Jon Simmons

AdAttributionKit: Unpacking Apple’s new ad attribution framework AAK unifies Apple’s various advertising attribution frameworks under a single umbrella product name and extends SKAdNetwork in meaningful ways, including with support for re-engagement and alternative app marketplaces. These are substantive improvements. But impediments to adoption remain: IP-based attribution is still widely viewed as a suitable alternative to Apple’s native iOS attribution framework, meaning that platform tools like Conversion APIs will take adoption priority.

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new episode alert: Magnite $MGNI CEO Michael Barrett breaks down the future of independent ad tech. we talk competing with Google, why The Trade Desk won, and what actually works in M&A. Plus some great insights on leading turnarounds: https://lnkd.in/eAKc84Qi

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A marketing measurement perspective that I don't see represented often is that, for a substantial proportion of advertisers, last-click really is optimal. If a fairly new mobile app with low TAM penetration scales exclusively on Facebook, how much actionable insight is gained by introducing complex measurement machinery? While I'm certainly guilty of advocating it, the viewpoint that more sophisticated measurement infrastructure is always better strikes me as overly generalized. In certain contexts, orchestrating experiments or building, tuning, and deploying probabilistic models probably won't meaningfully impact advertising efficiency. And in those specific (again: not all!) contexts, with limited data and a homogenous (possibly, single-channel) channel mix, reducing interpretability and overhead might do more harm than good. Creating complexity where last-click may perform just as well as an ensemble of methodologies doesn't actually optimize the bias/variance tradeoff -- it may not reduce bias sufficiently to compensate for a large increase in variance.

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Meta's introduction of incrementality-based optimization, revealed at Performance Marketing Week in June and officially introduced last week, is strategically shrewd: - Meta has natively facilitated lift studies for years, so it knows that its platform is incrementally accretive; - Meta is the singularly largest publisher for most eCom advertisers, and its contribution is likely being undervalued by psuedo-deterministic measurement solutions; - Meta would prefer to reduce its dependency on direct data transfer, even through server-to-server mechanisms, and it has slowly been increasing its reliance on aggregated attribution data from 3P measurement tools (see: AEM changes last year). Optimizing for incrementality will simply increase platform CPMs while shifting more budget allocation into Advantage+.

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📊 E-commerce Trend Alert: AI Chatbots Driving Traffic 🚀 Yesterday @Glenn Gabe (https://lnkd.in/ex9wCn2e) recently shared some eye-opening stats from an Adobe Forecast: - Online shoppers are expected to spend a record $241 billion this holiday season (up 8.4% from 2023) - In 2024, traffic to retail sites from AI chatbots has doubled - Direct referrals from these chatbots are 8 times higher than in 2023 This got me thinking, are you tracking this trend? If not, here's a quick tip to monitor your AI chatbot referrals in GA4: 1. Login to GA4 2. Go to Explorations 3. Create a new exploration (I named mine "AI Chatbots") 4. Add dimensions: Page referrer 5. Add metrics: Sessions 6. In Rows: Select Page Referrer 7. In Values: Select Sessions 8. Create a filter: - Page referrer matches regex - Use this value: ^https://(www.meta.ai|www.perplexity.ai|chat.openai.com|claude.ai|chat.mistral.ai|gemini.google.com|bard.google.com|chatgpt.com|copilot.microsoft.com)(/.*)?$ This regex captures referrals from popular AI chatbots like ChatGPT, Claude, Gemini, and more. Are you seeing an uptick in AI-driven traffic? How are you adapting your strategy? Let's discuss in the comments! 👇

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Back in 1997, The New York Times highlighted a “Roundtable in Multimedia” attended by senior media executives. They lamented that apart from a few exceptions like pornography websites and Amazon, no one had cracked the code for a viable 'interactive' media business model. Fast forward to 2024, and Fable has launched Showrunner, a revolutionary platform known as the “Netflix of AI" , which allows users to create their own TV shows with just a few prompts. 📺✨ The way we create and consume content has evolved dramatically. But what does "interactive media" really mean today? We break it down, exploring how it intersects with massive shifts in technology, culture, and new media. And how with a growing "Swipe before Type" generation, there is now an ingrained expectation of interactivity in all digital experiences. We dive into the future of interactive media and gaming and see where we're headed next! Link in comments. #InteractiveMedia #Gaming #AI #TechRevolution #ContentCreation #NewMedia

