Measuring Customer Experience ROI

I JUST looked at the data from recent customer calls, and 70% started the same way… "We need to understand what's being said about our industry/brand/competitors." Our data backs this up (Talkwalker). Mentions of "Social Listening" are up 145% year-over-year, with engagement around the topic up 84%. But this goes beyond traditional brand monitoring. The revenue leaders I’m speaking to are asking questions like: → What are prospects saying before they even reach out to sales? → How is our messaging landing compared to competitors? → What objections are surfacing in social conversations? GTM teams are starting to realize that while they're debating campaign performance in quarterly reviews, their buyers are having very public conversations about purchasing decisions… right now. So what can we learn from the world's largest focus group (5bi+ to be more precise)? Everything. Market shifts before they hit the mainstream. Competitive positioning gaps. Real buyer objections. Pipeline signals your sales team can actually act on. When we saw how GTM teams were using social intelligence we knew this was the future. The companies winning today aren't the ones talking the loudest on social. They're the ones listening the closest.

H2 is here: time to audit your brand like a cfo would Here's how: the CFO edition. Let’s not sugar-coat it. • If your brand isn’t remembered, it’s not chosen. • If it’s not trusted, it’s not bought. • If it’s not consistent, it’s not credible. • If it’s not tracked, it’s not understood at C-level. And if it’s none of those… you’re burning money. If you’re leading a business (not just a brand team), here’s the brutal truth: Your brand just played H1. Time to check the scoreboard and reset for H2. Ball in the centre. Let’s go. Let’s look how to audit your brand in 4 steps: 1. Identity & Consistency → Ask: • Does your brand look and sound consistent everywhere? • Are you building trust or confusion? → Look at: • Visuals, tone, decks, social, email, signage...does it all feel like one brand? → Metric Check: • Visual consistency rate • Template adoption • Tone alignment across channels 2. Positioning & Differentiation → Ask: • Is your value prop still relevant? • Are you leading with value — or shouting features? → Run: • Messaging audit • 3-word perception survey • Alignment workshop → Metric Check: • Share of Voice (Brand24) • Branded Search (Google Trends) • Consideration tracking (Tracksuit) This is the CFO’s territory: Are you spending to be seen, or to be remembered? 3. Messaging & Resonance → Ask: • Is your story consistent or reinvented every time? • Is everyone telling the same thing? • Are our campaigns sticking? → Look at: • Top/bottom content, sales pitch, internal message match → Metric Check: • Message alignment • Sentiment (Brand24) • Recall (Tracksuit) 4. Internal Branding: External strength starts inside. → Ask: • Does everyone know what we stand for — and why we matter? • Is purpose guiding real decisions? →Look at: • Comms, onboarding, values in action, leadership tone →Metric Check: • Brand clarity pulse • Template use • Training coverage • Leadership alignment Your brand isn’t fluff. It’s a business asset. So TRACK IT. That’s how your CFO sees the value, in margins, shorter sales cycles, reduced churn, stronger pricing, and better talent. The data says: • Strong recall = faster closes (Harvard Business Review) • Consistent brands = 33% higher revenue (Forbes) • Positive sentiment = price advantage (Kantar) • Brands tracked well = outperform peers (Forbes) Sooo the question isn’t: “Do we have a brand?” It’s: Is our brand working as a business tool?

In today's competitive market, brand marketing is essential for companies to differentiate themselves and build customer loyalty. Despite its importance, accurately measuring brand perception remains challenging. The default method of conducting surveys often falls short due to biases and limited reach. In this blog, the data science team from Airbnb shares their approach to leveraging deep learning-based solutions to quantitatively measure brand perception from social media interactions. -- From an architectural perspective, the team uses deep learning to create word embeddings and utilize the distances between these embeddings to measure the relatedness of brand perceptions. They explored a series of deep learning solutions, including Word2Vec, FastText, and DeBERTa, to capture contextual information effectively. -- From a metrics perspective, variability issues arise due to the stochastic nature of deep learning and the quality and quantity of the data corpus. To address this challenge, the team deployed a bootstrap sampling approach with repetitive training and leveraged a rank-based perception score to provide more stable metrics. The blog shares many intriguing insights and applications from this brand perception measurement approach. It is exciting to see how a more quantitative method can be applied to the traditionally vague area of brand marketing, making it a valuable case study for those interested in innovative marketing analytics. #datascience #analytics #measurement #brand #marketing #deeplearning #embeddings – – –  Check out the "Snacks Weekly on Data Science" podcast and subscribe, where I explain in more detail the concepts discussed in this and future posts:    -- Spotify: https://lnkd.in/gKgaMvbh   -- Apple Podcast: https://lnkd.in/gj6aPBBY    -- Youtube: https://lnkd.in/gcwPeBmR https://lnkd.in/gjEdixQ8

