A message from the author

Commercial real estate has plenty of software. Finding another platform is easy. Working out which one deserves your money, your attention, and a place in the way you do business is considerably more difficult.

There are established research platforms, specialist databases, prospecting tools, listing marketplaces, CRMs, underwriting products, and a growing collection of AI tools offering to make sense of all of it. Some do a narrow job extremely well. Others want to become the place you do everything. The range is genuinely interesting, although you could be forgiven for losing the will to compare another feature page.

Read enough of them and a peculiar thing happens: products built for quite different purposes begin to sound almost identical. Comprehensive coverage. Better intelligence. Faster decisions. You could rearrange half the adjectives without anyone noticing.

That is where my interest in this market begins. There is real variation underneath the language, and it matters much more than the language suggests.

A broker trying to identify an owner has a different problem from an investment team examining lease evidence. Someone researching a regional industrial market will judge coverage differently from someone tracking institutional transactions across the country. A lender looking at a particular loan needs a level of specificity that a general property record cannot provide. These people might all describe their requirement as “CRE data.” Their definitions of useful are miles apart.

Which makes the familiar question—what is the best platform?—rather difficult to answer honestly without asking a few more questions first. Best for whom? In which market? For which decisions? With what evidence available, and what permissions to use it?

I think a substantial amount of CRE data is mispriced. I also think the discussion about its cost is often too shallow to explain why.

Some information is expensive to produce and worth paying for. Verification takes effort. Research requires judgment. Maintaining a dataset through ownership changes, inconsistent records, and uneven source quality is a serious undertaking. Anyone who assumes all information should be cheap because it appears on a screen is welcome to have a go at maintaining it.

At the same time, a substantial subscription should come with a reasonably clear explanation of what makes it valuable. Familiarity, a large record count, and a persuasive presentation are insufficient answers to that question. The customer still needs to understand what is included, how current it is, where it is reliable, and how often it will materially improve the work.

A national coverage figure is a useful starting point. I would also like to know whether the fields I need are present on the properties I care about. A contact is useful when there is a defensible reason to believe that person is relevant. A comparable is useful when its context and limitations are understood. These distinctions can disappear surprisingly quickly once information is compressed into a row of ticks on a comparison page.

“Includes ownership data” leaves quite a lot unsaid.

Does it mean the recorded entity? Its mailing address? An explanation of the entity structure? A person associated with it? A recently checked route to the person making the decision? Each can have value. They deserve to be described precisely enough for a buyer to understand the difference.

The same applies to market research, tenant information, financial records, and comparables. Two products can use the same label for capabilities that overlap only partially. A thoughtful comparison has to get underneath those labels. Otherwise, we have produced an attractively formatted misunderstanding.

This is also why I have little patience for treating brokerage as one uniform activity. An experienced broker’s requirements depend on their specialty, geography, relationships, and how they win business. A platform that is excellent for one team can be an awkward purchase for another. A specialist product can justify its place through a single capability that its users depend on. A broad product has to demonstrate how well the pieces work together.

I would rather understand those tradeoffs than declare a universal winner and spend the rest of the article arranging the evidence around the trophy.

The commercial terms deserve similar scrutiny. What can you export? What remains accessible when the subscription ends? Which capabilities require another package? How much of the demonstrated experience is available to the person who will actually use it? Those questions influence value just as surely as the quality of the initial search result.

Then there is AI, which has made this market more interesting and its descriptions considerably less restrained.

I can see the appeal of asking a specific question and having software assemble the relevant research. There is substantial potential in making complex sources easier to navigate and keeping the evidence connected to the answer. A useful system could let someone investigate more thoroughly without demanding that they learn the internal structure of every database first.

But confidence of delivery is a poor substitute for confidence in the source. I want to know how an answer was reached, what was unavailable, and which parts require verification. When several records disagree, that disagreement is part of the answer. Tidying it out of sight might improve the demonstration. It does very little for the decision.

I am happy to be impressed by an AI product. I would simply prefer to inspect it before joining the standing ovation.

Time spent around commercial real estate has made me increasingly curious about these details: the difference between a capability people admire and one they repeatedly use; the information that changes an assessment; the feature a team would actually miss if it disappeared tomorrow.

I started CRE Data Tracker to give those questions more room.

This journal will look at individual products, practical workflows, and the assumptions behind the way CRE information is packaged and sold. I want to explain what a tool does well, where its limitations become relevant, and who is likely to find it worthwhile. When I have a strong opinion, you should be able to follow the reasoning. When the evidence is limited, that should be visible too.

I expect my views to change. A product improves. A source changes. Someone working in a market I know less well points out something I missed. Publishing an opinion should come with the willingness to revisit it. Otherwise, this becomes a rather elaborate way of preserving my own mistakes.

What I would like to build around the journal is a community of people willing to contribute that kind of perspective. Brokers, researchers, investors, operators, and the people developing these tools all see different parts of the same problem. Their experiences are worth bringing into the same conversation.

I am particularly interested in the specific observations: the dataset that is unusually useful in one market; the limitation that only becomes apparent after repeated use; the product that earns its place for a reason its own website barely mentions. Those are the details that help someone else make a better choice.

Disagreement is welcome. An example makes it considerably more useful. Tell me what you were trying to establish, what you used, and what you found. That gives us something to examine together.

The ambition here is straightforward: help people understand what they are buying, judge the evidence more carefully, and become more demanding about the value they receive. Good products should benefit from that scrutiny. So should the people paying for them.

There is plenty to write about. I intend to have a view.