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Following the likes of Robinhood & Salesforce, brands are betting the farm on owned media, but 90% of b2c brands are overestimating their upside. 2 things that differentiate those marquee efforts from most companies: Mass Appeal - Sherwood (Robinhood) and Salesforce+ are going after 2 of the largest audiences, respectively, in consumer investing and sales/marketing. But let's say you operate an insurance marketplace, a telehealth company, or... a mattress company... What are the real odds consumers subscribe to your newsletter? Investment - Sherwood is not messing around. They've hired a cadre of top talent, and then went and bought Chartr to sprinkle on top. You need to be creating a TON of great content to have a chance at creating a real consumer media brand, and too many owned strategies are being built on the back of 2-3 person teams. The truth is... b2c brands need to find audiences offsite, by leveraging their content/data into earned. Tell interesting stories, and create relationships that allow you to syndicate those stories at large.

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Announcing Aperiam's Latest Investment: Gigi! 🍒 Aperiam continues to make strategic bets in commerce media and CTV, the fastest-growing segments of digital advertising. With Amazon Ads being the largest commerce media channel AND the fastest-growing Streaming TV ad platform, we are excited to introduce our latest investment: Gigi. Why Gigi? 1) The product. Gigi’s unique ability to integrate a brand's first-party commerce data with Amazon's data for audience enrichment and deterministic omnichannel measurement sets it apart. This powerful combination enables brands and agencies to buy and measure Amazon Streaming TV ads more effectively. 2) The team. The founders behind Gigi consists of experienced commerce media executives - led by cofounder and CEO, Adam Epstein - who have a bold vision for the future of Streaming TV, commerce media, and data collaboration and a history of success in commerce media. Their expertise ensures that Gigi is at the forefront of innovation in this space. We believe Gigi’s capabilities and the vision of its team will drive significant advancements in how brands leverage data to enhance their advertising strategies on Amazon’s platform. Check out Gigi here: https://gigico.tv/ cc: James Borow Joe Zawadzki Danilo Tauro, PhD

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Has anyone ever sized the market opportunity the measurement/verification/attribution/optimization companies are fighting for a share of? Are long-term projections tethered to assumptions using math like we expect X share of a market sized Y, yielding revenue Z, margins A = valuation B? I suspect the pie is finite and not going to grow enormously, so in the end there is only room for a handful of players. And someone is going to have to lose significant share for even that to work. Especially as long as the sell side is paying most of the freight (directly and indirectly).

