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2 Seconds to Brand Impact: A Modern Video Ads Playbook
Would you believe it: Almost no one watches your video ads! Take your company employee hat off: Do you watch any other company’s video ads, if you have the choice to skip or swipe? Do you watch your company’s ads, if you have the choice to skip or swipe? The answer for you, me, our employee peers is likely no. Reason: Just as for our users… The ad’s in the way. When producing advertising, here’s the reality CMOs ignore: You are not competing against other ads. You are competing against the entire internet. All of it. If a human is actively watching your 60s ad on TV all the way to the end, the most likely reason is her phone’s battery is dead. Pause for reflection. This blog post was originally published as edition #489 of my newsletter TMAI Premium. Each week, I share strategic insights and actionable guidance on how to stay at the very bleeding edge of Marketing, Analytics, and AI-transformation. Sign up for TMAI Premium to accelerate your career trajectory. 100% of TMAI revenues are donated to charity. I am not advocating against video advertising. It is essential for effective and scalable brand marketing. I am advocating for ad creatives to embrace the decade-old reality of consumer behavior, media consumption, and attention fragmentation. I am for video advertising strategies that are built to recognize that attention is the most expensive currency on earth. To make the case for just how important this is… Here’s my synthesis of the data illustrating the average seconds of attention paid in each media channel, how much of that attention is with sound on (more effective!), and how much of your ad is watched all the way to the end… Video Ads: Attention Metrics [For a higher resolution image: Right mouse click > Open image in new tab.] Sobering, no? Big Insight: Active attention to an ad is contextual. And, brief. Increasingly: Just the first two seconds. Big Implication: A 60s TV ad is now, functionally, a 15-second ad with 45 seconds of background noise for most viewers. A 15s TikTok video ad is now, functionally, a 1s display ad view. Big Disappointment: Your Brand Marketing is largely delivering zero brand lift when measured with true test-control brand lift studies. If you are producing ads (“stories”) longer than 30 seconds – like the one- to five-minute sappy holiday creatives common this time of year – you are doing that purely for your own entertainment. Protect your career by not promising any business profits. The data above also explains why your TikTok / Reels / YT Shorts ad campaigns have almost never delivered brand lift with an above zero confidence interval – a massive waste of precious creative & Marketing budgets. [Note: TMAI Premium subscribers, carefully review TMAI #447: Confidence Intervals: A Brand Analytics MUST Have. Please email me if you do not have my awesome Excel model to compute your campaign’s real impact.] Why obsess about this? Effective Brand Marketing is the only way to grow Market Share over time. Video ads are a necessary tactic in that holy quest. Let’s embrace real consumer behavior, media consumption, and attention fragmentation. Shorter video ads. And, regardless of the ad length, front-loaded video ads with high-impact first two seconds. Wait, Wait, Wait… Loooong Ads Are Better! Like me, I’m confident you’ve heard a variation of this from your VP of Creative / Global Creative Director / CMO: Long creatives tell a better story, and people remember better stories. What does the data say? Data Fact One: Studies by Facebook’s Brand Lift team, Google/YT ABCDs find that shorter ads (6-15s) often drive equal or higher lifts in Ad Recall and Consideration than longer ads. (In part because they are less likely to be skipped or are unskippable.) Data Fact Two: Quantifying that… Research (Lumen/Teads) identifies that 15s ads drive 75-85% of the recall of a 30s ad – at half the media cost (Magna/IPG). Data Fact Three: If they hold attention throughout, longer ads (30s+) can drive higher emotional intensity and long-term brand affinity. Your VP, Director, CMO is right… Longer ads have additional value to offer! To deliver that special magic, long ad creatives have to solve three problems: 1. The long ad needs to be built to solve a different, long-term purpose. 2. If you just want to drive Unaided Brand Awareness, Consideration, or Purchase Intent, you can do so more efficiently with a shorter ad, while lowering resentment risk. The long ad creative needs to be super magnificently effective in the first 1-4 seconds. The creative has to be able to avoid the Skip / Swipe in skippable ad formats, and avoid the human looking away / going to the bathroom / looking down at their phone in the case of non-skippable formats. 3. The long ad creative needs to be supported by 3x – 6x additional media budget – when compared to the 15s ad media budget – to deliver the promised higher emotional intensity. Life Changing Insight: The modern battle for brand lift isn’t won by one long story; it is won by frequency of short, high-impact moments. No matter your ad length, if your ad is not seen x number of times over y weeks, it will not deliver impact. [Note: Premium subscribers deep dive and incorporate: TMAI #431: Impact of Ad Length on Campaign Cost.] It is difficult to meet these three magic-producing criteria, but it can be done. Use the ad length that is optimal for the business purpose you are solving for. Don’t use a jumbo jet to commute to Manhattan. Don’t try to cycle from NY to Chicago. Regardless of ad length/purpose, I’m confident you noticed that you really need to make the first two, three, seconds count. [Special Advice: The Ad Sales team at one particular ad platform aggressively champions the cause of looooooooooong ads. If you run into them, set all else aside and ask one question: How do we get distribution for the looooooooooong ads? If you get an affordable, scalable answer that spike and sustains, follow their advice.] An Ideal Video Ads Media Plan. Recognizing that effective Brand Marketing via video ads is not a one-size-fits-all, I want to sketch this starting point for your video ads strategy: Spark: 6s “Bumpers” / equivalent, will take a majority of your media budget (55-65%). They build frequency, recognition, and sustain your brand lift gains. Fuel: 15s / equivalent, will take nearly all of the rest of your media budget (25-35%). Ideally, sequenced with effective 6s ads so they would have gained interest to hear the rest of the story. Blaze: An occasional 30s (ideally non-skip) taking the remaining budget (5-8%), in big spike moments to support a specific brand feeling. Beacon: A rare, beautiful 60s film, not as an ad (0%), but organically seeded on social channels, shown in internal company meetings, submitted for industry awards. There can be small, occasional, variations. From my experience across industries and countries… For retail type companies, Spark takes up 70%. For B2B, Fuel can be up to 40%. For a revolutionary new product/company, Blaze temporarily can be 20%. Repetition: You will notice I’m consistently prioritizing frequency over length. Effective Brand Marketing is frequency-powered in an age where attention is the most expensive currency. Second repetition: Regardless of length, each type of video ad will have to start front-loaded, with a BANG. The first few seconds are critical to plant a memory, to generate interest in seeing rest of the story. Let’s learn how to do that. How to Be Creative: Zero 2 Interest in Two Seconds! Across all social video, users pay only 12 seconds of active ad attention for every hour(!!). Implication: Your share of voice is infinitesimal unless you disrupt their pattern. To do that, you have one to three seconds max. I’ll share data-identified effective creative tactics, for each channel. But first, there are five creative tactics that apply regardless of channel. Big 5 Universal Creative Effectiveness Truths. 