Illustrative approach

AI property matching for a multi-branch estate agency: how we would approach it

The UK property market is competitive. Buyers and renters expect quick responses and relevant matches.

Illustrative example of our approach, not a client result. It contains no client data and no performance figures.

Property workflow: Buyer criteria captured, then Shortlist of listings, then Viewing booked, then Agent confirms1Buyer criteriacaptured2Shortlist oflistings3Viewing booked4Agent confirms
Property workflow, agent confirms
  1. 1Business problemDescribed
  2. 2Expert guidanceOur approach
  3. 3SolutionProposed
  4. 4EvidenceNone claimed
  5. 5Next stepsYour baseline

1The business problem

Are you a branch manager or director at an estate agency?

A typical multi-branch agency loses interested buyers when enquiries wait for manual triage and agents are stretched by admin.

Slow Lead Triage

New enquiries can wait too long before anyone responds.

Manual Property Matching

Agents spend significant time matching buyer criteria to live listings by hand.

Limited Project Visibility

Developers often lack timely visibility of build progress, supplier costs and delays.

2What we would advise

We would design AI agents across the transaction lifecycle, from first enquiry to completion, with agents in control of every client commitment.

  1. Property Workflow Audit. Map the buyer and renter journey and agree what to measure.
  2. Agent Deployment. Pilot the matching and viewing agents with your team.

3The proposed solution

Proposed workflow: Buyer criteria captured, then Shortlist of listings, then Viewing booked, then Agent confirms1Buyer criteriacaptured2Shortlist oflistings3Viewing booked4Agent confirms
The final step, agent confirms, stays with a person.
Capabilities we would design and evaluate. Nothing here is a tool already chosen.
CapabilityWhat it doesStatus
AI Property MatcherMatches buyers and renters to suitable listings quickly, using the criteria they give.To evaluate
AI Viewing CoordinatorBooks viewings, sends reminders and manages cancellations.To evaluate
Final decisionAgent confirmsHuman decision

4Starting point and aim

Typical starting point and what we would work towards. No figures, because this is not a client result.
AreaTypical starting pointWhat we would work towards
Lead responseManual triagePrompt first reply and matching
Property matchingManual, agent by agentAutomated shortlist for agent review
Pipeline visibilityPeriodic spreadsheetLive dashboard

5Evidence and how we would measure it

This is an illustrative approach, so there are no results to report. In a real engagement we agree the measures first and report against your own baseline.

  • MeasureLead-to-viewing time and agent admin hours against your own baseline
  • ReviewResults reviewed with you at 30, 60 and 90 days

Expert insight

The aim is to move agents from admin towards relationship management.

Questions we are often asked

Can the AI handle commercial and residential listings?

It can be set up for both, with separate matching rules.

Does it integrate with our existing CRM?

We integrate through your CRM where it offers an API, and confirm this during discovery.

Most relevant for: Estate agencies, property developers and property management firms.

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