Clean Up Your Data

January 14, 2026

I use Fibery to consolidate what I know about my readers, customers, and investors

AI agents and workflow automations cannot help you create better experiences when your data is crap and all over the place.

Imagine chatting with someone over coffee and only later you find out that they're one of your Substack's paying subscribers. 🤦🏻
Imagine meeting someone at an event and when you get back to your hotel, you discover they were one of your crowdfunders. 😣
Imagine recognizing someone's name and face but being completely oblivious that you're facing one of your book reviewers. 🤷🏻

I'm sure you recognize the problem.

You have no fricking clue who is who.

Your Substack subscriber stats are trapped in the Substack dashboard. Thousands of LinkedIn connections exist only within the LinkedIn app. More thousands sit in Google Contacts, an aging MailChimp or Mailerlite list, perhaps a half-forgotten Discourse community, and some obscure CRM you installed during a moment of optimism and have touched maybe once or twice since. Everyone who's ever joined your Zoom calls lives behind the shredded veil of Zoom's atrocious user interface. And your paying customers sit safely locked up in Stripe and your bookkeeping software.

In short, you're suffering a serious case of data sprawl, as if your Rolodex got hit by a tsunami.

Everyone you've ever met is technically "in your network"—in the same way that your socks, spare change, and discount coupons are technically somewhere "in your house." Each tool guards its pile of contacts like a territorial dragon. Every time you want to actually do something—spot a pattern, respond to a signal, nurture a relationship—you negotiate with six dashboards, three 2FA gates, and interfaces designed by people who hate users.

You don't have a "network." You don't have a relationship management system. You have a distributed museum of people-you-once-met, curated by SaaS vendors, funded by your monthly subscriptions, held together by hope, spreadsheets, and the fantasy that you'll "clean this up someday."

Welcome to my (former) life.

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Good Data Before Good Automations

It's time for the mantra that applies to everything from cooking to herb gardens to automation:

Garbage in, garbage out.

If your data is a disaster area, your "multi-agent system" will be just a gang of lumbering fools.

Without good data, your business may not survive the future.

Everyone I know is now in ONE place: my relationship management system

So, before you burn another evening on n8n workflows, Make scenarios, Zapier chains, or the latest AI agent promising to "run your business while you sleep," do yourself a favor:

STOP!

Back away slowly. Clean your data first.

Because in a slightly less ridiculous future, you could have:

An AI agent that tells you exactly which people signed up for your Substack newsletter after a Zoom webinar
An automation that nudges you to celebrate the Nth anniversary of a paid subscriber instead of ghosting your most loyal supporters
A LinkedIn connection that gets matched automatically with your Google Contacts instead of becoming Yet Another Anonymous Face in Your Feed
Actual knowledge of which email addresses and other data belong to the same human being across five different SaaS platforms
Substack subscriber statistics enriched with payment metadata from Stripe
And on and on it goes

None of this is science fiction. It just requires something utterly boring in the era of vibe-coding tools and AI-driven Solo Chiefs: reliable processes and daily maintenance.

Yeah. Sorry.

Full disclosure: I haven't implemented all of this myself either. I'm not writing from atop a perfectly normalized data utopia. But I've made serious progress. Enough to see the light. I'm on a journey toward a networked agentic organization, and I'm happy to take you with me. This post covers the first leg.

Let's discuss how to extract your data from its scattered silos and consolidate it into one central relationship management system, where it can finally stop embarrassing you and start doing useful work—work that makes you happy and, more importantly, makes the people you know feel valued. Your human connections deserve better than being treated as the debris of a digital explosion all over your digital house.

An Example

As a preview, let me show you the data card for my good friend Lisette Sutherland.

It tells me she's based in the Netherlands, has five different email addresses (because of course she does), and exactly one LinkedIn account. It shows which email she used on Substack, when she joined, and whether she's on a free or paid subscription. The "Found Names" line in the screenshot lists how her name appears across platforms—mercifully consistent in her case, unlike certain people who reinvent their call sign with every online tool they use. I've added a few notes about things Lisette has been involved in or contributed to, because context matters, more than ever.

And this is just the beginning.

Now that the basics are in place, I can plug in any number of platforms, tools, and apps to ensure the important information about my contacts lives in one place instead of playing hide-and-seek across a dozen SaaS vendors. (The next one I'm going to add is my former Slack community, which has another 8,000 people in it.)

Even better, I've built a range of de-duplication mechanisms. When someone shows up as Dr. Janny De Boer-Veenstra CSM CSP on LinkedIn but casually calls herself Janny Veenstra on Substack, the system will catch the duplicate (even when she's using different emails) and it asks me to merge the records.

Now pause for a moment and imagine the endless possibilities that emerge when all the information a person has shared with you actually connects across systems:

You actually know you're chatting with a reader, customer, or investor when you meet someone, without looking like a clueless fool, because you have everything in one place. You can stop asking stupid questions (“Remind me again—where are you based?”) when the person has told you that three times already. You can monitor expiring and renewing subscriptions and reach out proactively instead of discovering churn weeks later in a revenue report. You can update someone's outdated details in your bookkeeping software when their LinkedIn profile changes, without playing forensic detective. You can prioritize reading and responding to social media posts from your paying Substack subscribers, giving them the attention they deserve instead of relying on which social media algorithm screams loudest.

But let's not get carried away.

Rome wasn't consolidated in a day.

Before we unleash the automations, the workflow scenarios, the AI agents, and the smug satisfaction of finally having our data under control, we need to answer a more basic question:

Where do you put all this information without losing your sanity?