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Last night, while in town for GAI Insights #GenerativeAIWorld, I co-hosted a dinner with long time friend Dave Balter and True Ventures, gathering top minds in AI, VC, and entrepreneurship in Boston. BrandRank.AI CTO Matt Cox (based in Boston w/our tech team) and investor Bill Hildebolt of gen.video joined us. We dove into how AI is revolutionizing productivity across industries. The consensus? AI literacy is becoming as crucial as digital literacy was a decade ago. Our discussion centered around four key themes: - AI'S IMPACT ON BUSINESS: From automating tasks to enhancing decision-making, AI is transforming how companies operate and compete. - HUMAN-AI COLLABORATION: We explored the potential of AI as a creative partner and decision-making tool, and the implications for various industries. (Perfect timing for CincyAI for Humans (CincyAI) one-year anniversary celebration today.) - THE FUTURE OF WORK: We debated which jobs might be displaced, which new roles will emerge, and how to prepare for an AI-driven workforce. - ETHICAL AI AND BRAND PERCEPTION: Our work at BrandRank.AI is showing how AI can reveal uncomfortable truths about brands, raising questions about transparency and authenticity. (Are LLMs are too smart for BS!) What jumped out in the conversation is that AI isn't just a tool – it's becoming a collaborator, creator, and potential competitor. Are we ready for AI in boardrooms, creative processes, and as the primary interface for brand interactions? The entrepreneurial energy was palpable as we explored opportunities in AI-driven health monitoring and human-AI creative collaboration -- this balanced with ethical considerations and the responsibility we bear as leaders in this space. The future of business is AI-collaborative. Are we prepared to be good partners? This discussion echoed the conference's sentiment, bolstered by outstanding presentation by MIT and HBS faculty: we're in an unprecedented moment of disruption. It's not just a technological shift, but a fundamental reimagining of work, creativity, and interaction. (Amazing conference so far Paul Baier, John Sviokla Liz Vanzura) Great time to be an entrepreneur! And the ultimate test for leadership! Thanks Dave, Gus Coldebella and True team for great and timely conversation. Kelly Cohen Hank Hudepohl Carl Fraik Aftab Pureval Kendra Ramirez Christopher Brock Jon Salisbury Helen Todd (Human) Jon Salisbury Jack Wyant MJ Price 🌱Lauren Morgenstein Schiavone Judy Zitnik Christopher Morse Christy Page Jocile Ehrlich Lee Beech Tracey Cooke Sherrie Kinderdine Adriana Altuve Chetan Parekh Diana Takach Jonathan Carson

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Adtech M&A is certainly heating up. Last week Digiday reported that Teads is exploring various sale options. This kind of news piques our Quo Vadis curiosity. So we did our best to puzzle together a fundamental valuation model. As imperfect as it may be, our model tells us that $2.2 billion is close to the magic number. Get the details and see how we get there: https://lnkd.in/ee6wEyXM Subscribe to Quo Vadis to follow this very interesting adtech valuation story! #adtech #programmatic #radicaltransparency

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What’s wrong with Nike is that they’ve been running a mid-2000s to 2014 playbook. It reminds me of so many early internet advertisers who spent millions on last cookie attribution. Unfortunately, that game is still alive and well into the billions. In Nike’s case (and so many others), they are all in on performance advertising. Direct-response display. Google search to the (p)max. Then they have “brand”, and there is no connection between them. Approaching advertising like this means chasing metrics that aren’t real. Here’s an example. Imagine Nike sponsors a bunch of athletes at the Summer Olympics and they’re all wearing a uniquely branded yellow shoe. Then they run some inspiring tv spots to tap into the emotion of the games. My son sees all of this and thinks the shoes are sick and searches for them on Google, and gets directed to buy them on Nike.com. If you’re just focused on the last touch, you’ll buy more Google search and ignore the brand spots and athlete sponsorships. “Sponsor less athletes. Buy less TV.  Buy more Google.” Of course, that’s insane. That is essentially what so many brands are doing with their marketing today. Nike is not alone. They don’t understand there’s not a top of funnel and a lower funnel, really. The two are connected. If you’re just doing lower funnel, you’re largely getting the people you’d get anyway. It’s a question of attribution versus contribution. If you spend more money on channels that are geared for attribution, you’re just “attributing” credit for sales that you were already going to get or are being driven by channels/tactics that are responsible for creating that demand. Unfortunately, Nike optimized out of those channels/tactics that were actually creating demand like they did in the 2012 Olympics because they chased the fools gold of Google’s attribution game. The best time to change direction was yesterday. The second best time to change direction is today.

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Ten years ago brands like Zillow and American Express nailed it as pioneers of brands launching media companies - while hundreds tried and failed. Now we're in a new era for brand publishing... What's different? 🚀 The Journey For the brands mentioned above, the strategy was a success. But many brands struggled to find their footing, leading to the shutdown of countless content initiatives. Today we’re seeing a resurgence and a true new era for brand publishing, fueled by lessons learned from past challenges. 🔍 What’s Different Now? Today, successful brand publishing has 3 important components: 1. Distribution Focus 2. Strategic ROI 3. Measured Investment. More on this in my latest article - link in first comment. #BrandPublishing #ContentMarketing #BrandJournalism #EarnedMedia Image Credits: Roman Samborskyi - Shutterstock

