If your reports never match and the one person who understands your tech stack is either gone or planning to leave, you already know something's wrong. What you might not know is that the spreadsheet you keep going back to isn't the solution to that problem. It's a symptom of it.
Sarah and I have been working with B2B companies for sixteen years, and we've seen this play out across companies of every size. You get a tool to solve a problem, then another to solve a slightly different problem, and before long, you've got a Frankenstack: software bolted together without any shared logic, where the data speaks different languages, and nobody fully trusts any of it. This episode gets into how that happens, how to know when you've got it, and what a smarter approach looks like. You'll come away with a concrete framework for evaluating your current stack, a clearer picture of why your data keeps telling conflicting stories, and a practical way to move toward a source of truth you can actually use.
This post is based on Episode 59 of Revenue Rewired | Ep 59: Why Your Spreadsheet Is the Most Expensive Tool in Your Tech Stack.
If you'd rather listen than read, find the full episode on Apple Podcasts, YouTube, Spotify, or Amazon. It's worth your time.
How Does a Company End Up With Three CRMs?
Faster than you'd think. One of our current clients has HubSpot because their marketing lead loves it, Salesforce because the VP of sales came from a Salesforce shop, and Pipedrive because a team member is comfortable with it. When those three people made their cases to leadership, the response was essentially: " You know your tools, go ahead. Now they're trying to figure out how to make all three talk to each other, and nobody's asking whether they should have all three in the first place.
This is how Frankenstacks form. It's rarely one reckless decision. It's a dozen reasonable ones, made in isolation, each time by someone who knew their tool and had a real problem to solve. The trouble is that no one person ever owned the full picture, and as those people cycle in and out, what remains is a patchwork of integrations, duplicated functionality, and quiet failures that don't announce themselves until something visibly breaks.
I've seen this across the 250-plus companies we've supported over sixteen years. Size doesn't matter much. Companies at $5 million and companies at $50 million both end up here. The difference is that bigger organizations tend to notice it later, because the stack is harder to see clearly when 30 people are touching it.
Why Your Data Is Telling You Two Different Stories
Here's something I've probably said a thousand times across client calls: Google Ads will tell you we got four conversions last week, and Google Analytics will say we got two. The same company's products. Same time window. Different numbers. This isn't a slight rounding error. It's attribution. Google Ads looks at last touch. Google Analytics might be counting differently based on how your tags and goals are set up. If your tag manager has layers from three previous agencies all firing at once, the numbers will be off in ways that are genuinely hard to diagnose.
We're currently working through a full integration audit for a client where the report runs to fifty-plus pages, and what we keep finding is that years of accumulated tag and trigger overlap have made the data essentially unreadable. Their last three agencies each went into the tag manager account and built different tags and triggers that all do the same thing. A previous marketing director brought on a tool that stopped working a year ago, and nobody's been managing it. These things don't announce themselves. They leak quietly, like a pinhole in copper piping behind a wall, until you see the mold and realize the damage has been building for years.
The move many companies make here is to build a spreadsheet that pulls from multiple sources and creates a manual source of truth. And I understand why. When no tool gives you the right number, you cobble together something that feels more trustworthy. The problem is you're now maintaining that spreadsheet alongside the tools you're already paying for, and the person who built it is probably the only one who understands it.
What 'Good Enough' Actually Means for Your Data
Sarah made a point in this episode that I want to repeat because it shifts the frame: you don't need perfect data. You need data that's reliable enough to guide the next decision. That's actually a different standard, and it's one many companies could meet without rebuilding everything from scratch.
The podcast analytics situation is a good illustration of how we've handled this ourselves. Spotify and Apple report listener numbers differently. There's no cross-platform standard. We can't get a single clean number. So we picked one signal we trust enough to make decisions from, noted its limitations, and moved on. Chasing the gap from 80% accurate to 100% accurate takes real time and money, and it rarely changes the decision. What it does is delay the decision while you argue about methodology.
What this means practically is that when a client comes to us frustrated that their organic search traffic is down, we don't immediately jump to fixing organic search. We take a step back.
Is the total qualified pipeline actually down, or are you seeing a shift toward LLM referral traffic that your reports don't show yet?
Those are different problems. One of them is actually fine. Starting from the macro question, what did our marketing investment produce in sales opportunities, gets you to the right answer faster and keeps you from investing time in something that wasn't broken to begin with.
The Part Nobody Thinks to Document
Here's what keeps hurting companies, and it's not the tools themselves. It's that one person understands how they connect, and that person leaves.
We've had this happen with clients too many times in the last few years. A team member who built the integration setup gets poached or takes another opportunity, and suddenly, we're scrambling to figure out where the logins are. Nobody knows which account the billing is tied to. Nobody's sure what the integrations are supposed to do. The whole thing doesn't fall apart instantly. It starts as a small leak, and by the time it's visible, the damage is significant.
The answer isn't to find better people. It's to build a system that isn't dependent on any one person's memory. You need a named tech stack owner, a documented map of what's connected to what and why, and a quarterly review where someone asks whether you're still using everything you're paying for. Sarah runs that process for StringCan, and we regularly find subscriptions nobody's touched in months. The exercise doesn't have to be complicated. It just has to happen consistently.
FAQ
Q: We have 25+ software tools, and nobody agrees on which numbers to trust. Where do we even start?
A: Start with one question: What did your marketing investment actually produce in the pipeline for your sales team last month? That's the macro number you need first. Everything else, which tool reports it, how attribution is handled, can get sorted once you know what signal matters.
Q: Is it worth paying for a full tech stack audit, or can we do it ourselves?
A: It depends on how layered the problem is. If you've had multiple agencies touching your tag manager and your CRM setup has changed hands more than once, a structured external audit will find things you can't see from inside. If you've maintained reasonable continuity, a self-audit with a documented checklist can work. Either way, someone has to own the outcome, or the findings just sit in a document.
Q: Our marketing reports never match our CRM data. Is this fixable without rebuilding everything?
A: Usually yes. One common culprit is attribution settings that don't match across platforms, which can often be fixed without a full rebuild. Start by documenting what each tool is actually measuring, finding where the definitions diverge, and agreeing on one source of truth to anchor your reporting to, even if it's not perfect.
Q: We keep adding tools, but things aren't getting better. When should we stop adding and start cutting?
A: When you can't answer what each tool is producing for your business. If a tool has been in your stack for six months and you'd struggle to explain what decision it helps you make, that's a cut candidate. A quarterly review process is what makes this manageable, rather than a one-time purge you never finish.
Q: How do we protect ourselves when the one person who understands our tech stack leaves?
A: Documentation is the only real answer, and it has to be treated as a living document, not a one-time project. That means a written map of what's connected to what, where the logins live, what each integration is supposed to do, and who currently owns each piece. The goal is that any reasonably technical person on your team could pick up where the last person left off without a two-week transition period.
Ready to Get Your Tech Stack Actually Working for Revenue?
At StringCan, we've spent sixteen years helping B2B companies align their marketing, sales, and operations so every tool in the stack earns its place. That includes working through Frankenstack situations, the data trust problems, and the cases where the honest answer is to simplify before layering anything new on top. We're not trying to sell you another tool. We're trying to help you get real value out of the ones you already have.
If this episode landed for you, listen to the full conversation here and then reach out to us at stringcaninteractive.com. If your reports aren't telling a consistent story and you're not sure who owns the problem, that's exactly the kind of conversation we're built for.
