Rob C.

On paper Boost Mobile x Liquid Death have no business doing a collab. In culture it makes perfect sense. There is no overlap of products, distribution, or consumption occasions. So why would they team up if there is no category adjacency. What matters here is shared positioning. Both brands define themselves as disruptors in industries where consumers have long felt taken advantage of. → Liquid Death takes bottled water and flips it with irreverence.  → Boost takes on the Big Three carriers with a promise of transparency. The common ground is not the product, it’s the attitude. That is why the Cellphone Bill character feels so natural. It is grotesque, absurd, and culturally resonant. It looks and feels like a Liquid Death idea, but it dramatizes the pain points of the wireless industry. In that move, Boost borrows credibility and attention from an audience already primed to enjoy it. Partnerships like this don't need to make sense in a traditional way.  They are about association and shared codes. → Associating with Liquid Death transfers its entertainment-first equity to Boost. → Associating with Boost gives Liquid Death a new canvas to extend its creative IP. For Boost, the strategy is clear. They cannot outspend Verizon or AT&T, but they can out-entertain them and dramatize consumer frustration in ways incumbents never will. For Liquid Death, it is proof that the brand is not just a canned drink, but a cultural IP factory that can collaborate with other disruptors. Together, this is less about selling phone plans or water and more about building relevance through shared cultural disruption. That association is enough.

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Your perfect landing page is worthless if affiliates can't prove they sent the traffic. We were hemorrhaging conversions and nobody knew why. Partners swore they were driving signups. Our data showed "direct traffic." Every extra click between landing and signup was murdering our attribution. Users would land, explore features, check pricing, then sign up. By then, cookies failed, pixels misfired, and attribution windows expired. Mobile made it worse. App stores were a catastrophe. The fix was really simple. Split landing pages with embedded sign-up on one side and just enough context on the other. There was literally no navigation required. Everything users needed was in one place. ✓ Social proof ✓ Value props ✓ Trust signals That single change probably improved affiliate conversion rates by double digits. Our team became one of the best growth design teams in all of FinTech. The best converting page means nothing if partners can't prove they drove the conversion. Every extra click is money left on the table.

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🖥️✅ Mike Shields / Substack (10/21): “Roku is one of the companies that is bullish on this would-be sector, rolling out a self-serve platform called Roku Ads Manager about a year ago. The company says it’s seeing real growth here - with one key caveat. We’re seeing a new advertiser category emerging,” said a Roku executive on the Next in Media podcast this week. “We’ve got lots of different parts that make up our total platform revenue, and this area is the fastest growing. I think the misnomer for a lot of these platforms is that they think there’s just going to be this onslaught of SMBs that is going to make up some really fast revenue opportunity. And the reality is that onboarding SMBs is challenging. You need to onboard thousands, if not tens of thousands or hundreds of thousands for that revenue to make up anything meaningful.” What Roku is seeing is that performance advertisers, including many of those direct-to-consumer brands, are coming to TV quickly. That’s great, but it’s not the wave of mom-and-pop shops that make up huge chunks of the millions of advertisers drawn to Meta and Google. “Those mom-and-pop shops, they advertise in the newspaper,” Roku said. “They advertise with local radio. Sure, they advertise on social and in search for sure. But they don’t have a sophisticated marketing team. They don’t have a very large marketing budget. Whereas the digital performance buyer is very sophisticated in its methods and its measurement, and is doing its own analysis on revenue impact, total ROAS, their lift and regression analysis. They might be doing incrementality analysis and geo-holdout lift studies and all of these kinds of things. That group is the one that we’re seeing move more heavily into CTV.” ⬇️ #streaming #ctv #ott #avod #programmatic #smb #dtc https://lnkd.in/ewCxfptQ

