Buying comps data and having a comp set are different things, and the gap between them is where the analyst hours go.
A subscription answers "what transacted near here". Underwriting needs "which of these apply to this property, adjusted how, and can I defend the choice". Nothing in the first answer produces the second.
What The Platforms Actually Differ On
They are usually compared on price and coverage. The more useful axis is where their data comes from, because that determines what they are reliable for.
- Researched datasets — the largest providers employ researchers who call brokers and verify transactions. Broadest coverage, highest cost, and the strength is market context rather than any single record.
- Contributed lease comps — platforms where brokers contribute comps in exchange for access. Depth on lease economics that is hard to get any other way, with coverage that follows contributor density rather than geography.
- Public-record-led — ownership, transaction history and debt assembled from county records. Strong on who owns what and what it last traded for; thin on leases, which are rarely recorded.
- Marketplace-led — data derived from what is listed for sale. Excellent currency on what is on the market, and a structural bias toward asking prices rather than closed transactions.
The practical implication: sale comps and ownership are increasingly available from public records, while verified lease comps remain the expensive part. A team switching to save money usually discovers that in month two.
Test Coverage Where You Work
National coverage claims are close to meaningless for a firm operating in three submarkets.
Take ten properties you already know — ideally including two that traded recently and one with an unusual ownership structure — and check each platform on those. You are looking for whether the transaction is there at all, whether the price matches what you know, whether the date is the contract or the recording, and whether ownership resolves past the holding entity.
A platform that is excellent nationally and thin in your county is a subscription you will supplement anyway.
The Reconciliation Nobody Sells
Assume the data is good. You still have to:
- Decide which transactions are genuinely comparable — same asset type and tenancy profile, not just the same postcode.
- Separate transactions from listings that never traded.
- Catch the subject property appearing in its own comp set under a variant address. This happens more than anyone admits, and it is invisible in a spreadsheet.
- Adjust for the differences that matter, and state the adjustments rather than absorbing them into a conclusion.
- Reconcile records that disagree — an assessor's area against a recorded survey, a price that differs between sources.
- Be able to show the reasoning to someone who will argue with it.
This is not a data problem. It is the part a subscription hands back to you, and it is why teams with excellent data still spend days per property.
What A Defensible Comp Set Looks Like
Each comparable named, with a date and a source a reader can look up. A stated reason it is comparable to this asset. Explicit adjustments. And an honest note where the evidence is thin, rather than a confident number standing on two weak transactions.
If a comp set cannot survive being handed to someone who disagrees with the conclusion, it is not evidence. It is a list.
Where Titleman Sits
We are not a comps subscription, and we do not replace one where you need researched lease data in a specific market.
What we do is the reconciliation. Titleman assembles the property record first — parcel, ownership, zoning — then gathers comparable transactions from public records and the sources available, names each one with where it came from, applies and states adjustments, and flags the disagreements rather than resolving them silently. Where evidence is thin, it says so.
The output is a comp set with its reasoning attached, ready for a licensed professional to review and sign.
What None Of This Replaces
- A licensed appraisal where a lender or standard requires one.
- A broker's knowledge of why a specific deal traded where it did, which is frequently not in any dataset.
- Your own judgement about which differences matter for this asset.
Data platforms sell access. The conclusion is still yours, and the value of any tool in this category is how much of the argument it hands you already built.