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I started tracking UK business domain changes — it turned into something much bigger

MELIAM

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I've been working on a data experiment that originally started because of my interest in domains.

I wanted to see whether I could identify businesses that had changed from one domain to another by comparing successive monthly UK business/place datasets.

I compared July → August 2026 and found 14,044 own-domain → own-domain changes.

But once I'd built the comparison, I realised there was quite a bit more hiding in the monthly changes.

The same comparison found:
  • 56,976 existing-business records with a meaningful change
  • 90,234 newly observed places
  • 11,497 genuine phone-number changes
  • websites being added
  • websites being removed
  • places no longer observed
Rather than just recording that something changed, I've kept the useful business record with it — business name, category, location, postcode, phone, current website and the before/after values where applicable.

I've ended up building a small site around the experiment, ChangeCapture.co.uk/Samples, where I've put up 50-record samples of each change type so people can see what the data actually looks like.

I'm not really posting this as a sales pitch — the full files aren't even available yet. I'm interested in whether other people can see uses for this data that I haven't thought of.

Obviously, the 14,044 domain changes caught my attention as a domainer, but I'm starting to think the newly observed businesses and website-added/removed data could be just as interesting.

What would you look for in data like this?
 
The actual before-and-after domain swaps are honestly what I find most fascinating. Watching an established brand upgrade from a clunky multi-word URL to an exact-match, or move from a .co.uk over to the global .com, adds so much context that raw sale numbers completely miss. It really highlights the commercial justification behind why that specific buyer pulled the trigger.
 
That's exactly the sort of thing that got me started on this in the first place.

The before/after is what I found interesting too, because instead of just seeing that a domain is now being used by a business, you can see what it replaced.

With 14,044 own-domain to own-domain changes in one monthly comparison, I'm wondering whether there are patterns in there — .co.uk to .com, long domains to shorter ones, rebrands, exact-match upgrades, etc.

I hadn't thought about matching those changes against historical domain sales though. That could add another interesting layer to it.

Once I've got several months rather than just July → August, I think the history could become more useful than any individual monthly snapshot.
 
Thanks, that's pretty much how I'm looking at it. The comparison process should work with other countries as well, but I think there's enough to learn from the UK data first.

I'm particularly interested to see what becomes more useful once I've got several consecutive months rather than just the July → August comparison. A proper history of changes could be more interesting than any single monthly dataset.

I'm also interested in what happens to the old domains when businesses move to a new one - particularly whether any of those old domains eventually expire and become available to register. With 14,044 own-domain → own-domain changes in this comparison alone, that could be an interesting dataset in itself.
 
https://shoplocator.williamhill/ That’s a sponsored tld.

WilliamHill.com was registered in 1995. Another question you could look at is when did the “new” website address get registered, was it recently sold, etc. because obviously a company that chooses to have a STLD is large enough that it has a large amount of its ip locked up.
 
https://shoplocator.williamhill/ That’s a sponsored tld.

WilliamHill.com was registered in 1995. Another question you could look at is when did the “new” website address get registered, was it recently sold, etc. because obviously a company that chooses to have a STLD is large enough that it has a large amount of its ip locked up.
That's a very good point. Domain registration age hadn't occurred to me as another layer to add to the change data. It could be particularly interesting to distinguish a move to a newly registered domain from a move to a long-established domain, and also check what subsequently happens to the domain they've moved away from. I'll have a look at whether I can add that to the analysis.
 
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