comes to investment in data & insight, and this can give them a clear competitive edge. Smaller businesses are unlikely to be able to match their spend, but they can spend *smarter* to compete more effectively. Here’s how: 🚀  1. Start with High-Impact Data ↳ Market Overview Reports: Affordable sources like Mintel or Euromonitor provide a snapshot of market size, trends & competitor positioning. This helps identify category trends & establish the right areas or Shoppers to target without the ongoing cost of continuous data feeds. ↳ Focus on Key Business Questions: Pinpoint where insight will make the biggest impact e.g. - Detailed understanding of Retailer category performance ahead of a range review to help secure new distribution. - Identifying target consumers & optimal outreach strategies to boost penetration. 🔍  2. Leverage Selective EPOS & Loyalty Data ↳ Market-Level EPOS Data: This can be invaluable for insight into category dynamics & benchmarking KPIs vs competitors whilst avoiding high costs of retailer-specific feeds. ↳ Loyalty Card Data: Although this will only cover one retailer (so no total market read) it can give you very granular insights on sales performance as well as WHO is buying your brand. 🎯 3. Focus on Actionable Insights ↳ Prioritize Impactful Data: Concentrate on insights that can directly drive product development, pricing & promotions. Avoid ‘nice-to-have’ data that doesn’t materially impact your business. ↳ Make the most of the data you need DO have: Manage scope to only buy the data you *need* & make sure each source is *fully* mined. Investing time in analysis instead of buying new data can yield deeper understanding & more opportunities to optimise your brand performance. 📈 4. Scale Data Investments with Business Growth ↳ Mix One-Off & Continuous Feeds: Start with one-off data sources, then add targeted continuous data feeds as you scale. Regularly review usage & actionability & stop reports which don't add value. 🧠 5. Outsmart, Don’t Outspend --> Be Agile ↳ Develop a *Learning* culture : Smaller businesses can move around the Build/Measure/Learn loop much faster than bigger brands - Insight is the rocket fuel you need to power this. Key Takeaway: Strategic Data Use Although small & medium sized businesses will inevitably have less data, if they use what they can afford to answer the right questions & act quickly to execute then they can find a competitive edge of their own. What are your thoughts & experiences - let us know in the comments. Want to find out more? This week's #CategoryWins newsletter digs into this subject in much more detail : See link in comments or my bio ♻️ & if you enjoyed this post, please like & share it with your network. #CategoryManagement #FMCG #CPG #DataStrategy #CompeteSmarter

Marketing Week published data this week that every CMO should pin to their wall. Campaigns that drive significant increases in brand trust are 27 percentage points more effective at delivering business growth. One client saw a 1% improvement in trust score produce €98 million in incremental annual sales. The industry has had this data for years. And yet most marketing dashboards contain no trust metric at all. This is not a measurement philosophy problem. It is a planning cycle problem. Quarterly reviews demand quarterly numbers. Quarterly numbers reward activity. Activity produces visible metrics. Trust compounds invisibly, so it never gets the budget it deserves. The result: brands that are very busy, very present, and slowly losing their commercial edge. The question worth asking this week is simple. Look at your current measurement framework. Does it contain any metric that would take longer than twelve months to move? If not, you are measuring your team's output, not the asset you are building. Trust is not a soft metric. It is a revenue mechanism. The brands treating it as infrastructure are building something their competitors cannot easily match. The brands ignoring it are competing on execution. Execution can always be matched. Trust cannot be replicated overnight. My deep dive into this subject is in the comments.