1. Brand in 3. The brand must be recognizable within 3 seconds (logo, color, sonic signature, character). 2. Frame-One Impact. The first visual frame must tell a story or pose a question. (It is insanely difficult, that is what it takes to win.) 3. Sound as Lead, Not Support. Music, voice tone, and audio pacing drive emotional response faster than visual. 4. The “Why Now?” Answer the viewer’s unconscious question: “Why should I care about this right now?” (Reminder: Your ad’s competing against all the content on the internet.) 5. Creative Pre-Tested. The only way to win before you spend is to pre-test your creative – and ensure it passed in your ad’s media channel and your intended audience. For Concepts and high media weight Executions, use HMM Pro. For high volume, low media weight Executions, TikTok/Shorts/Reels, use HMM AI. These are super high standards for your creative teams to meet. In a world where you’ll get 12 seconds of ad attention per hour… Recommendations 1 – 5 above are mandatory. If you feel your video ads are falling short of the above truths: A. That explains why you can’t prove an iota of incremental impact from Brand Marketing on long-term Revenue. B. That should be a reason you pause your current video ad spend until your creative team/agency can deliver worthy creative. The Build Effective Creative Journey Continues. Every channel has its nuances. What works on TV rarely works on YouTube. What works on Reels often does not work for Facebook. Mobile video ads needs different Big Bang Two-Second start than if they are served on CTV. In TMAI #490 I’ve shared detailed best practices I’ve validated through testing and media tactics individually for Linear TV, CTV, YouTube Skippable, Facebook/Instagram Feed, TikTok/Reels/Shorts, and Snapchat. Lessons from approx. $10 bil in brand marketing spend analyzed. If you are a new TMAI Premium member, please email me if you can’t find edition 490 with detailed Part 2. If you are not, grab an annual Premium subscription here – the insights will transform your professional effectiveness! Bottom line. Our belief in the power of story is correct. Our canvas has changed. The 60-second spot is not dead, as illustrated above, it has a purpose in a Beacon strategy on free channels and for earning awards. The 60-second ad as interruption is dead. It does not perform as a media strategy. (Neither is there much inventory to buy. The platforms know it does not work!) Short-form creative is how we earn attention, and earn permission to tell our (slightly) longer, richer story. We are not abandoning our craft. Our quest remains legendary brand lift! The path we take to get there is new. Carpe diem. Avinash. PS: In the world of Chinese livestream sales, Zheng Xiang Xiang’s approach is super impressive. She sells 100 million Yuan ($19m) of products in a week. Don’t emulate it. Xiang Xiang operates within available attention. Appreciate that to become a better Marketer.
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Loss Recovery Growth Model: Answer Engine Optimization (AEO)
With the slow and steady evolution from keyword searching to resolution questions typed into Answer Engines, you are going to lose traffic (and revenue) somewhere in the rage of -18% to -64% during the course of the next calendar year. Today, our challenge is three-fold: A. How can you identify the size of your loss? B. What can you do to recover some losses? C. What actions can you take to take advantage of this shift and grow revenues? Every smart company is building a forecasting model to estimate these three life-critical dimensions. Let me make that important exercise a little easier for you. My model will help you estimate your losses, identify opportunities to recover, and share actions, and by how much each can drive growth. You can use the model to have strategic conversations with your CEO, CFO, and help your CMO create a clear, prioritized, list of actions (including hiring new staff with relevant expertise). This blog post was originally published as edition #482 of my newsletter, TMAI Premium. Each week, the newsletter shares strategic frameworks and practical here’s how to stay at the very bleeding edge of CFO-proof Marketing and Analytics. Sign up for TMAI Premium to accelerate your career trajectory. The Librarian to Grad Assistant Search Transformation. Past: When the User asked a question, traditional Google was a librarian. It did not know answers, it pointed us to a section of the library – four plus ten blue links – and said the answer is highly likely to be in these books, good luck. As a business, our job: Be the most attractive, relevant, authoritative book on the shelf, and/or pay to put our book on the special display by the front door of the library. Present: When the User asks a question, the new Answer Engine is the ruthlessly efficient grad research assistant. It goes to the library. It reads the 14 relevant books from a billion books, synthesizes the information, writes a perfect one-page summary directly answering the question. Most businesses lose the clicks, one or two get the click now – and even that we might not get as the Answer Engine absorbs ecommerce, and as AEs become Agentic eliminating the human step altogether. ChatGPT, DeepSeek, Claude are examples of Answer Engines. AI Mode in Google, now out in 40 countries, is also an example of an Answer Engine experience. ChatGPT Agent, Rufus from Amazon are examples of AE experiences that get close to Agentic search – humans need only express a wish; the agent does everything else. Learning, shopping, homework, will never be the same again. My recent AEO newsletter series, six editions (!), covered the changes underway, the actions you need to take on your digital experience, your organic and paid strategies, new measurement to embrace, and how you can prepare to live in an Agentic “Search” world. If you’ve not read that almost mini-book, please do. It is critical to understand the nuance and detail of this conversation. [Note: If you are a new Annual Premium Subscriber, please email me. I’ll be happy to share the six-part series with you.] Here’s a picture I sketched for a recent keynote on AEO, outlining the transformation underway… And, the implications… The completed forecast model will cover items 1 through 5 in the picture above, which are raised from these three questions for every business: 1. How much traffic will we lose? (Organic & Paid) 2. Given the librarian shift, how much of this loss can we recover? (Not all.) 3. Can I take advantage of this shift and grow new traffic? (Yes.) Let’s answer. The Business Losses Are Here (And, Accelerating). The change in user behavior above (in blue) is driving a change in the user experience (in black). Ex: Answers take up most of the real estate, with the answer often reducing the need to go to a downstream site. Ex: Paid ads might come, but for now there are either no ads or few ads (below the fold). Both create losses. My expectation is that the losses will accelerate in 2026. Important note: Losses, Recover & Grow will have different answers for different companies. Ex: For many publishers (news, magazine, content), the loss in traffic is already large, and permanent. These entities will need a phoenix type rebirth. I am going to focus on normal businesses: Ecommerce-type entities, B2B & B2C where the earning of revenue is a short, medium, long-term objective. 