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How Do We Pull Property Listings From Several Agents and Portals Into One Place?

Aggregating property listings by hand from agents and portals is slow and full of duplicates. SpiderHunts builds a permitted, deduplicated listings feed.

Updated 3 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Investors, buying agents and property businesses track listings across portals and many agent websites by hand, and still miss new ones. SpiderHunts gathers listings from permitted sources such as agent feeds, partner APIs and public pages where terms allow, removes duplicates, filters to your criteria and alerts you quickly when a match appears.

Refresh, scroll, repeat

Your team is looking for a certain kind of property: small commercial units in a few postcodes, or houses suitable for conversion under a price ceiling. They check the big portals with saved searches, a dozen local agent websites that list some stock only on their own site, and auction sites. The same property appears three times at slightly different prices.

The good ones go fast. By the time someone has worked through their list, a promising listing has been under offer for a day.

Why saved searches are not enough

Portal alerts only cover that portal. Smaller agents often post first, or only, on their own websites. Auction houses publish catalogues in their own formats. Each source describes properties differently, so filtering on things like tenure, condition or planning status is patchy.

Portal terms are also strict. The large UK property portals generally prohibit scraping, so a naive approach of collecting everything from everywhere is neither wise nor reliable.

SourceSensible route
Large property portalsTheir alerts or an official data partnership, not scraping
Agent websitesFeeds from their software, or public pages where terms allow
Auction housesPublished catalogues, often downloadable
Land Registry and planning dataOfficial open data and APIs

What manual tracking costs

Missed opportunities, especially on stock that appears only on small agent sites. Staff hours on repetitive checking. Duplicate listings wasting viewing time. And no history, so you cannot see how long properties sit or how often prices drop in an area.

Inconsistent notes are another cost. When three people track listings in their own spreadsheets, nobody knows whether a property was already viewed, rejected or offered on, and an agent gets two calls about the same unit from the same firm.

Speed is the heart of it. In a competitive market the buyer who hears first gets the viewing first, and a process that depends on someone remembering to refresh a dozen websites will always be a step behind.

How we build a listings aggregator

  1. We list your sources and check each one's terms and technical options. Many agents use common property software that can publish feeds, and some will share a feed on request.
  2. For permitted public pages, we build polite collectors that check new listings on a schedule.
  3. We add open data where useful: price paid history from HM Land Registry, EPC ratings and local planning applications.
  4. Listings are normalised to one structure: address, price, type, size, tenure, agent, link, first seen date.
  5. Duplicates are matched by address, postcode and features, so one property appears once with every source and price listed.
  6. Your criteria filter the results, and an AI step can read descriptions for things that are not in structured fields, such as mentions of needing modernisation.
  7. Matches trigger alerts by email, WhatsApp or Slack, and everything goes into a searchable database with history.

We will not build collectors for portals whose terms forbid it. Where a portal matters to you, their own alerts or a commercial data agreement is the right route, and we can connect those into the same system.

One list of what fits

Each morning, or as they appear, you see new listings that match, once each, with every source and price. The team spends time on viewings and offers rather than refreshing websites. Over time the history shows how quickly stock moves and where prices are softening.

Each listing can also carry a status your team sets, such as viewed, rejected or offer made, so everyone works from the same record and nobody chases a property someone else has already ruled out.

The history also supports better offers. Knowing how long similar properties sat before selling, and how often asking prices were cut in that postcode, gives your team a stronger basis for negotiating than the agent's description alone.

Does this sound like your week?

  • You check many agent websites as well as the big portals
  • The same property turns up several times
  • Good listings are gone before you see them
  • Your criteria cannot be expressed in portal filters

FAQ

Frequently asked questions

The questions readers ask us after this guide.

Still have a question?

Ask us directly — a senior engineer will get back to you.

Ask about your project

Can you scrape Rightmove or Zoopla?

Their terms generally prohibit it, so we do not. We use their alerts or an official data route and focus automated collection on sources that permit it.

Do agents mind their sites being read?

Some welcome the exposure and will share a feed; others do not. We check terms, collect politely and respect robots.txt. This is general guidance, not legal advice.

Can it include sold prices and planning data?

Yes. Land Registry price paid data and many planning sources are published as open data.

What affects the cost?

The number of sources, whether they offer feeds, how complex your criteria are and how many alert channels you need.

Keep reading

More on Problems We Solve

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Watching too many property sites?

Tell us which sites, what you need from them and where it should end up. We will check for an official feed or partner route first, and tell you plainly if automated collection is not the right answer.

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  2. A senior engineer reviews itAnd comes back with questions, a realistic range and an honest view on fit.
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