When Spirit Airlines went under, the planes and routes got the headlines. The quieter sale was stranger: Google paid $10 million for the airline's data — de-identified business records, software code, and operations history — at the bankruptcy auction, and said it plans to use the trove to improve its AI models (Reuters, Axios).
Nobody paid eight figures for Spirit's desks. They paid it for the records. That's the clearest signal yet of what business data has become: not a byproduct of doing business, but an asset in its own right.
You don't have an airline's worth of data. But the same logic applies at the scale of a 10-person shop — and the AI era makes your data pay twice. Here's why, and here's the 30-minute audit that puts it to work.
Why Buyers Care About Data Now
When a small business sells, the price is mostly a multiple of earnings. But the multiple itself moves with risk. A service business that depends entirely on the founder's daily involvement might sell for two to three times earnings; a business with recurring revenue, a strong team, and diversified clients can command five or six times (Forbes).
What's inside that gap? Transferability. A buyer is asking one question: does the value of this business leave when the owner does?
Clean, organized, exported data is the most underrated answer to that question:
- Customer history — who buys, how often, at what price points
- Operational records — job history, costs, turnaround times, warranty claims
- Pricing rules — documented rate logic instead of "it's in the owner's head"
- Vendor and contract terms — renewable agreements a buyer inherits
A business where that information lives in the owner's inbox sells at a discount, if it sells at all. A business where it's organized sells at a premium. Buyers price risk relentlessly — and messy data is risk.
The Second Payoff: AI Readiness
The Spirit sale points at the second reason this matters now. Google bought that data to train AI. The same shift is happening at every scale: businesses want to put AI to work, and AI can only work with what it can read.
Every AI automation — drafted follow-ups, invoice chasing, lead qualification, demand forecasting — runs on the same fuel: your data, in a usable form. A business whose records live in five SaaS tools, twelve spreadsheets, and one founder's memory has nothing an AI agent can use. The 30-minute audit below is, not coincidentally, also step one of almost every automation project.
That's the double payoff: the same data hygiene that makes a business sellable is what makes it automatable.
The 30-Minute Data Audit
This isn't a data-science project. It's a map. Set a timer and answer four questions.
Step 1: Where does data live? (10 minutes)
List every place your business information is stored. Most small businesses end up with five buckets:
- SaaS tools — CRM, scheduling, invoicing, email marketing, POS
- Spreadsheets — the tracking files nobody admits they rely on
- Email and text threads — pricing quotes, client decisions, supplier terms
- Paper and notes — job-site notes, receipts, the notebook in the truck
- People's heads — pricing logic, supplier terms, "who we don't work with anymore"
Write the buckets down. Don't fix anything yet — just see the sprawl honestly.
Step 2: What's exportable? (10 minutes)
Go down your SaaS list and run the export test for each: can you get a full export — right now, without contacting support?
A CSV export button and an API key are the baseline. If the only path to your own data is "email our success team," that's a flag — your data lives in someone else's vault. Note each tool as exportable or locked.
This matters in a sale (buyers ask for data rooms, not logins) and it matters for automation (your AI can't use what it can't reach).
Step 3: Who owns each piece? (5 minutes)
For each bucket, note who depends on it and what breaks if that person leaves. The spreadsheet only one person can read, the pricing logic only the founder knows — these are your single points of failure, and they're exactly what buyers and lenders probe.
Step 4: Write the one-page data map (5 minutes)
Turn your notes into a single page:
| Data | Where it lives | Exportable? | Owner |
|---|---|---|---|
| Customer list | CRM | Yes | Ops |
| Job history | Spreadsheets | Yes | Owner |
| Pricing logic | Owner's head | No | Owner |
That single page is the deliverable. It becomes the backbone of a data room if you ever sell, and the starting point for any AI automation you attempt.
What to Do With the Map
Once the audit exists, three moves pay for themselves:
- Close the export gaps. Move anything sitting in a locked tool to a place you control, or at minimum set a recurring export. Recurring monthly exports of every SaaS tool is the cheapest insurance in business.
- Get the head-data out. The pricing rules and supplier terms that live in your head are worth more written down than stored. A one-hour session with an AI assistant dictating "how we price" produces a document a buyer — or an AI — can actually use.
- Feed the map to an AI agent. Hand your data map to any capable AI assistant with a prompt like: "Here's where my business data lives. List the five automations this data supports, ranked by hours saved." That's a faster route to an automation roadmap than most paid audits.
Honest Limits
A few caveats, because this topic attracts over-promising:
- Google's $10M purchase is an outlier. It involved millions of operational records from a national carrier. Your data won't sell at auction — its value shows up as a smoother sale, a better multiple, and lower diligence risk, not a headline number.
- A data audit doesn't create value out of nothing. If the underlying business is unhealthy, clean books won't fix it. Data hygiene multiplies value; it doesn't substitute for it.
- Doing the audit once isn't the win. The win is the habit — quarterly, 30 minutes, re-run the map.
The Bottom Line
Spirit Airlines' most interesting asset turned out to be its records. For a small business, the lesson isn't "someone might buy your data" — it's that your data is the part of the business that survives you, and it's the fuel every AI tool needs. Most owners are sitting on both a sellability gap and an automation opportunity, and they're the same gap.
Thirty minutes and one page closes both.
Want help with step three — turning your data map into working automations? The Boring Automation Pack includes ready-to-use templates for the follow-up, review response, and reminder workflows your audit will surface.
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