1. Factors driving losses in SEO Traffic. Informational queries are at the highest risk. These are the what is, how to, and best of queries. They represent, what some people call, top of the funnel. AEs are designed to directly answer these. Commercial queries are close to the highest risk. These are the vs queries, comparisons. Lenovo ThinkPad Snapdragon vs. Asus Zenbook A14. These are very high value queries, AEs will not generate an on-the-fly custom comparison table and even tell you to buy the Zenbook (btw, I have one and it is spectacular!). Non-brand High-Intent Transactional queries are at moderate risk. These are the user typing “buy men’s waterproof hiking shoes for an Alaska trip.” The current UX is that the AE will provide a handful of recommendations, with a summary of why. The user will click fewer times, and your organic category page will be ineffective. Branded & Navigational queries are at low risk. These are “Kate Spade Black Friday Sale.” Or “Coach Tabby in loved leather.” The AE will deliver the traffic to you, as that is the intent of the human. In future iterations, there might be insertion of things like “site links,” which might be a small risk. [Bigger lesson: Brand Marketing has never been more critical!] So, what’s the potential loss through the year 2026 of no AEO action by your company? Let us assume you currently get 5,000,000 visits from Organic Search, and the Revenue Per Visit (Total Organic Revenue/Total Visits) is $2.5. Based on my research, conversations with the top LLMs, competitive intelligence tool builders, and my judgment, here’s the section of the model that proposes the potential losses due to SEO (as Users shift from old-school searching to resolution queries in AE experiences): From an anticipated Revenue of $12.5m, a potential loss of $4m is coming your way. [Note: Annual Premium Subscribers received a full working Excel forecasting model, with losses, recovery, grow included. If you’ve misplace it, or are a new Subscriber, please email me.] Your to-do is to go to your Digital Analytics tool and take your current Organic Search traffic and compute the size of your Informational, Commercial, Non-Brand Transactional, and Branded & Navigational. Then, update column 2 (% of Current Visits). The rest of the cells will update and you’ll see your real losses. My assessment of Potential Loss in each row is conservative, and for “strong brand ecommerce” type business. If your business is different, please invest in research and update that column. With so much changing all at the same time, it is difficult to predict user behavior shifts with 100% accuracy. Consider the loss estimates as the best educated markers. They could happen much faster, could take a little bit of time, but if you stretch over the year 2026, you will broadly be in this range. Hence… Time. For. Action! 4. Factors driving losses in PPC Traffic. The threat to Paid Search is different, and just as scary. It is defined by two words: Transformation, and displacement. Remember, for now, none of the LLMs have advertising as a business model (though, it is too lucrative to resist ads for monetization). That’s displacement. Google, with the largest Search business to protect, will surely have ads in AI Mode, but for now they will look different and seem to be below the fold. Bing is trying new ad formats in its version of AI Mode. This is Transformation. Translation: Fewer options for you to pay to get clicks. Let’s use the same categorization as SEO to reflect on risks. Informational queries represent the same high risk of loss. Setting aside the no ads and below the fold ads issues, the entire purpose of Answer Engines is to answer. Hence, budget spent on informational questions will likely be completely wasted. The User is likely to ignore the ad, and certainly not scroll for ads below the fold. Commercial queries hold a giant point of friction. Our paid ads for, say, “best shoes for hiking,” will compete with the Answer Engine’s AI-analyzed answer for… best hiking shoes! Unless by the grace of God your brand was the AI’s assessment of the right answer, your text ad will lose the fight for attention. Non-Brand High-Intent Transactional queries are likely the bulk of your current ad spend. Ex: buy waterproof hiking shoes for a trip to Alaska. The risk here is not elimination, rather it is format shift. Ex: Text ad slots with breadcrumbs are being replaced with one (or two) AI-powered carousels. The four ad slots were clearly visible; in a carousel format that might not be the case. AEs are likely to have new approaches to Ad Quality Score (tied to now their superior understanding of the user’s intent), this might make it harder for your ad to show up. Other as yet unpredictable ad “innovations.” Branded & Navigational queries, as with SEO, are likely to have a lower risk of reduction. (But, as with your brand keyword ads today, when you measure them today on the basis of Incrementality, using CLS, you will find that they have very low incrementality. So… You should not be buying ads today. Definitely not in Answer Engines either – it is in their vested interest for them to send a user with your brand intent to you. [Note: There is another threat to Navigational and Branded ads. Buying seems to be moving directly into the Answer Engines. This might mean more wins for your competition, and certainly fewer cross and up-sell opportunities for you (lower AOV). Both, not fun.] So, what’s the potential PPC loss through the year 2026 of no AEO action by your company? Assuming $7m annual Visits, with Value Per Visit of $2.5… Here’s my model to help direct your strategic choices: From an anticipated Revenue of $17.5m, a potential loss of $4.6m coming your way over the course of CY 2026. As with SEO forecast, update your Traffic and Value Per Visit numbers from your Google Analytics data. Cluster the keywords you are buying into Informational, Commercial, Non-Brand Transactional, and Branded & Navigational. Update the column titled “% Current Visits.” The rest of the cells will fill in. Compute your potential losses. Take both of these tables to your next CxO strategic conversation. Have a good group cry. Then, start a little Marshall project to kick off urgent action. A Humbling Realization. Recognizing that every company is unique, even similar ones, and hence predicted outcomes will vary… My assessment here of the potential Loss for each query cluster is conservative. Additionally, I’ve assumed that you do everything I’ve urged you to do in TMAI #469: AEO Exp & PPC, TMAI #470: AEO Content FTW. If you have not, the non-positive impact will be significantly higher. So, pelase do not delay understanding and the urgent need to influence your company culture. The Modeling Journey Continues. Good news: You can recover some of your losses! Excellent news: You can take bold action right now, earlier than your competitors, to grow your traffic and revenue in an Answer Engine world!! The grow possibilities are substantial for some industries. TMAI Premium editions #483 and #484, outlined specific Recovery and Growth actions, and anticipated positive percentage impact of each action. They would specifically apply to ecommerce-type entities, B2B & B2C where the earning of revenue is a short-, medium-, and long-term objective. Using the format above, the model offers the same for Paid Ads. If you are a new Premium member, you can email me for the complete forecasting model. Bottom line. Every user behavior transition brings adjustments that businesses have to make. This is one such moment, happens to be the once-in-a-generation kind. Even when so much is unknown, you now have a clear and helpful model to start to quantify the size of the impact. That gives you power to take control of your destiny. Get your team ready to recover, and even grow. Carpe diem. PS: As you execute all of my recommeded actions, you’ll have an intelligent program of Answer Engine Analytics (AEA) to measure success, identify new opportunities. Here’s a helpful sketch, by our friend Gemini, of my Big 5 recommendations:
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AEO: Answer Engine Analytics | Best Reports, KPIs, Metrics.
