Marketing Analytics

Every marketer is sitting on a pile of campaign data and still guessing. Which channel is actually driving pipeline? Which ad is converting, and which one is just burning budget? Where should I push harder, and what should I kill? These aren't hard questions. They're just hard to answer when your data is spread across six tools and three dashboards none of your team looks at the same way. Dreamdata AI changes that. It pulls your revenue data together and lets you just ask it things. Plain language. Real answers. No pivot tables, no BI ticket, no waiting for someone on the data team to get back to you. What I didn't expect: I never have to leave the tools I'm already in. Dreamdata has an MCP, which means I can pull revenue attribution and campaign performance data directly inside Claude or ChatGPT. I set a reminder every morning to check in and ask what I should be prioritizing that day. It's the first time I've felt like my data is actually working for me instead of the other way around. If you've ever ended a campaign review still unsure what actually drove the results — this is worth a look. Link in the comments. https://dreamdata.io/dreamdata-ai?utm_source=chris-cunningham&utm_medium=Ryan-swindall&utm_campaign=Dreamdata%20AI%20Launch #Dreamdata #B2BMarketing …more

What happens when you actually check whether your clicks are people? I build Radi8, and it tracks link clicks, so one afternoon I went and looked under the number. Of 1,791 clicks across 177 links, 624 came from a human. The rest were bots, crawlers, preview-fetchers, the quiet machinery of the internet pinging a link so it can draw a little card. And here's the humbling part, a bot only gets counted as a bot when it politely announces itself, LinkedInBot, Googlebot, facebookexternalhit, which means the real human count sits somewhere below 624, never above it. Then it got worse for my assumptions. The channel I'd have sworn was carrying me on raw clicks turned out to be mostly sending machines, while a quieter one was sending far more actual people. I almost optimized straight toward the emptier number. Every figure on your dashboard is counting something. Make sure it's counting the thing you care about, before you spend a month acting on the wrong one. …more

Today's post is 301 words, a 2-minute read. Sources: Generative AI Enterprise — "McKinsey Unveils AI Profit Lessons" 1 big thing: We just entered a new phase of enterprise AI — here's what that means for B2B marketers The question is no longer whether AI works. It is whether your organization can actually deliver on it. Why it matters: McKinsey's 2026 State of AI confirms what most enterprise leaders already sense — AI investment is surging, individual productivity gains are real, but P&L impact remains elusive for most organizations. Driving the news: McKinsey surveyed 1,719 participants across 97 nations. → 80% say AI has improved their individual productivity → Only 37% attribute any EBIT impact to AI — roughly flat year over year despite surging investment Zoom in: Companies breaking through share two practices: they redesign workflows alongside the model rather than layering AI on top of existing ones, and they measure in business outcomes rather than accuracy metrics. → McKinsey anchors this with two case studies — a global manufacturer scaling with AWS and a conglomerate deploying agentic AI at speed Yes, but: 20% of respondents say AI operating costs — tokens, infrastructure, compute — are already constraining usage. Cost management is becoming a real strategic variable, not a footnote. Be smart: If your AI initiatives are measured in time saved or content volume produced, you are measuring the wrong things. Tie AI output to pipeline influence, conversion rate, or content-attributed revenue. That is the only measurement that survives a budget conversation. The bottom line: Technology is rarely the binding constraint. Delivery, adoption, and measurement are. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai #AIStrategy #B2BMarketing …more

We're halfway through the year. I've been doing a lot of thinking about what's actually worked in my marketing vs. what I thought would. Here's my honest take. What I expected to work: a polished content calendar, consistent posting across multiple channels, well-designed assets. What actually moved the needle: direct conversations that started from a single, specific LinkedIn post that named an exact pain point my audience was feeling. The post wasn't clever. It wasn't visually interesting. It was just specific and true. It got more inbound messages than anything I'd posted in the previous three months combined. The lesson I keep relearning: marketing feedback loops are much shorter than founders think. You can know within 30 days whether a message is working — if you're watching the right signal. Not follower count. Not impressions. Conversations started. That's the metric I watch now above everything else. How many people responded to something I wrote and said "this is exactly what I'm dealing with"? That's the leading indicator that content is building pipeline. The other thing that worked: teaching something specific in every post instead of sharing opinions. Opinions get likes. Teaching gets DMs. DMs become customers. My Inspiring Founders community on Skool is where I share what I'm learning as I learn it — if you want to follow along, join us. It's free: https://www.skool.com/inspiring-founders-5861/about …more

I host the Inspiring Founders Podcast. Every Thursday we publish a new episode where founders share practical lessons from building companies. A brief lesson from launching programs: define one clear success metric per horizon, limit concurrent initiatives, and align resources to the highest-priority horizon. That clarity reduces friction and improves decision speed. If you want to discuss this or be on the podcast, send me a message. #founders https://www.inspiringfounders.com/podcast …more

I ran a one-week experiment with Radi8 on my LinkedIn content. Engagement rose 64.8%, impressions increased 55.8%, and members reached grew 78.1%. The takeaway: Radi8 has immediate impact on your reach and engagement. …more

From running small growth experiments at startups, I learned that local businesses do best when attention is tied to action. Flip's approach, building simple systems that link social posts, customer data, and basic automation, turns organic interest into predictable, trackable revenue without paid ads. Practical steps: map the post-to-sale journey, capture contact data early, automate low-friction follow-up, and measure conversions not impressions. If you are testing organic channels, send me a message. #startups https://www.santacruzworks.org/news/flip-commerce-rethinking …more