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I recently sat down with The Current to discuss Walmart's acquisition of Vizio and why it's a BIG deal for retail media. Here's the TL;DR: • Shopper data > retail margins: Walmart follows Amazon’s lead by building a closed-loop advertising ecosystem that converts shopper insight into $s. • 1 + 1 = 3: Vizio's ACR data combined with Walmart's shopper data is a massive revenue enhancer that shouldn’t be underestimated. • Beyond CPG: This isn't just for big brands. Retail media data can be valuable for all kinds of advertisers. • The new third-party data? As cookies crumble, retail media data offers a scalable and transparent alternative. Check out the full Q&A here →  https://lnkd.in/gxTf9Eiz

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Trust and transparency is key to business growth and one must play by the book always 👍

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Exciting New AI-Powered Updates from Google Ads 🚀 We’re thrilled to announce new features in the G-Ads platform to supercharge results... 🌟 Asset-Level Conversion Reporting for Performance Max + Gain transparency with conversion metrics. + Optimize your creative with detailed insights. + Ensure brand suitability on YouTube and Display. 🎨 Expanded Generative AI Image Editing + Add, remove, or replace objects. + Expand backgrounds and crop to different ratios. 📱 Asset Generation for App and Display Campaigns + Accelerate creative asset building with improved AI tools. + Access new image generation models for better performance. 🤝 New Creative Partnership with Typeface + Seamlessly integrate assets from Typeface into Google Ads. + Follow best practices with provided templates for Performance Max. + Stay ahead of the curve and elevate your ad game with these powerful tools! https://lnkd.in/g8T5MzXi #GoogleAds #DigitalMarketing #AI #CreativeTools #PerformanceMax #Innovation

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There's a new growth strategy on the block. And I'm dubbing it "The U-Haul Playbook." It's when a founder moves to where their target market lives. Not everyone can do this. Few should. But the real takeaway is in understanding why this matters. Customer discovery is the most important activity for a startup founder who is in pre-market phase, MVP phase, or seed stage. Spoiler alert: the importance never ends, but the tactics can change as you grow. I wrote a bit about this trend and how to think about customer discovery in my latest beehiiv for Five Four!

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Wooooow! Who could explain it pls?! O_o zero budget for advertising, SEO, context, social, etc - zero, no money at all. The image&data provide analytics for a link https://lnkd.in/eSAT_9VF, which redirects to my new book on https://amzn.to/3NYxnSc Amazon page. Here’s a breakdown of what is displayed: Human clicks - 14,000 (Redirects: 22,000) Date Range: November 8, 2024 – December 8, 2024 (The peak traffic occurred on December 5, 2024 with 2,601 clicks - why?! O_o) Top Countries & Top Cities: Singapore: 86% (12,000 clicks) Woooow O_o United States: 12% (1,756 clicks) Other countries include Indonesia, Belgium, India, and more, each contributing marginally. London: 11% (1,580 clicks) Other cities include New York City, Jakarta, Santa Clara, Mumbai, etc. Top Browser: Chrome Mobile Web (93% of clicks, 13,000 users). Top OS: Android (98% of clicks, 14,000 users). Most traffic comes from unidentified sources (99%, 14,000 clicks). A small portion (0.3%) from nansen.id. Most social traffic is unidentified, with a small fraction attributed to Google.

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In today’s Marketecture newsletter, in the context of the recent attention directed at the business model of Honey, the POS coupon surfacing service, Ari Paparo asks whether CMOs should be intimately familiar with the machinations of their marketing channels. My response is that they absolutely should — that understanding where budget is deployed and how those recipient channels deliver value is the essence of the CMO role. I don’t think there’s any level of altitude, or any scale of operational complexity, that absolves a CMO of that obligation. But this doesn’t necessitate that a CMO fundamentally understand the business model of Honey (or any other affiliate-like channel) specifically. Rather, it entails instilling a culture of disciplined analytical rigor within the organization. A CMO can be completely unaware of Honey’s commercial model while still demanding that the marketing team test it (and every other channel) for incremental impact.

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