Ep 61: Why Good Data Feels Bad at First episode artwork

EPISODE · May 21, 2026 · 32 MIN

Ep 61: Why Good Data Feels Bad at First

from Revenue Rewired · host Jay Feitlinger & Sarah Shepard | B2B Growth Experts

Most $10M–$50M B2B companies aren't working from bad data. They're working from data they've never properly questioned.When StringCan onboards a new client, the first thing they audit is the reporting foundation. What they find, almost every time, is a version of the same problem: traffic numbers inflated by internal employee logins, attribution gaps that make a $50K campaign look like it disappeared, and year-over-year comparisons built on two entirely different measurement systems. The reports looked right, yet the decisions built on them were wrong.In this episode, Jay Feitlinger and Sarah Shepard break down what happens when you actually fix the data, why it almost always looks worse before it looks right, and how to bring your leadership team through that moment without losing their confidence. From the GA4 migration that invalidated years of comparison data to the client who thought his numbers had fallen off a cliff (they hadn't, they just became accurate), this episode is a direct conversation about one of the most common revenue leaks in owner-led B2B companies: the Metrics Misfire.If your team is reporting activity and your leadership is nodding along, but nobody is connecting those numbers to actual pipeline or closed revenue, this episode is the one to share.What You'll Take AwayClean data looks like a problem before it looks like progress. That's not failure, it means you're finally seeing real numbers you can build on.The GA4 migration wasn't just a platform change. It rewrote the comparison baseline for most teams, and those who didn't account for it are still reporting from two stitched-together measurement systems.The single biggest data inflation issue Jay sees on new client onboards isn't bots or tracking errors. It's internal employees and partners hitting the site daily with no IP exclusion, inflating traffic and tanking engagement rates.More data isn't better data. The right question is never "what does this report show?" It's "what are we trying to answer, and what does this number actually tell us?"Presenting accurate data to leadership isn't bad news. It's their first honest starting point. The skill is framing it so they see it that way.Episode Chapters00:00 When the Spreadsheet Stops Telling the Same Story 02:00 The Client Whose Accurate Numbers Looked Like a Collapse 05:03 What the GA4 Migration Actually Did to Your Year-Over-Year Data07:56 What "Single Source of Truth" Actually Means to a CEO 11:59 Cleaner Data vs. Fixed Data: Why the Difference Matters 14:50 Why Marketers Resist Letting Go of Familiar Metrics 16:32 How to Bring Leadership Through a Data Reset Without Panic 21:31 Reporting for Reporting's Sake Is a Revenue Leak 23:43 The 54-Slide Dashboard Nobody Could Follow Past Slide Seven 27:44 The Two Data Inflators Jay Finds on Almost Every New Client Audit Your HostsJay Feitlinger, CEO of StringCan Interactive LinkedIn: https://www.linkedin.com/in/jayfeitlinger/Sarah Shepard, COO of StringCan Interactive LinkedIn: https://www.linkedin.com/in/sarahshepardcoo/About Revenue RewiredRevenue Rewired is built for owners, CEOs, and founders of B2B companies doing $10M to $50M in revenue who know their marketing is producing activity but can't see where it's actually producing pipeline. Each episode diagnoses one part of the growth system where revenue is leaking, and gives you a framework to fix it.Get the book: https://www.amazon.com/Revenue-Rewired-Identify-Leaks-Costing-ebook/dp/B0FST7JCXQ Newsletter: https://www.linkedin.com/newsletters/revenue-rewired-7423414515779936256/   Website: http://www.stringcaninteractive.com Email: [email protected] Take our Revenue Leak Assessment now: https://stringcaninteractive.com/revenue-leak-assessment marketing data accuracy, B2B marketing metrics, Metrics Misfire, single source of truth B2B, inflated website traffic fix,

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Ep 61: Why Good Data Feels Bad at First

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