There is a growing narrative that AI will diminish the role of brand. I believe the opposite is happening. In the AI era, brand may become one of the most valuable strategic assets an enterprise possesses. As buyers shift from searching to asking AI for recommendations, the battleground changes from impressions and clicks to trust, authority, discoverability, and recommendation probability. The question increasingly becomes: Will the AI mention or cite you at all? In this article, I explore why customer advocacy, analyst validation, operational credibility, narrative consistency, and proof ecosystems are becoming foundational to enterprise growth in the AI era. My thinking has been heavily influenced by conversations and insights from Tim Sanders, Godard Abel G2, Matt Marschinke, Tammy Tufty, David Lapp, Memsy Price, Seer Interactive, Romain de Saint Périer KKR, Felipe Thomaz, Saïd Business School, University of Oxford, and many fellow CMOs navigating this shift in real time. The future of the brand is not about shouting louder. It is about being trusted enough to become the answer.

Most enterprise brands are still optimizing for google rankings. (But AI engines don’t rank… they cite) And 57% admit they lack the skills to adapt a Hence, The smartest CMOs in Fortune 500s know this: Your brand isn’t competing on keywords anymore. It’s competing on authority signals. Because in AI search, credibility outranks content. And recognition beats repetition. Here are 6 authority levers every enterprise CMO should be pulling today: 1. Entity Recognition - Schema, profiles, and consistent brand identity. - If AI can’t define you, it won’t cite you. 2. High-Value Citations - Research reports, guest content, earned media. - Answer engines trust what other authorities trust. 3. Topical Depth - Content hubs, refreshed data, expert authorship. - Surface-level blogs don’t sustain visibility. 4. Brand Consistency - Quarterly audits, fact-checks, certifications. - Contradictions confuse AI systems. 5. Engagement Signals - Shares, discussions, influencer alignment. - Human validation powers AI trust. 6. Authority Measurement - Track citation share, audit knowledge graphs, flag harmful mentions. - Don’t guess. Optimize. The future of AI visibility won’t be won with more content. It’ll be won with smarter signals. Strong CMOs don’t chase traffic. They engineer trust. The AI Search Reality (via Semrush) 50% of ChatGPT-4o links point to enterprise sites. The other half scatter across news, blogs, forums, and more. LLMs already rely heavily on your website when generating answers. If half of AI citations already come from business sites, then enterprises must optimize their authority signals. And in AI search, trust isn’t a ranking. It’s recognition. Save this. Bring it into your next strategy meeting. Because authority isn’t an SEO play anymore… It's an enterprise growth strategy. Where Brandlight Helps Enterprises? Major brands leverage Brandlight to: - Monitor how their brand is cited across AI platforms. - Score and optimize content for AI-driven visibility. - Ensure consistent, factually accurate brand signals globally. - Track influencer/partner impact in AI-generated answers. - Flag harmful mentions instantly and protect reputation. For Fortune 500 brands and Large scale enterprises, Brandlight transforms authority signals into defensible AI visibility So your brand gets recognized, cited, and trusted where it matters most. 👉 Check now:https://www.brandlight.ai/ ♻️ Repost it to share with your network Follow me Madhav Mistry for insights on marketing

Not all PR is good PR. And not all awareness is the awareness you want. It’s easy to get caught up in big numbers. More mentions. More impressions. More eyeballs. But when leadership focuses only on reach, the quality of that attention gets overlooked. And sometimes, the wrong kind of awareness works against your brand goals. Here’s how to shift the conversation: → Include sentiment analysis in your reporting so you can show how people are talking, not just how many are talking → Focus on the audiences that matter most, not just the ones that are easiest to reach → Pair your reach metrics with trust and credibility measures to paint a fuller picture And here’s where AI can help: 1️⃣ AI can scan thousands of articles, posts, and comments in seconds, tagging tone (positive, neutral, negative) and highlighting recurring themes 2️⃣ AI can flag sudden changes in sentiment, so you know when a story or conversation is shifting 3️⃣ AI can break down sentiment by audience segment, so you can see if your core audience feels differently than the general public 4️⃣ AI can package this into easy-to-read dashboards and reports, so you can show leaders the quality of awareness alongside the quantity Awareness is only valuable when it moves you closer to your goals. Otherwise, it’s just a distraction.