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1 Comment

Stripe's website violates every rule about API marketing. Their homepage links directly to curl commands. Test keys are public. The docs have better navigation than most marketing pages. Here's why their nerdy site converts everyone: 1. They built for developers, not consumers PayPal owned payments by focusing on consumers. Stripe went straight to developers. The entire site speaks in code. API references in main nav, Curl commands on the homepage, Technical docs as marketing material. They bet that developers would choose the payment infrastructure, not end users. PayPal never saw it coming. 2. You can use Stripe BEFORE you sign up Go to stripe.com/docs. Copy the test key. Run the curl command. See your request in their logs. You just processed a (sample) payment through Stripe without giving them your email. Compare this to every competitor: PayPal requires business verification. Adyen needs a sales call. Square makes you create an account. Stripe lets you experience success first, KYC friction second. Within hours, you could have already integrated their API. You've invested serious effort. The psychological commitment already happened. That's why their activation rates destroy everyone else's. 3. Test mode never expires and has zero limits Most API companies give you 14 days or 100 requests. Stripe gives you infinity. Public test keys. Unlimited requests. Full functionality. Forever. Startups can run in test mode for 6 months while building their product. By launch day, they’ll have written thousands of lines of Stripe-specific code. Trained their entire team on Stripe's patterns. Built their database schema around Stripe's objects. The cost to switch would be MONTHS of rewriting. Stripe turned their free tier into it’s stickiest feature. Once you build on test mode, production is inevitable. 4. The documentation IS the sales process Every Stripe page has two buttons: "Start now" and "Contact sales." Both lead to the same place: the API reference. No separate enterprise portal. No PowerPoint decks. No solution architects drawing diagrams. The Fortune 500 CFO validating compliance and the developer implementing payments read identical documentation. BMW evaluated Stripe using the same public docs you're using. When code becomes the sales material, two things happen: 1) Developers trust it (no marketing bullshit) and 2) executives can verify claims themselves (reducing sales cycles from months to weeks). KEY LESSON Stripe's site speaks exclusively to developers, not consumers. No "Pay with Stripe" badges. No consumer benefits. Just code. This let them bypass PayPal entirely. Every developer who chose Stripe became their distribution The site converts because it ignores 99% of people to obsess over the 1% who actually implement payments.

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Meta just confirmed what I've been arguing for months. In their Q4 earnings call, they explicitly stated that investments in GEM (Generative Engagement Models) are improving ad performance and attracting more ad dollars. [FULL QUOTE BELOW] Most marketers will hear this and think: "More AI hype." They're wrong. Meta has fundamentally re-engineered its ad platform at the technical level. It's invisible to most people: -Consumers just see better ads at the right time -Advertisers see the same campaign manager interface -Unless you've hit a scaling wall, you might not notice anything I wrote about this shift a few weeks ago (link in comments): Meta moved from interest-based targeting to predictive intent. From "show ads to people who like yoga" to "show ads to people our system predicts will buy yoga mats in the next 72 hours, regardless of their stated interests." That's not an incremental improvement. That's a different product. Here's what frustrates me about all the AI hype: everyone's trying to predict how this technology will change the world in 10 years. Meanwhile, the companies that invented this stuff—Google, Meta—are already using it. Not in some flashy consumer app. In their ad stacks. Because that's what drives their stock price. If you're still running Meta ads the same way you did two years ago—optimizing around interests, testing endless creative variations, obsessing over attribution—you're putting the same gas you use for your Corolla into a rocket ship. The platform has changed. Your strategy needs to change with it. What does that mean practically? Feed the algorithm more signals. Give it conversion data. Give it the creative diversity it needs to learn what works. Let it find your customers instead of you trying to define them. Trust the predictive engine you're paying to access. The marketers who adapt to this shift will scale. The ones who don't will keep hitting walls they can't explain. --- Susan Li, CFO "In Q4, we doubled the number of GPUs we used to train our GEM model for ads ranking. We also adopted a new sequence learning model architecture, which is capable of using longer sequences of user behavior and processing much richer information about each piece of content. The GEM and sequence learning improvements together drove a 3.5% lift in ad clicks on Facebook and a more than 1% gain in conversions on Instagram in Q4. This new sequence learning architecture is significantly more efficient than our prior architectures, which should enable us to further scale up the data, complexity and compute we use in our future ranking models to deliver performance gains. As we scale up our foundational ads models like GEM, we are also developing more advanced models to use downstream of them at run-time for ads inference. In Q4, we launched a new runtime model across Instagram Feed, Stories, and Reels, resulting in a 3% increase in conversion rates in Q4."

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Programmatic Prose🪄 Hey friends, quick reminder: too many campaigns still stop at CTR. In DV360, Brand Lift & Search Lift are the simplest way to see if upper-funnel spend is actually shifting demand. If you’re not running them, you’re flying blind.

