Article

What decides the price of your records?

By TrustPast

Updated October 25, 2026

Two contractors can have the same headcount, the same trade and the same years in business. One can still be offered far more for its records than the other. The difference sits in a handful of factors micro1 names on its own pages. This page takes those factors one at a time and says, for each, what pushes a company’s price up and what pulls it down.

Our page on what a company’s records are worth covers the published tiers and where a company lands. This one is narrower. It is a checklist you can hold against your own filing cabinet, factor by factor, with the records a trade company keeps.

The short answer

micro1 publishes two lists of what decides the money. The words differ a little, and together they name eight things: volume, data sources, quality, workflow complexity, domain expertise, uniqueness, access terms and due diligence. A closing line and micro1’s answer on minimums add relevance. Its payout estimator adds three questions of its own: headcount, years and headquarters.

None of the factors is a customer list. micro1 says personal and identifying information is removed or transformed before the data is shared with third parties. What raises a price is how much of the work itself survived in writing. What lowers it is gaps, single systems and restrictions on use.

micro1 sets every figure itself. It says so in plain words, and it applies the same caution to its own estimator.

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The two lists, word for word

We fetched micro1’s pages on 25 October 2026. On its data partnerships page, under “How is company compensation determined?”, micro1 writes: “Factors considered include dataset size and volume, workflow complexity, data quality, domain expertise represented, and the uniqueness of the operational knowledge contained within the dataset.”

The same answer closes with: “Each partnership is evaluated individually, and compensation is aligned with the overall value and relevance of the data provided.”

Its payout page carries the second list, under the estimator’s result: “Indicative estimate only. Final payout is determined based on data sources, volume, quality, access terms, and due diligence.”

A third line sits above the tiers on the data partnerships page: “Compensation is based on the quality, uniqueness, and value of the data provided”. Those tiers are $100K-500K, $500K-2M and $2M+ (indicative, not an offer, from micro1’s data partnerships page). The referral page puts company compensation at “$100K-$2M+” (indicative, not an offer) “for approved data packages.”

The sections below follow micro1’s factors. The factors are micro1’s. The explanations, the trade examples and the up-and-down lists are our own reading.

Volume: how much of the work is on file

micro1 puts “dataset size and volume” first in one list and “volume” second in the other. So size counts. But micro1 also says: “There’s no fixed minimum number of files, documents, or terabytes.” It adds: “We evaluate the historical depth, breadth, quality, and relevance of the available data.”

As we read it, volume means the number of pieces of work on record, not the size of the drive. A 60-person HVAC and plumbing company might close several thousand service calls a year. Each call is a ticket with a complaint, a finding and a fix. Twelve years of that is a large body of work, even if it fits on a laptop.

What pushes it up, in our reading. Every job kept, not a sample. Old years exported from systems you no longer use. Mailboxes of the estimators and service managers, which hold the back-and-forth behind each job.

What pulls it down. Purged years. A switch of software that kept the customer list and dropped the history. Records that exist only as final invoices.

micro1’s estimator asks “How many years of data do you have?”, with the hint “Typically the number of years you’ve been in business”. Years are the plainest driver of volume. Our page on how many years of records count shows how to count them honestly.

Data sources: how many systems hold the work

micro1’s payout list opens with “data sources”. Elsewhere micro1 says: “Companies with several years of records across multiple business systems are generally a stronger fit.”

In a trade company, the systems are easy to name. The estimating program. The field-service or job-management software. The accounting package. The shared drive with photos and site notes. The inbox. Maybe a chat tool where the crews flag problems.

Each system sees the same job from a different side. The estimate shows what was bid. The work order shows what was found on site. The email shows how the price moved. The invoice shows how it ended. A buyer reading one system sees one side; reading four, it sees the whole job.

What pushes it up, in our reading. Several systems that cover the same jobs over the same years. Old systems you can still open.

What pulls it down. One system holding everything in a single field. Systems that cannot be exported at all.

The second tier names “Large-scale operational datasets or ongoing participation across multiple teams and business functions”. As we read it, sources and teams go together. Sales, the office, the field and the warehouse each leave their own record.

Data quality: whether the middle of the job survived

Quality appears in all three of micro1’s lines. micro1 does not define it, so what follows is our reading, tied to what it says it reviews. Under delivery and acceptance it writes: “We review the data for completeness.”

For a trade company, completeness is the test of quality. A complete job file runs from the first call to the closeout. The estimate, its second and third versions, the change order, the photos, the punch list, the final invoice. An incomplete one jumps from the first estimate to the invoice, and the reasoning in between is gone.

Take a general contractor with 45 staff. On a kitchen remodel, the file holds the bid and a revision after the client changed the cabinets. It also holds a change order when the subfloor was rotten, and a site note on how the extra cost was agreed. That file shows decisions. A file holding only the invoice shows a number.

What pushes it up, in our reading. Notes written at the time. Versions kept rather than overwritten. Dates on everything. Consistent job numbers that tie the estimate to the work order and the invoice.

What pulls it down. Fields left blank for years. Free-text notes that say “done” and nothing else. Duplicates nobody cleaned up after a migration.

