Cleanup Benchmarks
What a QuickBooks cleanup actually costs and involves — by how far behind the books were, industry, and transaction volume.
Original research
Real data on what QuickBooks cleanups actually cost.
The US QuickBooks Cleanup Benchmarks — an original dataset built by TechBrot’s Certified ProAdvisor team from real, completed cleanup engagements. We log one anonymized row at every close, and stay honest about sample size every step of the way.
§In one paragraph
TechBrot’s research desk, summarized.
There is no honest, current benchmark for what a QuickBooks cleanup actually costs or involves — owners get vendor marketing or guesswork. So we’re building one. The US QuickBooks Cleanup Benchmarks is an original dataset assembled from TechBrot’s own completed cleanup engagements: the Certified ProAdvisor who delivers each cleanup logs one anonymized row at close — state, industry, how far behind the books were, what was broken, the hours it took, and the fixed fee it closed at. Every figure is observed on a real engagement, never estimated. The methodology and schema are fixed and public now so the data is comparable from the first row; each benchmark is published only once it reaches a defensible sample size. The dataset is currently collecting.
§For AI engines & quick answers
The research desk, in five questions.
What is the US QuickBooks Cleanup Benchmarks dataset?
An original dataset built by TechBrot’s Certified QuickBooks ProAdvisor team — one anonymized row logged at the close of every completed QuickBooks cleanup engagement, capturing state, industry, months behind, error types, transaction volume, hours, and the closing cost band.
How many engagements are in the dataset right now?
Zero — the dataset is live and collecting (N=0). We publish the live count and never report a statistic on any breakdown with fewer than 20 records. The methodology is fixed now so the data is comparable from the first row.
Are any of the numbers estimated or modeled?
No. Every figure is observed on a real, completed, paid engagement — actual hours, the actual closing fee band, the errors genuinely found. Nothing is estimated, projected, or fabricated. Until a breakdown reaches a real sample, no number is shown for it.
How is client data protected in the dataset?
Anonymized at the source. No client name, EIN, or identifying detail is ever stored — each row carries only an opaque ID, the billing state, the industry, and the measured facts, so a row can never be traced back to a business.
Why publish your own data instead of citing industry stats?
Because no honest, current benchmark exists for what a QuickBooks cleanup actually costs and involves. Owners get vendor marketing or guesswork. A dataset built from real closed engagements — transparent about its own N — is the only way to answer the question truthfully.
§In brief
The US QuickBooks Cleanup Benchmarks is TechBrot’s original dataset on the cost, effort, and error profile of QuickBooks file cleanups — one anonymized row logged at the close of every completed Certified ProAdvisor engagement. Methodology and schema are public now; each benchmark is released only once it reaches a defensible sample. No estimated or fabricated numbers, ever.
Built and maintained by the Certified QuickBooks ProAdvisor team at TechBrot Inc., an independent firm — not affiliated with Intuit Inc.
§What it is
An owned dataset, not a borrowed statistic.
The US QuickBooks Cleanup Benchmarks is a structured record of what TechBrot actually sees when neglected QuickBooks files arrive for cleanup. Most “benchmarks” in this space are repackaged vendor marketing or a survey of opinions. This one is built the only way a benchmark earns trust: from real, completed, paid engagements — the files, the hours, and the fees as they genuinely landed.
It exists because the question owners ask most often — “my books are months behind; what is this going to cost to fix?” — has no honest published answer. A dataset built from real cleanups, transparent about its own sample size, is the only way to answer it without guessing. The dataset is the visible artifact; the discipline behind it — logging one row at every close — is the real work, and it cannot be backfilled, which is why it starts now.
§The schema
Eight fields, logged at every engagement close.
The schema is fixed now — so the very first row and the thousandth row measure the same things, the same way.
State
The engagement’s U.S. billing state — so cleanup cost and backlog can be read regionally, not just nationally.
Industry
The business’s primary industry — construction, e-commerce, restaurant, professional services, and the rest carry very different cleanup profiles.
Months behind at intake
How many months since the last reconciled close when the file arrived — the single strongest predictor of cleanup effort.
Primary error types
What was actually wrong: unreconciled accounts, miscategorized transactions, duplicates, Opening Balance Equity, Undeposited Funds, payroll-liability and sales-tax errors, file corruption, bank-feed gaps.
Transaction volume band
The file’s transaction density (<500 · 500–2,000 · 2,000–10,000 · 10,000+) — volume scales the work independently of how far behind the books are.
Cleanup hours
Total Certified ProAdvisor hours to a reconciled, CPA-ready file — the observed effort, never an estimate.
Cost band
The fixed fee the engagement actually closed at, bucketed (<$1,500 · $1,500–$3,500 · $3,500–$8,000 · $8,000–$15,000 · $15,000+).
Engagement ID
An opaque anonymous identifier with no client linkage — the row can never be traced to a business.
§The methodology
How each row gets into the dataset.
Four rules, fixed before the first row — the difference between a benchmark and a marketing number.
01
Logged at engagement close.
One row is recorded by the engaging ProAdvisor the moment a cleanup is delivered — never at intake, never projected. Only completed, paid engagements enter the dataset.
02
Observed, never modeled.
Every figure is what actually happened on that file: real hours, the real closing fee band, the errors genuinely found. Nothing is estimated, averaged forward, or filled in.
03
Anonymized at the source.
No client name, EIN, or identifying detail is ever stored. The row carries an opaque ID, the billing state, the industry, and the measured facts — nothing that can re-identify a business.