SEO served us well; it remains a revenue driving powerhouse today, and will do so for the near future. As humans shift FROM “keywording” for 10-blue links to do all the work themselves TO typing resolution questions to have the LLMs do nearly all the work… Answer Engine Optimization (AEO) becomes an exciting next step to ensure continued revenue growth. Answer Engine use is accelerating. They are doing all the work of influencing the human, helping make end point decisions. Result: Conversion Rates from AE visitors are massively higher! Seer Interactive: ChatGPT traffic converts at 16% vs. Google organic’s 1.8%. Link. Ahrefs: 0.5% of the traffic is from AI Search, it is responsible for 12% of signups. Link. SEMrush: AI visitors are 4.4× more valuable on average than Google organic. Link. These numbers are early blush, they will settle downwards. But, I anticipate AE Conversion Rates will be significantly higher than the avg ecommerce CR of 2% – these humans will be arriving pre-influenced. To take advantage of this delicious upside, you need to urgently allocate your Digital team’s focus to AEO to ensure Answer Engines recommend your Brand. To do that well, you’ll need to embrace Answer Engine Analytics. (AEA) This blog post was originally published as edition #473 of my newsletter, TMAI Premium. Each week, the newsletter shares strategic frameworks and practical here’s how to stay at the very bleeding edge of CFO-proof Marketing and Analytics. Sign up for TMAI Premium to accelerate your career trajectory. Answer Engine Analytics: Big Picture. To do AEA intelligently, you’ll need a new tool to identify where to focus and accelerate what to do. To do that without wasting time/money, it is critical to understand: 1. key higher order bits re how Answer Engines work, 2. four methodology questions to ask an AEA tool, 3. the Big 3 Success KPIs and 4. three helpful Diagnostic Metrics you need to leverage for deep insights. [TMAI Premium Subscribers: Please reflect on the comprehensive AEO playbook across TMAIs #468 through #473. For today, it is critical to reviw TMAI #472: Answer Engine Analytics: Methodologies & KPIs. If you can’t find it, or you are a new Subscriber, please email me.] With that clarity settled on your brain, it is time for insight-filled analysis! I’ll teach analysis via two tools I use: Evertune (paid solution, with depth, breadth) and Gumshoe (one free report available, a fascinating approach using AI-built personas). [Disclosure: I made a tiny, tiny, tiny angel investment in Evertune in Oct 2024.] I use a six-step process to power my Answer Engine analysis, to glean actionable insights. Regardless of the tool you use, I recommend this approach. First, critically assess the methodology powering the tool (lots of “magic beans” around), and the definitions of the KPIs (it is not unusual for two tools to have a Visibility Score metric, but measure entirely different things). Step 1. Analyze the Word Associations. Our objective is to identify clusters that are small that we want to be big. 😊 As we discussed in depth in Premium # 470: Bye SEO, Hello AEO, a ton of your earned influence in LLMs will come via a custom 1P & 3P Content Portfolio Strategy. The Word Association report is a good place to start as it shows the most common words, and their sentiment, when AI models describe your brand. [Note: Aided Awareness.] Evertune asks each model (DeepSeek, above) to generate reviews – repeatedly to capture a wide range of responses, realizing these models are probabilistic and not deterministic (see TMAI #472). The frequency with which a word appears is its Association Score (0 to 100 scale), how positively and negatively the word is used is the Sentiment Score (-100 to +100). Each Answer Engine understands you differently. Compare above report for DeepSeek with below for Gemini. If the large green words are the ones you consider most important for your Brand, celebrate. If they are not, you have a perception problem to fix. I would rather the large green words in Gemini were the ones in DeepSeek… And that right there gives me my to-do list re AEO. If you are self-critical like me, you will only see the red words. 😊 As Longchamp, I’m getting hosed on Gemini. As Google has shoved Gemini into most of its products, a negative sentiment across them is a big brand problem. Another actionable add to my to-do list. Step 2: Understand Consumer Preferences. Word Associations are a good start, next question: In what context were these words used? Hence, it is important to understand the consumer journey view as the researching humans see it (and NOT as me the company prefers they see it!). Consumer Preferences are specific attributes humans ask about when researching a category. And, how likely is my brand to appear unaided (the ultimate test). Here’s my awesome Evertune custom report, with Gucci as my competitor and ChatGPT as my model… Coach is crushing it on Price, Functionality, and Durability. Yes! It is important to appreciate that all of the above performance vectors are identified by the AI (and not the human or Evertune). This is super helpful as it shows me what the Answer Engine/LLM thinks is most significant about my category (handbags). These are topics AI will proactively talk about when helping the user decide on trade-offs. This is freaking gold, because I can now specifically identify where to focus my AEO efforts. If Quality or Style is my actual big deal, the data shows they should be high priority focus areas. With any tool, spend time internalizing where the data comes from. In case of Evertune, it will: A. Ask (remember unaided) a number of unique prompt variations. One variation of many, many: Which handbags are known for outstanding durability? Can you list handbag brands that offer excellent style? B.Sample a massive number of times to weed out noise and identify statistically significant patterns – a key competitive strength for ET. As you take action, you can track your performance across Answer Engines and over time using the metric AI Brand Score: Focus is key. I recommend the highest priority be placed on ChatGPT (approx. 650m MAUs), then Gemini (approx. 350m MAUs), and then DeepSeek (approx. 97m MAUs). We’d established that the opportunity for Coach was not Visibility Score, rather it was Average Position. (See TMAI #472 for metric definitions and reports.) As you improve your content creation AND distribution strategy in focused performance vectors, you can review the improvements in the focus KPI of Avg. Position. Look at Kate Spade! Maybe grab the new Duo – it has been deemed cool by GenZ. 😊 Step 3: Identify Content Creation Focus. With our focus words identified, further refined by the performance vectors we want to focus on… It is time to write content to build on your strengths and combat the brand’s weaknesses. In Evertune, in the AI Education Brief section, I can create a new brief by choosing the Product Category (handbags for me) and my focus performance vector (style). It goes off to the races and in a min, spits out the top three content creation recommendations that most resonate for Coach with Answer Engines. The messages that will improve my Visibility Score and Average Position, the stories that I need to tell (inspired by the keywords shared above). Very SEO, no? Different tools use different approaches. As an example, Gumshoe has anchored its approach on AI-built Personas. As someone who has advocated for intent-centric marketing, See-Think-Do-Care, I am unaligned with a Persona-driven approach – it ends up making our customers into unhelpful caricatures. Noting that worry, I appreciate what Todd is trying to do. Gumshoe identifies content creation focus areas, in columns, by your potential personas, in rows. In cells is your brand’s current visibility. For the performance vectors you care about, from Evertune, you can also prioritize content creation using the columns above. As with Evertune, blue image above, Gumshoe helps you get started. I love how easy it is. Click on one of the boxes, and it’ll help you create a first draft of FAQs you should post on your site. For Coach, I selected the persona Social Media Trendsetter and improving visibility for the topic Fashionable Statement Purses for GenZ. Gumshoe helpfully provides a bunch of FAQ questions, with AI written answers as starting points to influences LLMs. Two notes of caution. Caution 1: Remembering the lesson in TMAI #470, I recommend human writing the answer so that they are “AI Resistant” (definition: Of genuine novelty and depth) – because anyone can have AI write content, but there’s only one of you. Caution 2: It was never easy to fool Google, but it is really not easy to fool Answer Engines. For a simple reason: LLMs have way, way, way, way, more sources, across text, audio, video, that influence their “belief system.” Hence, if you have a weakness that is legitimate, it will be extremely difficult to trick an LLM into “overcoming” that weakness. It will know you are lying. Because tens of thousands of other sources confirm your lie. My advice: Spend your energy fixing the source of weakness across your products & business practice. Step 4: Create a Content Distribution Strategy. In TMAI #470 (More content, more places, more often], I’d shared a custom content distribution plan for Coach and a company that owns Auto Dealerships. 