I built a Clay workflow to monitor brand mentions across social media and turn them into GTM signals my team can act on. Most teams either ignore social chatter, drown in it or react when their investor sends them something they saw. None of these works. They lack a strategy and a system to enable social listening. My Clay workbook listens across Reddit, LinkedIn, and Twitter/X, analyzes sentiment, summarizes the context, and drops a clean signal straight into Slack. Here’s how the workflow works: – Pull brand mentions from Reddit, LinkedIn company mentions, and Twitter/X keywords – Visit the source URL to extract the actual post text – Analyze sentiment and assign a score so you know if it is positive, neutral, or risky – Generate a short summary instead of dumping raw text – Send everything into a dedicated Slack channel in near real time What I love most about this is how many use cases this unlocked. If sentiment is positive, you get instant feedback on what messaging resonates. If sentiment is negative, you catch brand risk early before it spreads. If buyers are talking about a problem you solve, you spot pipeline signals hiding in public conversations. And because this lives in Clay, you control everything: Keywords, sources, frequency, models and event costs. This replaces expensive social listening tools and gives GTM teams something better... a living feedback loop tied to action. If you want the full walkthrough and Clay template, it's in this week's Stack & Scale episode. Or comment "Clay workflow" AND connect with me (I've run out of InMail already), and I'll send the resources directly. Happy (social) listening! 

I waited a few days for the noise to settle before writing this, because the lesson here is bigger than the incident itself. Recently, a customer in Egypt shared a post claiming that a car purchased as “new” had already been used and had been damaged! The brand involved is well known. Within days, the issue escalated across social media, influencer content, TV programs, and multiple media outlets. The case was eventually resolved and the post was removed. But reputational impact doesn’t reset that easily. This is where online reputation management becomes critical. ORM is not about replying to comments or managing a crisis after it explodes. It’s about visibility, structure, and decision-making speed at the very beginning — when an issue first appears, not when it peaks. It allows brands to understand what is being said, where conversations are spreading, and how to act before perception hardens. I’ve suprived delivering hundreds of ORM reports for global brands across FMCG, real estate, telecom, and tech. And the same questions consistently come up at leadership level: • How is our brand perceived online today? • How do we compare to competitors? • What are customers and media really saying about us? These are not marketing questions, They are business questions. Brands that manage reputation well don’t rely on luck or damage control. They invest in clear monitoring, defined escalation paths, and informed action. If you can’t answer the questions above quickly, you’re leaving value — and trust — on the table. Three practical priorities for any brand today: • Real-time monitoring: across social and media channels to detect issues early • Clear escalation and response playbooks: who speaks, what is said, and how fast • Continuous measurement: sentiment, competitor activity, and impact In Egypt and the Gulf, one post can undo years of brand building and If you manage a brands and you don’t have that system in place, let’s fix it before a single post becomes a headline #Brandmanagement #Reputationmanagement #ORM #CrisisManagement #Corporatebranding

Here are the results of a brand tracking study on marketing automation platforms (mid-market B2B SaaS segment). When we asked "which brands come to mind first?", about half mentioned HubSpot, Adobe Marketo, Pardot. Everyone else? 10% or single digits. Getting people to think of you is the hardest challenge for new platforms. The big brands already own space in buyers' minds before the buying process even starts. They grab the first 3 spots in the initial shortlist, leaving only a couple of spots left for others. Braze, ActiveCampaign, Customer.io, Constant Contact - these companies have 55-70% aided awareness. Smaller brands like Ortto only 13%. Brand preference: HubSpot dominated with 56% Marketo got 42% Pardot 28% The juicy part? No challenger brand reaches even 10%. Brand perception: HubSpot owns "easy to use" (74% association). Marketo and Pardot split "powerful" and "enterprise-ready." The challengers? They have no clear identity. Braze gets 18% for segmentation. That's their biggest win. Some brands have perception problems. Pardot has solid aided awareness (99%), but relatively low brand preference (28%). There are some reputation problems they need to solve. Constant Contact also has high aided awareness (77%), but only 1% prefer them - signaling an urgent need to modernize perceptions. Here's what buyers said kills their interest in lesser-known platforms: • Economic gap - 42% won't even look at you without concrete savings proof. "It would need to be at least 40% cheaper," one marketing leader said. • Stack-fit gap - 27% demand plug-and-play with their stack. Moving away from HubSpot means potentially breaking 20 other tools. That's career suicide material. • Capability-confidence gap - Buyers assume incumbents have deeper functionality and better service; challengers must supply trials, proof points, and service assurances to earn trust. 20% mentioned AI as their wishlist item. But here's the thing - none of the big players own the AI narrative yet. If you're a challenger brand, that's your opening. But don't lead with "AI-powered." Lead with "Launch a multi-channel campaign in 60 seconds" and then show how. The incumbents have a moat. You need a bridge. Price + proof + integrations + one killer use case = your only shot.