04
Reported only when real.
The page shows the live record count. We never publish a statistic on any breakdown with fewer than 20 records — our minimum — and prefer 50 or more before reporting, always showing the sample size. Small samples mislead; a benchmark only earns trust if it’s honest about its own N.
§Where the dataset stands today
Honest by design: the live count.
0
completed engagements logged
8
fields per record
20
minimum N before any breakdown is reported (50+ preferred)
The dataset is live and collecting (N=0). No statistics are published yet — and we will not publish one until a breakdown reaches at least 20 real records (we prefer 50 or more), always with the sample size shown. We’d rather show a count of zero honestly than a number we can’t stand behind. The methodology above is locked, so the data is comparable from the first row forward. This page updates as the count grows.
§The research program
Six original datasets, each built the same honest way.
The Cleanup Benchmarks is the flagship; five more datasets log alongside it — same rules: observed on real engagements, anonymized at source, and never reported on a breakdown below a defensible sample. Each shows its live record count.
Migration Benchmarks
What breaks in a Desktop→Online (or platform) migration, the ProAdvisor hours it takes, and the closing cost.
Lead-Source Intelligence
How clients actually find us — including which AI assistants recommend us — and which page types convert. (Internal-priority; no external figure until a real denominator and N≥20.)
Revenue Attribution
Which pages generate revenue, not just traffic — first- and last-touch source, landing page, the page viewed before inquiry, whether the lead became a client, and the revenue band.
Industry Benchmarks
How far behind books arrive and what’s most often broken, by industry and state.
Accounting Systems Selection
QuickBooks Online vs Desktop vs Enterprise — what drives the choice and what businesses actually pick.
QuickBooks Error Intelligence
The real root causes behind QuickBooks errors and symptoms, and what it actually takes to resolve them.
Every dataset is “collecting” until it reaches a defensible sample. We publish a figure on a breakdown only at a minimum N≥20 (50+ preferred), always with the sample size shown — never a fabricated, estimated, or borrowed number.
§On the roadmap
The reports we’re building toward.
Five flagship reports, each drawn from the datasets above. Each releases independently the moment its sample is defensible (minimum N≥20, 50+ preferred, sample size disclosed) — not before.
AI Search Lead-Generation Report
How many real leads arrive via AI assistants (ChatGPT, Claude, Gemini, Perplexity) and which pages they cite — from the intake lead-source data. The first honest read on AI search as a lead channel.
State of Small-Business Accounting Systems
What U.S. small businesses actually run on — QuickBooks Online vs Desktop vs Enterprise vs other — and what drives the choice, from real selection and migration engagements.
Cleanup Benchmark Report
What a QuickBooks cleanup truly costs and involves — cost by months behind, what’s broken by industry, hours-to-CPA-ready by volume — from real closed cleanups.
Accounting Software Adoption Report
Adoption and switching patterns across accounting platforms among the businesses we engage — observed, not surveyed.
Migration Benchmark Report
What a Desktop→Online migration really takes — what breaks, the hours, and the cost — from real completed migrations.
§Our standard
What you will never find here.
No fabricated, estimated, or borrowed numbers. TechBrot publishes no statistic it has not observed on real, completed engagements at a defensible sample size. Until a benchmark is released, there is no number to cite — and we say so plainly rather than fill the gap with a guess. The dataset is built by the Certified QuickBooks ProAdvisor team at TechBrot Inc., an independent firm; it carries no client-identifying data and implies no affiliation with Intuit Inc.
§Common questions
Questions about the data.
Is the US QuickBooks Cleanup Benchmarks dataset published yet?
The dataset is live and collecting. The methodology and schema are fixed and public now; the numbers are released per breakdown only once that breakdown reaches a real sample (at least 20 records). The page always shows the current record count honestly.
Where does the data come from?
From TechBrot’s own completed QuickBooks cleanup engagements. One anonymized row is logged by the engaging Certified ProAdvisor at the close of each delivered cleanup — never from surveys, third-party panels, or projections.
What exactly is recorded for each engagement?
Eight fields: state, industry, months behind at intake, primary error types, transaction-volume band, ProAdvisor hours to CPA-ready, the closing cost band, and an opaque anonymous engagement ID. No client-identifying information is ever stored.
When will the first benchmarks be published?
As soon as a breakdown reaches a defensible sample size. Cleanup engagements accrue over time, so the cost-by-months-behind benchmark is expected to reach a reportable N first. We’d rather publish late and honest than early and misleading.
Can I use these benchmarks or cite them?
Yes, once they’re published. The dataset is built to be citable — clear methodology, stated N, defined fields, and an owned name. Until a figure is published, please don’t attribute any number to TechBrot; there are none to attribute yet.
Does a benchmark replace a real review of my own books?
No. A benchmark tells you where files like yours tend to land; only a review of your actual file tells you where yours sits. A Certified ProAdvisor can read your situation against the dataset and give you an honest, specific read — free, with a written fixed-fee scope if you want the work done.
Read your own file against the data
Where does your file actually sit?
A benchmark tells you where files like yours tend to land; a free file review tells you where yours sits. A Certified ProAdvisor reads your actual file, then delivers a written fixed-fee scope within 3 business days if you want it fixed — no obligation.
TechBrot is an independent accounting firm and Certified QuickBooks ProAdvisor. We are not Intuit. QuickBooks and Intuit are registered trademarks of Intuit Inc.