3P Content, thus far, seems to have significantly higher influence on AEs. To create your own, in Evertune identify the Domains that are important for your Brand… Brand Share of Voice (bSOV) is calculated by taking the top 50 domains, estimate how many pages are relevant to the product category (handbags, for me), and then what % of those pages include the brand (Coach, for me). Ex: Bag Vanity has an AI Education Score of 10.0 in our category. Coach’s bSOV on it is 6.7%, LV is 10.2% and Prada is 7.5%. On Marie Claire, Coach is 1.5%, Prada is 12.1%. A simple way to identify the domains you should prioritize. A nuanced lesson, stay with me: Domains can influence an Answer Engine, without being cited as a source in the answers presented to the human. Ex: This blog, Occam’s Razor, might have taught Answer Engines a lot about Digital Analytics because it has 0.8 million words written by me, and 1.7 million words in comments written by readers. BUT. When you use ChatGPT, it might cite others (ex: more recent sites). Hence, the important role of Sources Analysis, it shows the citations, references, other links actually shown to the human user of an AE. As a business, it is fine if you are not the domain the AE is learning from. It is Not Fine to not be part of Sources. Humans click on Sources in AE replies, that is how they find you. I would prioritize a focus on Citations and References. You also see above my prioritization of ChatGPT based on data. Your Earned Media team (PR, Affiliate, SEO, etc) now has a to-do list. Gumshoe, takes a different approach to helping you build a custom 3P content distribution strategy. You can view the companies AI pulls from when mentioning your brand (Top Sources), then you can break down visibility by type of website driving awareness where you could be underrepresented (Source Type). I click on a Source Type and choose Blogs/Content sites, and for Coach I get the actual sources cited by the models when answering questions. I click on Marie Claire, and I get specific links to Marie Claire, as well as my competitors being mentioned. [Nuance: The mention is referring to the brands mentioned in the prompt or answer, not necessarily the Source. Still very helpful, but worth being aware.] This is another way to approach the to-do list for your Earned Media team. Important Reminder: In TMAI #470, my Action #10 was a recommendation for you to merge your PR, Affiliate, SEO and Content teams into a single entity called “Answers Quality Team.” If you don’t break these silos, chances of sucking are higher. Step 5: Monitor Impact, with Big 3 Success KPIs. For AEA, at the moment, AI Brand Score, Visibility Score, and Average Position are the Big3 KPIs. Across tools, they can be measured differently. Please check the root definitions before you use any tool, or, god forbid, multiple tools. Given our prioritization of Average Position as the More Important Opportunity, track improvements. Like so in Evertune… The second priority will be to track changes in the AI Brand Score across priority AEs (ChatGPT, Gemini, Deepseek in our case)… Really superb performance by Coach! Finally… Google used to change its core algorithm occasionally – with huge consequences for all of us. LLMs seem to launch a new version like every other week! Hence, as we reflected on how AEs work in TMAI #469, #471, it is important to keep track of our Big 3 Success KPIs as models change. Here’s what that looks like in Evertune… What’s difficult to isolate at the moment is why? Ex: Coach went down by 3, probably not significant. Kate Spade went up by 11, that is massive. Why? No idea. We have such little visibility into LLM black boxes, we can only pray to Krishna and Jesus that the next set of weights being used favor our brands. The like to like comparison in the colorful bar chart above will help us identify with some measure of causality of our Content Creation and 1P + 3P Content Distribution strategies. Step 6: Get Your House in Order! Welcome LLM Bots. In TMAI #469, I’d underlined the importance of your site & mobile app experience, your internal site search to meet evolving customer preferences AND for Agentic AI. As you do steps 1 thru 5 above, don’t forget that you could have barriers on your site. Two reports you should shower your Corporate IT team are: A. Page AE Insights: How does an Answer Engine understand an important page? The sweet Content Retrievability Analysis report from Gumshoe analyzes a specific page through the eyes of an Answer Engine. It automatically generates questions related to the page, reports Citations Found and Citation Rate. The above report is for Kate Spade’s Duo webpage. It has a decent Citation Rate. But, the key is in digging into each question and seeing the Answer Engine’s understanding of that page. If you open the above image in a new tab, you’ll notice that the AI Response, top right of image, is wrong, wrong, really wrong. Like terrible. The LLM does not understand us! And… That is our fault as a brand. Why? B. Page Quality Analysis: Is our page understandable? To answer why, you would look at the second report… These results are so, so, so bad, that through my tears I convinced myself that Gumshoe is a garbage tool and not functioning right. I decided to double-check. I ran the same report for the webpage of my favorite jacket in the world: Patagonia’s Nono Puff. Damn it!! 😢 I guess it is not the tool. Ok. Deep breath. The Page Quality Analysis report helps explain why the Page AE Insights report showed a poor understanding of our page and product. An AI Optimization Score of 5.8% perhaps does not deserve to be understood. My feelings are hurt, but I get a clump of helpful metrics. I can dig deeper into understanding why each score. Ex: The Content Balance is low because we need to “add comprehensive product description and details, include relevant product specifications and features, provide customer review content.” Etc. Action time for our IT team. Six simple steps, in order, that will unlock specific actions you can take, starting now, to attract pre-influenced by Answer Engine humans. They might be small in numbers, but they convert into customers at a rate multiple times higher than your site average. Bottom line. A change of this magnitude comes once in a generation. It also comes with the innovator’s dilemma. The change in consumer behavior is small numbers for now. It is comforting to sit in your old SEO cocoon, with its still big numbers. The danger is that by the time you realize you should start changing… You are in deep, deep, trouble. Remember, a whole bunch of non-brand traffic you are currently losing every day will never come back. Across the six editions of TMAI, I’ve shared 70-pages of comprehensive analysis of the problem, the four clusters of opportunities, and over 50 specific actions covering Marketing, Content, Analytics. The time to start is now. Carpe diem.
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AI Age Marketing: Bye SEO, Hello AEO!