AI platforms don't rank your pages. They form opinions about your brand. Most marketers have no idea what those opinions are.. I've run SEO across multiple businesses for 16+ years. For most of that time, the job was simple. Track rankings. Track traffic. Track keywords. But AI search changed the question entirely. It's no longer just "where do I rank?" It's "what does AI say about me when someone asks?" Because when a buyer asks ChatGPT or Perplexity for a recommendation, they don't get 10 blue links. They get a narrative, a summary, an opinion about your brand. And that opinion is shaping decisions before anyone reaches your site. Most marketers have never seen that narrative. They're flying blind. That's exactly why I use Semrush One's Brand Performance feature. It's a set of reports inside the AI Visibility Toolkit that reveals how AI actually perceives and positions your brand. It shows me: 1/ Share of Voice vs competitors → How often AI mentions you compared to your direct competitors → See exactly where you lead and where they have the edge 2/ Brand sentiment → Whether AI describes you favorably or as background noise → Poor sentiment can undo months of brand-building. Catch it early. 3/ Narrative drivers → The specific factors shaping how AI talks about you → Which features, sources, and topics drive your reputation 4/ The raw AI answers → See the actual, unedited responses AI gives about your brand → Read exactly how ChatGPT, Gemini, and Perplexity describe you to buyers 5/ AI-generated strategic recommendations → Specific actions to strengthen your position → Not just what's wrong. What to do about it. In traditional SEO, you optimize for rankings. In AI search, you're managing perception. How AI frames you, positions you, and recommends you against competitors. You can't manage a perception you've never seen. Brand Performance lets you see it. Across ChatGPT, Google AI Mode, Perplexity, and Gemini. The brands watching how AI talks about them right now will shape that narrative. The ones ignoring it will let AI and their competitors write it for them. See how AI describes your brand with Semrush One: https://lnkd.in/gG2Cgbrg ♻️ Repost if you think brand perception in AI is the next thing every marketer needs to track. #SemrushPartner

AI is changing how we get found. (And most brands haven’t caught up yet.) Google rankings tell one story But AI tells another Every time someone prompts ChatGPT or Perplexity about your niche They’re served a version of your brand The question is: Is it accurate? Positive? Visible at all? We're entering the AI-first search era. People no longer only Google, they ask. And the AI answers shape perception instantly. So I tested Writesonic’s GEO tool. It’s the first enterprise-ready solution to help brands measure, manage, and grow their visibility inside LLMs. Here’s what stood out: → You define brand topics and prompts. → GEO queries AI engines consistently. → It tracks when, where, and how you’re mentioned.   And then the AI Visibility Monitor provides brand with the following: 𝗕𝗿𝗮𝗻𝗱 𝗣𝗿𝗲𝘀𝗲𝗻𝗰𝗲 – 𝗖𝗼𝗿𝗲 𝗔𝗜 𝗦𝗲𝗮𝗿𝗰𝗵 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 Visibility: % of AI answers mentioning your brand. If you're not visible, you don't exist. Mentions: Total AI answers that include your brand, shows scale. Sentiment: AI's tone when mentioning your brand. 𝗖𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀 – 𝗪𝗵𝗮𝘁 𝗔𝗜 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 𝗶𝗻 𝘆𝗼𝘂𝗿 𝘀𝗽𝗮𝗰𝗲: Total Pages Cited: Unique pages AI pulls from in your niche. Your Pages Cited: Pages from your site AI actually references. Low = content opportunity. Domains Cited: Number of different sources AI trusts in your space. 𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗼𝗿 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝗶𝗻𝗴 – 𝗬𝗼𝘂𝗿 𝗔𝗜 𝗠𝗮𝗿𝗸𝗲𝘁 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻: Market Share: Your slice of total AI visibility vs. actual market share. Position: Your rank among competitors. You can even compare side-by-side to identify gaps fast. The result? You’re no longer flying blind in AI search. You see how you're being represented. You see how to improve it. And most importantly, you stay ahead as AI Search evolves. Google still matters. But it's no longer the only gatekeeper, with 100 million+ weekly AI search queries. Understand AI discovery or risk being invisible. → See how 𝗚𝗘𝗢 works: http://bit.ly/4eoUfXF P.S How are you tracking your brand’s presence in AI right now?

