Solutions · Real Estate & PropTech

LeadClue for Real Estate & PropTech

Real estate and proptech buyers think in markets, not verticals — the same pitch lands differently in two cities twenty miles apart. This playbook raises geography and company size, drops the technology and AI weighting, and keeps outreach grounded in the buyer’s specific market.

Who you're selling to: VP Operations, Director of Technology, Broker-Owner, Head of Portfolio Management.Tone: Hyper-local and relationship-first. A vendor that understands the specific market outperforms one with a bigger name but no local read.

Ideal Customer Profile

This playbook

Roles: VP Operations, Director of Technology, Broker-Owner, Head of Portfolio Management, COO
Company size: 20–2,000 employees
Maturity: Actively managing or transacting a live property portfolio — not a pre-launch fund
Geography: US, UK — metro markets with active transaction volume

Buying signals

New market or metro launch announced
MLS or property-management-system integration need
Funding raised for portfolio expansion
Brokerage or portfolio headcount growing

Disqualifiers

Pre-launch fund with no active portfolio
Operating in a single market with no expansion plans
Portfolio currently under active divestment

The weights

How the nine scoring factors get re-tuned

Default weights come straight from the platform's baseline model and total 100. The PropTech tuning keeps the same total and moves points toward whichever factors actually predict a good proptech lead.

Role / decision authority
Default 20 ptsTuned 18 pts▼ -2
Decisions are often shared between a broker-owner and an operations lead, softening this slightly.
Industry match
Default 15 ptsTuned 14 pts▼ -1
Still a strong signal, just marginally less decisive than market fit in this vertical.
Services-to-needs alignment
Default 15 ptsTuned 13 pts▼ -2
Slightly less predictive once geography and company size already capture most of the fit signal.
Company size fit
Default 10 ptsTuned 12 pts▲ +2
Portfolio size correlates reasonably well with budget and buying authority here.
Geography match
Default 10 ptsTuned 20 pts▲ +10
The dominant signal — real estate is transacted market by market, and the wrong metro is a non-starter.
Technology relevance
Default 10 ptsTuned 6 pts▼ -4
Digital maturity still varies widely across the industry, so the stack signal is less reliable.
Outsourcing probability
Default 10 ptsTuned 9 pts▼ -1
A modest reduction — outsourcing propensity tracks market and portfolio size more than general willingness.
AI / digital transformation fit
Default 5 ptsTuned 3 pts▼ -2
The sector is still catching up on basic digital tooling, let alone AI, so this is dialled back.
Contact info completeness
Default 5 ptsTuned 5 pts— no change
Broker and portfolio contacts are usually already well documented.

Default total: 100 pts · Tuned total: 100 pts

Default versus Real Estate & PropTech tuned weight for each of the nine scoring factors
Factor	Default	Tuned	Change	Why
Role / decision authority	20 pts	18 pts	▼ -2	Decisions are often shared between a broker-owner and an operations lead, softening this slightly.
Industry match	15 pts	14 pts	▼ -1	Still a strong signal, just marginally less decisive than market fit in this vertical.
Services-to-needs alignment	15 pts	13 pts	▼ -2	Slightly less predictive once geography and company size already capture most of the fit signal.
Company size fit	10 pts	12 pts	▲ +2	Portfolio size correlates reasonably well with budget and buying authority here.
Geography match	10 pts	20 pts	▲ +10	The dominant signal — real estate is transacted market by market, and the wrong metro is a non-starter.
Technology relevance	10 pts	6 pts	▼ -4	Digital maturity still varies widely across the industry, so the stack signal is less reliable.
Outsourcing probability	10 pts	9 pts	▼ -1	A modest reduction — outsourcing propensity tracks market and portfolio size more than general willingness.
AI / digital transformation fit	5 pts	3 pts	▼ -2	The sector is still catching up on basic digital tooling, let alone AI, so this is dialled back.
Contact info completeness	5 pts	5 pts	— none	Broker and portfolio contacts are usually already well documented.
Total	100 pts	100 pts

The sequence

The tuned four-day sequence for PropTech

Same four-step structure the platform uses everywhere — reviewed profile, engagement, connection, AI opener — paced and worded for this vertical.

Day 1
Review profile & market footprint
Confirm the specific metro or region before writing anything — local precision matters more than product detail here.
Day 2
Engage with a market-expansion post
React to a new-market or portfolio-growth announcement.
Day 3
Send the connection request
Reference the specific market by name.
Day 4
Send the AI-drafted opener
Leads with a market-specific outcome, not a generic platform pitch.

Sample leads, re-ranked

Illustrative leads showing how the proptech tuning moves a score against the same nine-factor model.

VP Operations at a 300-person brokerage launching in a third metro market
Default 75%Tuned 90%▲ +15 pts
Director of Technology at a 40-person pre-launch fund with no active portfolio
Default 71%Tuned 55%▼ -16 pts
Broker-Owner at a 90-person firm integrating a new property-management system
Default 73%Tuned 87%▲ +14 pts
COO at a 600-person firm operating in a single market with no expansion plans
Default 78%Tuned 66%▼ -12 pts

PLACEHOLDER data: these companies, roles and scores are invented for illustration and are not real leads.

Get started

Bring one export. Leave with a ranked queue.

In a 20-minute session we load a sample of your own list, configure your company profile and ICP, and show you the scored, ranked, owner-assigned queue that comes out the other side.

Book a 20-minute demo Download the product overview

No credit card · No LinkedIn credentials required · Your data stays in your environment