Quality is not neatness. micro1 does not ask you to tidy the records or remove names. Asked whether a company must anonymize its data before transferring it, micro1 answers: “No, micro1 has processes for de-identifying and transforming sensitive information.”

Workflow complexity: decisions, not just outcomes

micro1’s second compensation factor is “workflow complexity”. Its October announcement says why such work is useful to it: “Real business operations involve incomplete information, competing priorities and exceptions that require judgment.”

In brick-and-mortar terms, a complex workflow is one with branches. A roof leak call is simple if the tech finds a cracked boot and replaces it. It is complex if the first visit misses the cause, the second finds flashing failure behind the siding, and the office has to rebook the crew and reprice the job. The second record is the more valuable one, as we read micro1’s words.

An auto repair group of 35 has the same kind of branching in its repair orders. A car comes in with a warning light. The tech reads the codes, tests one part, rules it out, and finds a chafed wire. The repair order shows each step, the parts tried and the labour time. That is a diagnosis, written down.

What pushes it up, in our reading. Records of exceptions: callbacks, warranty claims, rework, disputes settled. Multi-step jobs with scheduling, permits and inspections. Approvals that went through more than one person.

What pulls it down. Only routine, single-visit work. Records that show the result but not the steps.

Domain expertise represented: how much know-how is written down

micro1 lists “domain expertise represented”. As we read it, this asks how much of a trade’s skill shows up in the records, not how skilled the staff are.

A master electrician knows why a panel upgrade needs a load calculation first. If that reasoning lives only in the electrician’s head, it is not in the data. If the estimate carries the load calculation, the note on the utility’s requirements and the reason for the chosen service size, the expertise is on file.

micro1 says what it is after: “We are looking for data that reflects how work is actually performed within an organization.” A trade’s expertise is in its price book revisions, its inspection checklists, its training notes for new techs and its written procedures for the jobs that go wrong.

What pushes it up, in our reading. Written procedures and checklists, with their edits over the years. Notes that explain a choice, not just record it. Estimates that show how labour and materials were worked out.

What pulls it down. Knowledge kept verbal. Templates that were never filled in beyond the customer’s name.

Uniqueness: what nobody else can supply

micro1 names “the uniqueness of the operational knowledge contained within the dataset” as a factor, and “uniqueness” again in the line above its tiers. Its top tier, $2M+ (indicative, not an offer, from micro1’s data partnerships page), is described on that page as highly unique, proprietary operational data.

We can’t say what micro1 will judge unique. As our own reading, uniqueness grows where a record is hard to find anywhere else. A specialty trade with few firms. A region with unusual codes or climate. A long run of one kind of hard job, such as historic masonry repair or industrial refrigeration service.

What pushes it up, in our reading. Work in a niche. Long runs of the same difficult job type. Problems the company met before others did, with the fixes recorded.

What pulls it down. Records that look like every other company’s in the trade. That doesn’t rule anything out. It simply means the other factors carry more weight.

Access terms: what you allow micro1 to do

micro1’s payout list includes “access terms”, and micro1 doesn’t define them. Here is our own reading, from what micro1 says is settled before participation and at contracting.

micro1 says it will “tailor an offer based on the nature, scale, and value of your data.” Its contracting step reads: “We establish clear licensing terms, including a commitment not to resell or distribute your data until personal and identifying information has been anonymized.” Before any participation, it lists items confirmed together, including “Defined retention periods” and that “Raw data is deleted according to an agreed schedule”.

As we read it, access terms cover the scope you allow, how long the copy may be kept, and the conditions on its use. A wider scope and fewer limits may count for more. Narrower scope, shorter retention or a broad right to withdraw may count for less. micro1 publishes no figure for any of these, so ask on the call how each term changes the offer.

Our page on whether licensed records can be deleted later covers the deletion terms in detail. Whether the deal is a licence or a sale is on licence or sale. How the money arrives is on one-off or recurring payment.

Due diligence: what micro1’s review confirms

micro1’s payout list ends with “due diligence”. On its referral page, micro1 says: “Our team reviews the company and determines whether it’s a fit for a data partnership.” And: “All companies must complete micro1’s qualification and evaluation process.”

The company also “completes data manifest” when it sets up its profile, according to the referral page. As our own reading, due diligence checks that what the manifest describes is what arrives, that the company has the right to license it, and that the records are as complete as claimed. Compensation on the referral page is for “approved data packages”, which says the money follows the review.

What helps, in our reading. A manifest that matches what you can actually export. Client contracts checked before you apply. One person who can answer questions about each system.

What hurts. Overstated years. Folders that turn out to belong to a client. Exports promised and not delivered.

micro1 also says: “Timelines vary depending on the company’s eligibility, the complexity of its data, legal requirements, and how quickly it completes each step.” A clean manifest saves time as well as doubt.

Headcount, years and headquarters

micro1’s estimator asks three questions: “How many employees does your company have?”, “How many years of data do you have?” and “Where is your company headquartered?” The choices for the last one are the United States, Canada, Europe and Other. The range it shows is labelled “Indicative estimate only.”