My YOY computations indicate, as you head into 2026, you are going to lose 30% of your Organic Traffic from reduced opportunity, and 15% of Paid Traffic from reduced inventory. I’ll share tactics that’ll help you recover about half of your lost traffic. As of Aug 2025, my assessment is the other 50% will be gone – permanently. Most companies are unaware, hence doing nothing.😢 The challenge: Nothing seems to change for a while, then as if overnight everything changes. We are living through one such moment. Here’s data related to nothing seems to be changing: As of July 2025, ChatGPT received 2.5 billion prompts from global users. That’s smaller than Google’s 14 billion daily searches, but growing. (Note: Prompts and Searches are an imperfect comparison, but an indication of relative growth/size.) Gartner: Traditional Search volume will decline by 25% by 2026. (In 5 months!) SparkToro benchmarked that 58% of Google searches were already zero clicks (IE no click after search results are presented), a number that is 70% now. Ahrefs identified that the presence of AI Overviews (that little paragraph on top G SERPs), reduced clicks by 35%. Sites providing informational content (“what is,” “how to”) are experiencing Organic traffic drops ranging 18% to 64%. Ex: Biz Insider -55% (04/22 to 04/25). Chegg: -49%. Decrease in CTR of 15% to 20% from PPC since AI Overviews launched (largely impacting “non-brand” keywords). The nothing seems to change phase can last a while, lulling you to complacency even more. Ex: Reflect on how little you’ve done to deal with the above. Today, my sense is we are nearing the point of overnight everything changes. To ensure you are ready, I’ll illuminate the impact of all the underneath changes that have accumulated and outline immediate Answer Engine Optimization (AEO) actions you need to take to be ready for the overnight everything changes. Your SEO skills remain important as you embrace the new skills required for effective AEO. Please join me in being scared. Please join me in overcoming inertia, lethargic Senior Leaders, to increase agility and the pace of change. Please join me in AEO! [Branding: I did not want the new name to be based on the tech (“generative”). Tech changes. Hence, my name honors change in the consumer experience. No, GEO. Yes, AEO.] This blog post was originally published as edition #468 of my newsletter, TMAI Premium. Each week, the newsletter shares strategic frameworks and practical here’s how to stay at the very bleeding edge of CFO-proof Marketing and Analytics. Sign up for TMAI Premium to accelerate your career trajectory. What the heck’s going on? This: Search is changing to Answers. The foundational interaction model has changed: Past: I am so clever, just type a key word or two and I CAN GUESS WHAT YOU WANT. Present: Talk to me like a human, don’t be shy, type/speak as much as you want, and tell me all the nuances. I’m insanely delighted about this… The UX has changed: Past: Here you go, 4 Paid and 10 Organic links to help you do all your homework. Present: I’ve done all the homework; here’s the answer. New normal: Past: Search Engine. Present: Answer Engine. It is the most meaningful customer-centric improvement in Internet’s history. It has 100x sped up me getting to an answer. It is a much better answer. In a drastically better user experience. [It reminds me of the Blackberry to iPhone user experience shift. Changed everything.] Let me make this real. A simple but layered task: My parents are visiting. I’m taking them to Eataly as I love it. At their age, without tiring them it would be great to show them nearby New York bits they might enjoy. I know which Eataly I want to go to, but I don’t remember the address (I belong to navigate by landmarks tribe!). Because of how Google has trained me for 15 years, I would not think of using it. What would the keywords be? I go to my favorite Answer Engine, ChatGPT, and type a short but layered question: Could you please recommend tourist places to see within a couple of miles of etaly which is near flatiron building. Answer Engines are so new that the experience still blows my mind… First, notice it answered my simple layered, perhaps complex, question precisely. I do not need to go to 10 links to figure it out myself. Next, notice how excited and encouraging ChatGPT is in the first paragraph. With Google, I’ve always felt I was talking to a machine (and that was totally fine). With ChatGPT, I forget I’m talking to a machine – which is why I instinctively say please, thank you. Then, notice the smart elevation of the information’s usefulness. I did not ask for distances or context, but it anticipates: 10 mins to Empire State, and directly across for the park. Finally, notice it going well beyond the call of duty. It gives me Museums and Culture! (Though, I wonder if I’d said I’m visiting with my parents if it would have listed the Museum of Sex first.) I was delighted it gave me helpful snippets: Focuses on Himalayan & Buddhist art. I can choose faster. Oh, oh, oh… It did even more below the fold… Foodie Finds (the “besides Eataly” is such a clever touch)… A freaking custom mini walking tour just for me! With super helpful tips (“enter at 23rd st”). Not one from an expert or influencer which might be a good start but will need tweaking by me. If you switched to Answer Engines already, you are a little used to this radically better user experience. Can I tell you… Even as I’m typing this, seeing this image for the 10th time, it still brings me joy to reflect on just how exceptional the answer and the user experience are. The cherry on the cake, the last line. My next query: Type in my age and my parents ages, and it gave me an even more customized mini walking tour – which we could finish in 45 mins. This is the new normal. [Note: On this day, I started to pay for ChatGPT Plus – though the free version sufficed for me.] Much has been made about AIfication of Google. What if I typed the same question into Google? The Very First Thing Google does is make me feel bad about myself. It tells me I misspelled Eataly. ChatGPT did not think it was important to tell me I misspelled Eataly. It understood the Flatiron building location context and automatically made Eatly into Eataly. Google read Eatly as Italy. Google’s experience above is heartbreaking. Other than go figure it all out yourself on Tripadvisor, it is a tsunami of irrelevance: Listing my misspelling on the top (useless), Overview of NYC on the right (useless to the max), Facebook and Quora links (irritatingly useless), the People also ask (completely useless). Give me a moment to get a napkin to wipe my tears. I spent nearly 16 years at Google, this hurts my feelings. sniff. sniff. sniff. Ok. Ok. I’m back. See what I mean by the difference between Search Engine & Answer Engine? We are not in Kansas anymore. Don’t trust me. Go to an Answer Engine (ChatGPT, Perplexity, Claude, Mistral, others). Type/speak your questions, in their full multi-layered, complex, nuanced glory. Speak like you would to a human. Try this common commercially intent use case… I’m a cyclist. Like me, being patterned to think keywords by Google, you type: “best wireless headphones.” Please try it in your browser, so Google uses all your personal history it has learned. What does it show? Now, go to ChatGPT and act like a human by typing in the question you really have: “As an expert in consumer electronics, can you recommend affordable headphones for outdoor cycling, with great sound and fast charging.” What does an Answer engine show? For me, here are the results: Google: 1. Normal search, keywords. 