33 Sticks

We had a great turnout at the 33 Sticks suite yesterday! Thank you to all the amazing people who stopped by to cuddle the puppies. We will have the puppies again today between 1-4. Stop on by to rest, recharge, and refuel. We are in the Venetian north tower. DM for location details. #AdobeSummit

A is for Analytics at Adobe Summit

The Rule Sandwich, Now for the WebSDK: A Smarter Approach to Implementation The WebSDK has changed the way we think about data collection, but one thing remains the same ? clean, well-structured rules make or break an implementation. Enter The Rule Sandwich ??, a framework we’ve used for years to keep implementations scalable, predictable, and resilient. Now, we’re applying it to the WebSDK. If you’re struggling with rule complexity, conflicting conditions, or unpredictable outcomes, this approach will help you bring order to the chaos. Check out the full breakdown here: https://lnkd.in/g8jEsdbG #AdobeWebSDK #DigitalAnalytics #DataStrategy

Adobe Analytics User Group meeting in Munich with our friend Frederik Werner https://lnkd.in/gZX-rS4v

At 33 Sticks, we helped a global manufacturing company transform their struggling analytics program through a focused three-pillar approach: 1. Consolidating fragmented leadership 2. Implementing robust governance frameworks 3. Building the right analytics team structure The results were remarkable: ? 62% reduction in redundant data segments ? Report loading times decreased from 10+ minutes to under 60 seconds ? Data collection completeness drastically improved ? Business user confidence in analytics data increased We believe investing in analytics leadership should precede or accompany investments in tools and technologies. Without the right foundation, even the most advanced platforms will fail to deliver their potential value. Read the full case study to discover our implementation roadmap and key lessons: https://lnkd.in/g58VFMw4

i'm a bit of a coffee fanatic. This morning i'm enjoying a pour over with The Riverside, an Ethiopian blend, from Onyx Coffee Lab. And speaking of coffee, i recently had an experience with a friend who bought a highly automated espresso machine and i found myself using that experience to explore the intersection of analysis, learning, #GenAI, and automation. Give it a read and let me know what you think? The Espresso Paradox: How Automation Might Be Diluting Our Analytical Expertise -> https://lnkd.in/gZi7_4ic

Is there a connection between data analysis and espresso making? 33 Sticks founder jason thompson talks about how espresso making created a profound lesson about expertise, automation, and the future of analytical thinking given the current excitement around #GenAI https://lnkd.in/gCxJGAaz

i’m seeing a trend in the analytics agency space that i think is worth calling out. More and more agencies are rolling out “free AI tools” as a lead gen play for their traditional analytics services. Let’s break down how this actually plays out: - You’re invited to try a “game-changing AI agent” that promises to analyze all your digital data. ANALYTICS AUTOMAGICAL??. - The idea of a “free analyst” is exciting because who wouldn’t want to save a ton of money on an experienced analyst? Or maybe it’s appealing because your company can’t afford to hire a full-time analyst in the first place. - Enter the real world. The AI-generated “insights” are...ahhhhh... underwhelming. - The tool struggles with data quality, lacks context, or just wasn’t designed well enough to deliver anything useful. - Enter the upsell. To actually get meaningful insights, you’ll need the agency’s traditional analytics services for that. i know, this isn’t a new or innovative tactic, these types of lead magnets have been around forever. But it feels like the AI hype cycle is supercharging the sketchiness of these so-called funnels. Classic bait-and-switch. P.S. The agency partners truly worth working with won’t lure you in with overhyped promises only to upsell you later. And they absolutely won’t rely on smoke and mirrors or let AI do all the heavy lifting while conveniently ignoring its major limitations.

20 years ago, Avinash Kaushik said something like, for every $10 you spend on analytics software, you should be spending $90 on smart data people. And yet, here we are. Most companies have flipped that equation (probably even worse now with "AI"). Billion-dollar brands are replacing their data experts with AI agents some kid whipped up using Claude over the weekend. Data vendors announcing their 18th round of funding, which means the market will be attacked by even more sales FUD pushing us to buy even more tools we don't need because...NOW WITH AI?? But i'm not sure more tools, even AI agents promising to magically answer all our questions, are going to fix much. In fact, i'll argue they are going to amplify existing problems that fundamentally are not technology problems: - Low data literacy rates (people don't know how to use the data they have) - Non-existent data governance (20 different definitions for what a purchase is) - Dirty, untrustworthy data (garbage in, garbage out) - Lack of senior executive support (because "data-driven" sounds nice in theory, until it conflicts with egos) Do we really need more tools right now or do we need to actually, perhaps 20 years too late, invest in the people and frameworks that make the data useful in the first place and then align our tools, and the AI that will automatically make everyone in the org a 10x analyst, accordingly?

Beyond grateful to Chris Moeller for distilling the essence of our hour-long conversation into this powerful 2-minute clip, capturing what i believe is the most critical message for our industry, "If all we do is report the data, we will be the first to get let go." For over two decades, the analytics community has focused heavily on technical foundations like collecting data, measuring things, building pipelines, designing warehouses, and creating dashboards. While this infrastructure is critical, it's not what drives business value. Our business partners aren't looking for more dashboards, they're looking for insights that drive decisions. The analytics professionals who will thrive through this challenging time aren't just builders of data infrastructure, they're strategic partners who understand business and can translate complex data into clear, actionable insights.