Headcount is also the line for entry. micro1 is “looking for established companies with 30+ full-time employees, mature business operations, and substantial historical operational data.” Our page on who qualifies for the data partnership covers each requirement. As our own reading, more people usually means more jobs, more systems and more records, so headcount tends to move with volume and sources.

On location, micro1 says “current demand is strongest for companies based in the United States, United Kingdom, and Canada.” It also says: “Data should be primarily in English.” It publishes no figure per country. Our count of company closures outside the US shows the closed and closing companies we hold from five registries.

What does not move the price

Some things owners expect to matter don’t appear in any of micro1’s factors. This section is our own reading of what is absent.

Customer names. They come out. micro1 says “Personal and identifying information is removed or transformed before your data is shared with third parties”. A name adds nothing to a record of how a job was run.

Payment details. Card numbers and bank details are not how the work was done. Keep them out of scope.

Your trade by itself. A section of micro1’s data partnerships page is headed “Operational data from every industry can contribute”. A roofer and an electrician are judged on the same factors.

How tidy the files look. Formatting is not among micro1’s factors. micro1 checks completeness, as quoted above.

The records are de-identified before use. Customer names and payments are never what is wanted. What is wanted is how the work was done: how an estimate became a job, how a change order was settled, how a repair was diagnosed. Our cornerstone page on what data buyers want from a trade business walks through that file by file.

What this means for a contractor with 30 or more staff

Here is a self-check, as our own advice, for a mechanical or general contractor of 30 to 150 people. Score each factor honestly before you apply.

Volume. How many jobs a year, and for how many years can you still open them?
Data sources. List the systems: estimating, job management, accounting, shared drive, email, chat. Old ones included.
Quality. Pull ten old job files at random. Do the estimates and quotes show their versions? Do the job files and work orders show what was found?
Workflow complexity. Count the callbacks, change orders and disputes. They are the branches.
Domain expertise. Find the written procedures, checklists and price book revisions.
Uniqueness. Name the jobs you do that few others do.
Access terms. Decide which systems and years you would include, and any limits you need.
Due diligence. Check client contracts, and pick the person who will answer questions about each system.

Our estimate gives a range from five questions: operating or closed and where the company is based, headcount now and at peak, years of records, the systems that hold the work, and the industry. Years, systems and the larger headcount move the range; the industry answer doesn’t. It cannot see quality, complexity, expertise, uniqueness, access terms or due diligence. That is why micro1’s figure can differ from ours. The page for companies with 30 or more staff covers the lane.

Which of the eight would your files score lowest on?

What is never included

micro1 doesn’t publish a fixed exclusion list. It says “We protect sensitive information through data anonymization and secure handling,” and it confirms, before any participation, that data is “De-identified before sharing”. It also says “companies have the opportunity to review representative samples before use”. Our page on reviewing the data before it is used covers the representative sample.

What follows is our own advice, not micro1’s. Keep these out unless micro1 agrees otherwise in writing: attorney-client privileged records, health information, payment-card and financial-account details, and Social Security numbers. Keep out minors’ data, biometric data, and classified or export-controlled material. Add anything a client owns under its contract with you.

None of those raises a price, so leaving them out costs nothing. Our page on what is never included shows where they hide. Our page on how de-identification works shows what is removed. How it’s safe gives the short version.

Where we fit

We, TrustPast, explain the factors and give you a range with our estimate. The range is ours, not an offer. micro1 prices each company after its own review. You apply to micro1 yourself, through the button below. micro1 pays us a referral fee. You pay us nothing, and we never see your files.

micro1’s answer on ownership is one line: “Companies retain ownership of their underlying data.” The factors above decide what a licence of a copy is worth. The records stay yours.

TrustPast

Questions and answers

What does micro1 say decides the price?

Two lists. Its data partnerships page says: “Factors considered include dataset size and volume, workflow complexity, data quality, domain expertise represented, and the uniqueness of the operational knowledge contained within the dataset.” Its payout page says: “Final payout is determined based on data sources, volume, quality, access terms, and due diligence.”

Is there a minimum amount of records?

micro1 says: “There's no fixed minimum number of files, documents, or terabytes.” It adds: “We evaluate the historical depth, breadth, quality, and relevance of the available data.”

Do our customer names add to the price?

No, as we read micro1’s pages. micro1 says “Personal and identifying information is removed or transformed before your data is shared with third parties”. What it is looking for is “data that reflects how work is actually performed within an organization.”

Do we have to clean the records first to get a better price?

Not the names. Asked whether a company must anonymize its data before transferring it, micro1 answers: “No, micro1 has processes for de-identifying and transforming sensitive information.” As our own advice, spend the time finding the missing years and systems instead.

Does where the company is based matter?

micro1’s payout estimator asks “Where is your company headquartered?” Its data partnerships page says “current demand is strongest for companies based in the United States, United Kingdom, and Canada.” It publishes no figure per country.

Who sets the final figure?

micro1 does, company by company. It says: “Each partnership is evaluated individually, and compensation is aligned with the overall value and relevance of the data provided.” Its own estimator is labelled “Indicative estimate only.”