2. Normal search, complex question. 3. AI Mode, complex question. (I’ve used Google’s default search experience, as it is what everyone uses. But, please switch to Google’s AI Mode for a direct comparison. You’ll discover it is anodyne, less anticipatory, and has a worse user experience than Answer Engines. Click link above.) ChatGPT: 1. Complex question. 2. Follow up question. (It is delightful that ChatGPT always suggests a polite, can I do more.) Claude AI: 1. Complex question. We are going to discuss Agentic Search in the next newsletter. To experience how Agents working for us might think, feel, and behave, check out Mistral’s “Deep Research” mode results for my complex question. Fly in the Ointment. If all this is so great, what’s the problem? This: Customers win. Brands lose. We were so used to getting a ton of traffic from Google. We will get less. How much less will vary by industry (and how savvy you are at AEO). The losses stretch beyond traffic. Here are three I anticipate hurting: A. As a customer I would have visited 15 sites to figure out the answer if I used a Search Engine. Now, I visit zero. Traffic reduction problem. B. During those visits, I might have noticed the site’s name, url, colors, something, remembered it for a future visit or recommend it to friends. Now, I don’t know where the answer came from. Brand growth problem. C. If I’d used Google, because all it educated me was to go to Tripadvisor, I would have done that and might have booked a mini-walking tour there. Now, I don’t need to visit or buy. In cases with commercial intent, headphones, I’ll buy the first one and never consider you. Revenue problem. You get why the numbers on top of this newsletter scared me? If you are not freaked out, if you still have an old school SEO team/agency vs. AEO… I fear you are in for a worrying amount of financial pain. If you are freaked out, like me… Good news: I’m going to share tactics that I believe will help you do AEO, and recover atleast half of the traffic you are going to lose – which should help resolve the revenue problem as well. If you are a Premium subscriber, you have read 30 newsletters focusing on every dimension of sophisticated Brand Marketing. In the age of LLMs, effective Brand Marketing is 10x more important. If the age of AI Agents arrives quickly, then 15x more important. Before I share the areas of focus for recovery, a strategic recommendation… Protect Your Google Existence. Also, Ignore Google. Anyone who tells you Google is toast, or not important, is unintelligent. For the near future no one is going to send you more traffic than Google (even with zero-clicks exploding). Most humans use the default Search experience, they type keywords. No one is going to help you make more revenue than Google. Ensure your employees are doing what has worked on Google in the past AND quickly work on any changes Google releases. Also… Actively ignore Google as you imagine the future, or your future will be worse. Google has a gigantic present to protect. Google has been and will continue to be slower to change. Google will take fewer risks. Google will imagine every big new possibility through the lens of adding it to today’s products and features – the innovator’s dilemma vortex has outsized gravitational pull. Google’s workforce of approx. 300,000 FTEs & TVCs has intense cultural and financial incentives to be wired for the present. That’s not unique to Google—it’s what happens to every company at this scale. Lean instead on Claude, Perplexity, OpenAI, Mistral’s vision of the “future of Search.” Not because one of them will be the next “search” monopoly. More because those companies have no present to protect, less to be harmed by making bold, true customer-centric bets, and they are 50x more likely to imagine entirely new possibilities re products. They will deliver the “future of search” faster. Learning from their moves will ensure your strategic imagination is upgraded faster, and is bigger, broader, and awesomer. If Google retains its Search dominance, you’ll be ready ahead of the competition and win bigger. If someone else becomes the new Google, you’ll be ready ahead of the competition and win bigger. Protect your current Google existence. Ignore Google. Let’s win the “future of Search”, and get our traffic back! For my AEO work, I’ve taken the three problems above (A: Traffic reduction. B: Brand growth reduction. C: Revenue reduction), and converted them into four clear areas of action for my companies: 1. Pre-Search clusters the actions we need to take to understand a foundational shift in user behavior to expressing complex destination questions. In our behavior analysis and on our owned digital existence. 2. Search Experience clusters the actions we need to take to adapt our Paid Ads and Organic “Relevance” strategies and tactics. 3. Pan-Search clusters the actions we need to take to get ready for a world where humans use AI Agents to outsource what we call “searching” and “shopping” today. Early robots to replace humans are already here. 4. Measure Different clusters actions to incorporate above shifts into what (KPIs) and how (Methodologies) we measure. Over the next two Premium editions, I’ll outline thirty specific actions spread across the above four areas. Subscribers can expect a career boost. So, if you are not, become one! (See the money-back guarantee on the Annual plan.) Bottom line. I am genuinely freaked out about the evolution from Search engine to Answer engine. If my company suffers, there is a cascading impact on my co-workers, on me. And, remember, for many, at least half of these losses are not coming back. If I step outside of that self-view, I am genuinely delighted for us humans. This is an instance of AI truly in service of us, saving humanity billions of hours collectively. Once it becomes Agentic… OMG… What am I going to do with all my free time!!😂 Carpe diem.
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Kill Data Pukes: Split KPIs, Diagnostic Metrics & Influencing Variables.