Why I Choose Fibery

I don't use Notion, Airtable, Coda, or ClickUp.

I'm a fan of Fibery.

Fibery describes itself as "a complex but not complicated operating system for companies run by nerds."

Which is refreshingly honest, slightly intimidating, and surprisingly accurate.

In my view, Fibery is the Google Pixel of database workspaces. Compared to its larger rivals, it sacrifices glossy aesthetics and mass-market charm for a clean, technically solid foundation. The kind that doesn't fight you. One that lets you keep building high-quality apps and data on top without the whole thing collapsing into a brittle mess six months later.

It's also the Obsidian of no-code platforms. Built for power users who want to shape their own environment instead of being gently but firmly shoved into someone else's idea of "optimal framework." If you prefer extensibility, emergent design, and thinking for yourself over prepackaged CRM, HR, and productivity tools, you'll feel right at home.

And yes, it's the Revolut of collaborative document systems. Fibery acts as a modern operating layer on top of your legacy data, wrapping projects, products, and operations into a single collaborative workspace that's automation-ready instead of automation-hostile. Documents stop being cumbersome and start being operational.

Heck, I am writing this post in Fibery. Because even their text editor is one of the best I've found—and I tried many!

Of course, when compared to the likes of Notion and Airtable, Fibery is still the underdog. Brand awareness is modest. Market share is small. You won't impress your CEO by casually dropping its name in a meeting.

Same with my Pixel phone. The guy at the phone shop, who gave it a new screen protector yesterday, looked at it with interest. "What type is this? We don't see these very often."

Yeah, that’s exactly the point. I buy only the best, and I'm proud to be one of the lucky few.

Fibery is the build-your-own Oracle for tech leaders who have absolutely no desire to invite Oracle into their lives.

If you want, and you ask nicely, I might write another few posts describing how I've actually built my systems in Fibery. That would require a bit more time, but the nerds among you might love it.

Now, the elephant in the room…

GDPR

And now we arrive at the part where everyone sits up straight, lowers their voice, and whispers the inevitable acronym: GDPR.

Let's get a few things clear before anyone forwards this post to their lawyer.

I am not responsible for your GDPR violations. I'm responsible only for mine. What you do with your data, your tools, and your brilliant or terrible ideas is entirely up to you. I'm showing you how I work; I'm not giving you my legal blessing.
Intent and outcomes matter. The purpose of what I'm doing is better service and better relationships. That's my goal. Remembering who people are. Not asking them the same questions twice. Not treating loyal supporters like anonymous blobs in a dashboard. This is not about spamming people through sales funnels, growth hacks, or other marketing terrorism. That's my choice. Yours may differ. But let's be clear: GDPR was designed to prevent abuse of personal information—not to prevent you from being competent, respectful, and helpful to others.
Context matters too. There's a difference between a solopreneur with a few thousand personal contacts versus a global enterprise hoovering up behavioral data by the terabyte. Yes, the law is the same for everyone. No, enforcement and expectations are not. Compliance scales with the scope, sensitivity, and the impact of the data you collect. If you're running a multinational surveillance operation that would be the envy of a dystopian nation state, your obligations look very different from those of a solo creator trying to remember who attended which Zoom call.
Fibery stores data in the EU by default. For standard workspaces, Fibery stores all their data in Amazon Web Services' EU-Central region. That doesn't magically solve GDPR for you, but it does remove an entire class of late-night anxiety about where your data physically lives. (And it's another point scored by Fibery over their US-based rivals.)
The boring stuff is unavoidable. If you're processing personal data, you're going to need terms of service and a privacy policy. These documents explain what data you collect, why you collect it, and what people can expect from you. Yes, they're dull. If you collect data through LinkedIn, Substack, Zoom, etc. the policies of those platforms apply. But if it's through your own website, make sure you're legally covered.
If someone asks to be removed, you remove them. Period. No arguments. No "but my system is complex." No "just this one backup." GDPR is crystal clear on this, and so should you be.

GDPR is not a monster under the bed. It's a framework meant to stop misuse of personal data. Be respectful. Be transparent. Be proportional. Be safe and secure. No lawyer will mistake you for Sam Altman or Elon Musk. The EU has much wealthier and sneakier fish to fry. But take full responsibility for your setup, because no one else is going to do it for you.

Conclusion

It is my aim to give paying customers, shareholders and subscribers the care they deserve without me logging into six different platforms. I want to respond proactively to patterns emerging from the data—thanking a reader who's given one of my Substack posts her 100th like, replacing her bouncing email address with another that works, celebrating that we've known each other for ten years. You know, the nice things.

AI agents and workflow automations can help with that. But not as long as your data looks like shit that hit the fan. Those agents will never be able to do their work if they have to log into twenty different SaaS tools and figure out for themselves which data corresponds to which people. That's inefficient, ineffective, and expensive. It's a great way to quickly blow through all your token credits. It would be like asking a brilliant kid to repeatedly solve complicated puzzles for you—by hiding the puzzle pieces in kitchen closets, under beds, behind paintings, and in cardboard boxes in the attic. It's a waste of their time.

If you want to make a difference in the agentic era, you need to make it easy for AI agents to do great work for you.

Clean up your crap.

With Fibery, I've made significant progress retrieving the pieces of the puzzle from all over my digital house. The next step is setting the agents to work, alerting me to patterns I'd never be able to detect myself.

If you want, I can take you along for the ride.

— Jurgen, Solo Chief

P.S. Let me know if you want me to go into more detail or not.

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