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In the wake of advertising budgets shifting from traditional linear TV over to CTV, the question remains... where is Apple TV+? Premium platforms like Amazon Prime TV and Netflix are executing on targetable audiences and data. FAST players like Tubi and Pluto have strong data sets as well - and programmatic ad networks like The Trade Desk continue to capture share. CPMs are favorable making it a very compelling scenario for CTV... so again, why hasn't Apple jumped into this? I would have to imagine Apple's (TV+, Music, iPhone, etc) data is incredibly valuable - something advertisers would be extremely excited to leverage. TV+ has some of the best programming (both film and TV) committing to quality above all else. Apple's also no stranger to sports rights with the MLS and MLB deals. The missing piece looks to be an ad network. Subscription rates jumped 30% to $12.99 (up from $9.99) per month - while that still is super compelling on a consumer level, prices will only trend upwards from here... And would that indicate a split to premium versus ad-supported. So maybe its early innings since the offering is still very favorable for consumers. Maybe Apple hasn't built out the ad network capabilities for brands and advertisers? Maybe Apple simply just doesn't care to advertise... Though, Netflix, Amazon, FAST channels, Roku, and adtech players are capitalizing on an extremely hot trend (that doesn't seem to be slowing down all that much). CTV is (not-so-)slowly becoming the new normal for the TV medium, and Apple TV+ misses much of this.

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8 Comments

Last-touch attribution is the most widely adopted measurement in commerce media today. Budgets are planned with ROAS. Sales goals are assigned based on it. Algorithms optimization against it. If there is one metric that directs the flow of commerce media more than any other, it’s ROAS. So the $100-billion question: does it actually correlate to sales growth? The answer is still no. I remember reading Comscore, Inc.'s "Moving Beyond the Click" nearly 15 years ago and one line clicked for me (no pun intended) 😉 "Clicks don’t measure all of a campaign’s sales impact nor the cumulative (latent) impact of ads." As commerce media continues to move up the funnel this holds just a true now as it did 15 years ago. One of the first meta-analyses we did when I joined the Incremental team was to look at a broad cross-section of campaigns comparing last touch based attribution to incremental sales. The results were both surprising and not. Across a broad set of campaigns, incremental sales and last touch attribution didn't correlate. For those following over the years, this may not be a shocker as study after study have shown that click-based attribution has no relationship to true business growth. 2009 Nielsen: CTR vs. ROI: r=-0.07 2012 comScore: Clicks vs. Conversions: r=0.01 2015 Nielsen: Clicks vs. Conversions: r=0.01 2019 Dunnhumby: CTR vs. Incremental Sales: r=-0.28 2021 Quantcast: CTR vs. Conversion Rate: r=-0.12 While the reliance on last touch ROAS is a systemic risk, it is also a massive opportunity for those who have made the transition away from it. Especially if their competition is still reliant on it. All of that media is sub-optimally allocated for incremental growth. Every algorithm, every rule adjusting bids and budgets based on ROAS isn't steering towards growth effectively. Want more growth? Ditch the high-fructose corn syrup of last touch ROAS.

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SendX, an ESP, ditched legacy email sending tools and now has a 95-98% delivery rate with 300M+ emails per month. What’s powering this ESP now?   → It's SendPost. SendPost gives ESPs real-time visibility into every IP, domain, and sub-account with live email-provider response data and AI-driven deliverability health alerts. The results that SendX got after switching to SendPost can make any ESP jealous: ✨ Email delivery rate jumped from ~60% to over 95% (even in crypto, gaming, and affiliate!)  ✨ Warmup success rate improved from ~50% → 90–95%. ✨The same 5-person deliverability team now manages 20–30X more volume. If you want to try SendPost but are worried that it'll need more budget or take days to integrate, let me tell you that for SendX… ✨ Infra costs went down by 3X. ✨ Integration took <2 days, and full rollout happened in a week These results were possible because SendPost is built by people who actually run an ESP. We got tired of black-box analytics, no control over the speed of sending emails, and long delays in resolving any email delivery issues. We needed real control. Real visibility. Real accountability. So we built the infrastructure we wished existed. Here’s what makes it different 👇 ✅ SMTP-level analytics for every domain, subaccount, and IP. ✅ Auto IP & domain warmups that actually finish successfully. ✅ Granular ability to adjust mail queues and throttle sends per sub-account for optimal deliverability ✅ Deliverability alerts before something breaks. ✅ API-first design with Slack integration and webhooks that your ops team will love. …and so much more. SendPost isn’t for everyone. It’s for ESPs that are done playing blindfolded and ready to own their email delivery. 👉 Read the full before-and-after story behind SendX’s jump to 95–98% delivery: https://lnkd.in/gYK-AXDC

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