Across every layer of the company, business people get too much data. Hunting expeditions are launched to locate what’s relevant and useful. CMO scorecards have impressions! Agencies are using CPMs, or worse “Traffic” as primary KPI. A Bank’s CMO has NPS on their dashboard – NPS is sourced from everything a company does AFTER Marketing’s done! I now spend most of my time practicing the art of strategy — how to have an outsized impact across the entire business (with an eye to moving Profits). My approach to rolling back the complexity in data pukes, sorry, dashboards, is simple: Separate out the Critically Crucial from Diagnostically Helpful from Minor Bits. AKA Separate the KPIs from Metrics, and both of those from Influencing Variables. That separation dramatically reduces confusion. It sharpens the focus of the Extremely Senior Leaders (ESLs) on what actually matters. It serves notice to the Agencies and Platforms that in-flight optimization is of vital tactical importance, and it is one thing 100% in their control. Win. Win. Win. This allows you to win before you spend, win while you spend, and win the future! As simple as this sounds, so many teams and Agencies find this challenging. To help my clients, I’ve gone and identified what differentiates KPIs, Metrics, IVs across 11 variables. Let me share that with you today. This blog post was originally published as edition #448 of my newsletter TMAI Premium. Each week, the newsletter shares strategic frameworks and practical here’s how to stay at the very bleeding edge of CFO-proof Marketing and Analytics. Sign up for TMAI Premium, and accelerate your career trajectory. Big 3 Definitions. A Key Performance Indicator (KPI), is a metric whose movement directly impacts the company’s bottom line. Not through two or seven connecting steps, directly. Hence, they are typically used to measure a company’s topline objectives. Incremental Revenue, Unaided Brand Awareness are examples of KPIs. A Metric is a number that is used to track performance. Some metrics are directly connected to the company’s bottom line, they are called, KPIs. 😊 More commonly, they are used to diagnose the why when KPIs go up and down. Hence, I use the terms KPIs and Diagnostic Metrics. Cart Abandonment Rate, Audio Video On Complete (AVOC) are examples of Metrics. An Influencing Variable (IV) is a number that most often explains the performance of a Metric. More specifically, an IV explains a part of what’s going on with a Metric (up/down/around). Bids, On-Target % are examples of Influencing Variables. Important: Performance of one KPI will be explained by multiple Metrics. The performance of one Metric will be explained by multiple Influencing Variables. In this example, 1 KPI is explained by four Diagnostic Metrics, and the first Diagnostic Metric is explained by six Influencing Variables! This is not unusual. For any KPI that is directly connected to the company’s bottom line, you’ll have four to six Diagnostic Metrics, and a total of 25 to 35 Influencing Variables. #OMG That should explain why our Reports and Dashboards are such massive data pukes. It also explains why it is essential to identify these three clearly so you can simplify complexity. Finally, now you know why I insist in my Strategic Consulting practice: Please, please, no more than four KPIs for the entire business! [Note: TMAI Premium Members: Please review the detailed, with examples, three-part series: TMAI #337, 338, 339: World’s Greatest CMO Dashboard. If you can’t find it, just email me.] KPIs, Diagnostic Metrics, Influencing Variables: Key Dimensions. I highly recommend you grab your CxO dashboards, gather your team, and go through an exercise to separate KPIs from Metrics from IVs. I’ll give you 1,000 bonus points if for each KPI, you identify the Diagnostic Metrics, and for them, the cluster of Influencing Variables. To help you with this exercise, I want to share 11 dimensions that sharply explain the differences. By the end, even if you would rather not be, you’ll be an Analysis Ninja! 1. Who Sets Them? Your CMO (/CxO) will personally identify the KPIs. She/He will directly source from their strategy, and what the Company expects them to deliver as the incremental impact on the bottom line. Metrics are typically identified by the Director layer in the company. There will be many Directors, each ideally solving for a crystal clear KPI (for the CMO!). Hence, the Director’s success will be ensuring each Metric delivers optimal performance. An Agency will typically identify the Influencing Variables for each Metric they are going to help be successful. If you don’t have an Agency, it will be your internal Agencyish team. [Note: TMAI Premium Members: I cannot stress the importance of understanding this when selecting KPIs: TMAI #400: The 4Ps of Marketing are Dead! Else, you’ll pick KPIs that will lead you to career limiting moves. Email me if you can’t find #400.] 2. Purpose. KPIs, DMs, IVs, each power different run, fix, stop decisions. Should we keep doing what we are doing (run), are there some anomalies that need addressing (fix), is the performance such we need to stop spending money (stop). KPIs run, fix, stop high altitude items: Budgets, entire initiatives, individuals or teams. Metrics run, fix, stop the Marketing tactics underway. Influencing Variables run, fix, stop channel, or tactical, level execution underway for owned, earned, paid activity underway. 3. Time Orientation. This will be super helpful in ensuring your selection is smart. KPIs look at patterns, and influence decisions, over months, quarters, and years. Metrics are simply not that important. They look at patterns and influence decisions weekly, and monthly. Influencing Variables are simply not that important. They look at patterns and influence decisions daily, and weekly. 4. Measurement Focus. Now things get really, really, interesting. For winners who repeatedly win, KPIs use Incrementality as their core methodology. Kissable and huggable Metrics are ones that help focus on outsmarting competition. Yummy Influencing Variables, in 2025, are the ones that press AI execution buttons to let advanced algorithms and intelligence optimally deliver in-flight optimization. (Humans are kind of not good at this much scale.) 5. What’s Measured? I really like this one. KPIs: Outcomes. Metrics: Activity. Influencing Variables: Micro-Actions. Simple and sexy, no? 6. Flexibility. We underestimate this dimension. Sometimes we hold on to things well past their expiration date. Sometimes we judge too fast, and don’t go on a second date. If your KPIs are changing all the time, something BIG is wrong. You have the wrong leader. You have no strategy. Your business is getting massively disrupted. That will be the scale of wrong. KPIs should be questioned on an annual basis, but, if you’ve chosen them wisely, they won’t change for years. Torture your Metrics approximately every six months. Ask this simple question: Have the actions taken based on IAbI from this Metric had a direct impact on our KPI? [Note: Premium Members please review: TMAI #254: Rules for Revolutionaries | IABI] At a tactical level, Marketing and Platforms/Channels have changed at a rapid pace over the last five years, and I anticipate more of the same. Hence, your Influencing Variables might become useless from one quarter to the next. Ask the same question as Metrics, and discard frequently if the answer is no. [Bonus read: Kill Useless Web Metrics: Apply The “Three Layers Of So What” Test.] 7. Life Duration. You can see how this flows from the above. KPIs: Multi-year. Metrics: Multi-quarter. Influencing Variables: Multi-month. A straight-forward assessment. 8. Future Visibility. I wanted to include this, to underline that you really need to sweat the choice of your KPIs. Only the movement in KPIs can help predict that your long-term future will be brighter or duller. Metrics and KPIs simply don’t have predictive power. 9. Need Targets. Absolutely mandatory for KPIs! It is not possible to have focus, discipline, good behavior across the entire organization, without specific, measurable with high-quality methodology, Targets for your KPIs. [More: TMAI Premium Subscribers refer to: TMAI #435: Methodologies Trump Metrics!] If decent quality Analytics is being practiced in your company for two to three years, your Diagnostic Metrics will also have Targets. If you have a super smart Agency, one clear sign of that is that they would have identified specific Influencing Variables for your Metrics, and have run/fix/stop ranges for each Influencing Variable. Those run/fix/stop levels are the Targets. 10. Explains. KPIs explain the impact of your strategic activity on your company’s Profits. Metrics help explain why you missed your quarterly targets. Influencing Variables explain the success or failure of your campaign’s performance. Easy-peasy. :) 11. Where you’ll find them most frequently? This is the issue that started this saga for me. Dashboards filled with Influencing Variables! Your CxO Dashboards will only contain KPIs, and for each KPI they will have IAbI. [See: The “Action Dashboard”] Your Director, and around Director, reports will show the KPI and explain their performance by focusing on the Diagnostic Metrics. The first picture in this newsletter illustrates just how many Influencing Variables you’ll be juggling (actually, your expensive Agency), and hence it is not surprising that you’ll find them in small font data pukes. TMAI Premium Subscribers: If you would like a copy of the Microsoft Excel file with the consolidated view of the 11 dimensions, and one bonus counter-intuitive life lesson, please email me and I’ll be happy to share. Bottom line. Building a data-influenced org is complex, and difficult. It is as much psychology, as it is analytics. It is dang near impossible, if you don’t get the basics right. Now go and gather your dashboards, pull your team together, and to through the exercise I’ve recommended above. Rarely will getting the basics right be this life-altering. Carpe diem.
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