If you're not tracking your AI visibility yet, here's a checklist to get started. AI search is becoming a real traffic channel. But most teams don't have a process for it. Start with these: → AI Visibility Score – Use Semrush's AI Visibility tool to see where you rank across major AI platforms (ChatGPT, Perplexity, Gemini). → Compare your performance – Pull competitor AI visibility reports in Semrush: which brands appear most in AI answers for your category keywords? → Identify target prompts – Run your product category, pain points, and buying intent phrases through ChatGPT and Perplexity. Screenshot which brands show up and in what context. → Conduct an AI visibility site audit – Check your robots.txt file for AI crawler blocks. Review your structured data and entity markup. Daily & weekly tasks: → Track brand mentions – Set up daily alerts in Semrush AI Visibility. Run your brand name through LLMs every Monday to catch shifts in positioning. → Monitor competitor AI visibility – Check competitor tracking dashboards in Semrush weekly. Note any sudden jumps in their AI presence. → What is AI saying about your brand? – Read the full AI answers, are you positioned as a leader or an alternative? → Check the sentiment – Tag mentions as positive, neutral, or negative. Track if perception is shifting based on new content or citations. → Verify AI bots can crawl your site – Check your server logs for AI crawler hits. If you see zero activity from GPTBot or PerplexityBot, your robots.txt might be blocking them. Monthly tasks: → Update content – Identify your most important pages. Add clear definitions, concise summaries, and entity-rich intro paragraphs. Use Schema markup for FAQs and How-To content. → Benchmark against your top competitors – Run monthly AI visibility reports. Compare citation sources, mention volume, and positioning changes. → Identify new prompt opportunities – Use SparkToro's AI Overview tracking to find questions where competitors appear but you don't. Fill those gaps. → Monitor which sources get cited in your niche – Track which publications and sites AI platforms reference most. Build relationships with those properties. → Track how perception and sentiment are shifting – Adjust messaging if negative patterns emerge. Periodic tasks: → Citations from authoritative sources – Get quoted in high-authority articles → New content – Find prompts where you should appear and write comprehensive guides, case studies, or research reports targeting them. → E-E-A-T signals – Add author bios with credentials. Link to authoritative external sources. Get expert reviews or testimonials. → Multimodal AI – Create high-quality charts, infographics, and product images with descriptive alt text. Post video content on YouTube with detailed descriptions. → LLM seeding – Publish research, datasets, or frameworks that become go-to references. Build a routine, track the metrics, and improve over time.

𝗕𝗿𝗮𝗻𝗱 𝗮𝘄𝗮𝗿𝗲𝗻𝗲𝘀𝘀 is the result of your collective marketing efforts to generate an imprint of your brand in people’s minds. But how do you measure it? 🤔 Extracting intangible things like perception and awareness from people’s minds is tricky But there are tools you can use to capture directional growth, giving you a changing snapshot of how your brand’s presence grows (or shrinks) over time Correlating the timing of growth in brand awareness to say, a YouTube campaign you've been running, is one practical example of how you can measure the value of a campaign's effectiveness without direct conversion metrics: 🔍 𝗚𝗼𝗼𝗴𝗹𝗲 𝗞𝗲𝘆𝘄𝗼𝗿𝗱 𝗣𝗹𝗮𝗻𝗻𝗲𝗿 - Google Ads (Google Partner) Track branded search volumes and compare them to competitors 📈 𝗚𝗼𝗼𝗴𝗹𝗲 𝗧𝗿𝗲𝗻𝗱𝘀 Visualize brand search interest over time and see how it stacks up in different regions 📊 𝗕𝗿𝗮𝗻𝗱 & 𝗦𝗲𝗮𝗿𝗰𝗵 𝗟𝗶𝗳𝘁 𝗦𝘁𝘂𝗱𝗶𝗲𝘀 - Google Ads (Google Partner) Run through Google, Meta, or other platforms to measure how campaigns shift awareness and consideration 🌐 Semrush See organic growth in branded keywords, competitor share of search, and market visibility 🖥️ 𝗚𝗼𝗼𝗴𝗹𝗲 𝗦𝗲𝗮𝗿𝗰𝗵 𝗖𝗼𝗻𝘀𝗼𝗹𝗲 Get a direct view into impressions, clicks, and CTR for branded organic queries Together, these tools give you signals to understand whether your brand’s footprint is expanding, holding steady, or shrinking 👉 What tools have you found most useful for measuring brand awareness? Image Credit: Google Trends #brandawareness #marketinganalytics #ppc #digitalmarketing