Building an AI-powered Marketing Intelligence Engine for high-net-worth investors
How JLL Marketing is transforming investor targeting with automated profiling, adaptive scoring, and intelligent activation across 10,000+ HNWI/UHNWI prospects.
"Jeeva helped us penetrate a new $1B market in NA & EMEA in 90 days which may have taken my team 3 years without Jeeva."
— Ricardo Souza, Global Head of JLL Marketing, BD, & Demand Generation
Time to new market
90 days
Market size (NA & EMEA)
$1B
Investor profiles
10,000
AI insights per profile
10+
COMPANY
JLL (Jones Lang LaSalle)
TEAM
Marketing
INDUSTRY
Commercial Real Estate
USE CASE
Investor Intelligence
At a glance
JLL is one of the world's largest commercial real estate services firms, with 115,000+ employees across 80+ countries. Their Marketing team targets some of the most sophisticated buyers in the industry: high-net-worth and ultra-high-net-worth individuals looking to deploy capital into premium assets.
The challenge isn't finding wealthy people. It's finding the right wealthy people — those with genuine CRE appetite, active liquidity, and alignment with JLL's offerings. And then engaging them in ways that convert interest into deal flow.
Traditional approaches relied on manual research, static contact lists, and one-shot outreach that ended after events. JLL needed a system that could continuously identify, score, and activate the highest-potential investors at scale.
The challenge: Manual research limits precision and speed
Targeting HNWI and UHNWI investors requires more than basic contact data. You need to understand wealth sources, investment history, property holdings, liquidity events, network connections, and behavioral signals that indicate readiness to transact.
JLL's existing workflows faced three critical gaps:
Fragmented Research
THE GAP
Manual, ad-hoc searches across inconsistent data sources limited targeting accuracy and consumed analyst time.
THE IMPACT
Analysts spent more time on data cleanup than engagement. High-value investors were missed or reached too late.
WHAT WAS NEEDED
Automated investor identification with profiles that update continuously as new signals emerge.
Static Lead Lists
THE GAP
Outreach relied on fixed contact lists with no feedback loop to identify which investors were most likely to engage.
THE IMPACT
Wasted effort on low-intent prospects. No way to learn from engagement data or prioritize dynamically.
WHAT WAS NEEDED
AI models that continuously score and rescore investors based on real engagement signals.
Dead-End Engagement
THE GAP
Investor engagement typically stopped after events or initial outreach. High-intent prospects went cold.
THE IMPACT
Warm leads weren't converted. Brokers missed opportunities to connect with qualified investors.
WHAT WAS NEEDED
Automated follow-up that detects intent signals and triggers personalized re-engagement.
The Solution: Marketing Intelligence Engine
JLL partnered with Jeeva AI to build a three-pillar Marketing Intelligence Engine designed specifically for HNWI/UHNWI investor targeting.
AI Market Mapping
Automate investor identification and profiling using Jeeva's enrichment and event detection engine. Profiles update continuously as new financial or behavioral signals emerge.
Deliverable
10,000 enriched investor profiles
2
Adaptive Lead Scoring
AI continuously learns from engagement data — email opens, event attendance, broker interactions — to rescore and prioritize investor cohorts. The model improves with every feedback cycle.
Output
New 10K lead cohorts in a closed learning loop
3
Intelligent Activation
AI detects warm signals from events, webinars, and campaigns, triggering personalized follow-ups via email, LinkedIn, or SMS — enabling brokers to connect with qualified investors faster.
Outcome
Engagement converted into measurable deal flow
How deep does the data go?
The Marketing Intelligence Engine fuses integrated data sources with AI-powered enrichment to build a living investor graph. Each profile contains signals across multiple dimensions:
Wealth Intelligence
• Net worth tier
• Liquidity events (IPO, M&A, secondary sales)
• Asset visibility (property & CRE holdings)
• Family office network (principals, entities)
Professional Identity
• Name, title, seniority
• Corporate affiliation (company, industry)
• Career trajectory (history, tenure)
• Functional domain (department, role)
Influence & Network
• Board & advisory roles
• Elite memberships (YPO, Tiger 21, private clubs)
• Philanthropy signals (foundations, causes)
• Relational intelligence (network linkages)
Behavioral Signals
• Event attendance & speaking presence
• Media footprint (mentions, thought leadership)
• Affinity mapping (cause & investment alignment)
• Lifestyle indicators (interests, hobbies)
Why this matters
For JLL Marketing, the Intelligence Engine represents a fundamental shift from reactive to proactive investor engagement.
Before vs After
Before: Manual research
Analysts spend hours on data cleanup
Before: Static lists
No insight into investor intent
Before: One-shot outreach
High-intent investors go cold
After: Automated profiling
Analysts focus on engagement
After: Adaptive scoring
Continuously prioritized by engagement
After: Intelligent activation
Warm prospects converted to deal flow
The outcome: sharper targeting, reduced waste, and higher conversion through adaptive, feedback-driven marketing.
"This isn't contact data. This is investor intelligence—the depth you need to understand how high-net-worth individuals actually think and invest."
— JLL Marketing Team
About JLL
JLL (Jones Lang LaSalle) is a global leader in commercial real estate services, with operations in over 80 countries. The firm provides investment, development, leasing, property management, and advisory services to clients ranging from individual investors to multinational corporations.
With 115,000+ employees worldwide, JLL manages billions in real estate assets and advises on transactions that shape cities and communities around the world.
