AI-DRIVEN PROPTECH GROWTH

Horizon Properties Achieves 2.9X High-Value Investor Acquisition with AdZeta's Predictive LTV Targeting

Horizon Properties, a leading proptech firm, revolutionized its investor acquisition strategy by leveraging AdZeta's predictive AI. This partnership enabled a strategic focus on high-LTV (Lifetime Value) investors, resulting in a 2.9X increase in high-net-worth investor acquisition and significantly optimized advertising spend across its diverse real estate portfolio.

PROJECT HIGHLIGHTS
01

Client Profile: Horizon Properties

Horizon Properties is an innovative proptech company connecting discerning investors with premium real estate opportunities via its sophisticated digital platform. The firm specializes in exclusive residential and commercial property developments, offering high-yield investments to qualified individuals.

02

The Challenge: Identifying High-Value Investors

Horizon's investor base varied significantly, from occasional participants to high-net-worth individuals engaging in multiple substantial investments. Standard advertising metrics, such as Cost Per Acquisition (CPA) for initial inquiries, failed to distinguish prospects with the highest long-term value, hindering sustainable and scalable growth.

03

Previous Advertising Strategy & Limitations

The company's prior strategy centered on optimizing Google and Meta advertising campaigns for initial property inquiries or website registrations. This approach led to unpredictable investor quality and difficulties in profitably scaling acquisition efforts across their varied property offerings.

04

The AdZeta Solution: Predictive LTV Targeting

AdZeta deployed its advanced Predictive AI engine to accurately forecast investor LTV from early interactions. This enabled Horizon Properties to implement Value-Based Bidding strategies, specifically targeting high-net-worth individuals demonstrating greater potential for investment frequency and portfolio diversification.

05

Strategic Implementation & Execution

AdZeta utilized Horizon's first-party data to train bespoke LTV models. These predictive signals were then seamlessly integrated with Google Ads (Target ROAS) and Meta Ads (Value Optimization) campaigns. Rigorous A/B testing against the previous strategy was conducted, with a concentrated focus on high-value investor segments.

06

Quantifiable Outcomes & Business Impact

The strategic shift yielded a 2.9x increase in high-net-worth investor acquisition. Concurrently, Horizon Properties realized a 43% reduction in customer acquisition costs for its premium investment segments, directly attributable to AdZeta's predictive LTV insights.

Understanding the Problem

The Core Challenge: Inefficient Ad Spend & Uncaptured LTV in Proptech

Traditional proptech advertising methodologies often struggle to efficiently identify and target high-value investors, leading to suboptimal budget allocation and missed revenue opportunities.

Proptech funnel
without
AdZeta
All Property Visitors
Optimization event
Property Inquiry
Mixed Investors
Low Retention
Proptech funnel
with
AdZeta
Targeted Investor Traffic
Quality Investors
Optimization event
Investor LTV
High Investment
01
Inefficient Spend Without LTV Optimization

Proptech companies often invest substantially in investor acquisition without precise mechanisms to identify individuals likely to become significant long-term partners. This frequently results in misallocated ad spend on low-potential inquiries and overlooked opportunities with high-net-worth prospects.

02
The Lifetime Value Gap in Proptech

Conventional Return on Ad Spend (ROAS) metrics are typically confined to initial interactions or lead generation. This limitation makes it challenging to optimize campaigns for investors who will generate substantial lifetime value through repeat investments and portfolio growth.

03
Underutilized Data Assets

Many firms, even those with sophisticated CRM systems, face difficulties in transforming their rich investor behavior data into actionable insights for intelligent bidding strategies across their diverse property portfolios and marketing channels.

ADZETA'S SOLUTION

The Strategic Approach: How AdZeta Delivered for Horizon Properties

  • Advanced Predictive AI Modeling

    AdZeta developed custom machine learning algorithms that analyzed over 110 distinct investor behavior signals from Horizon's data. These signals included property viewing patterns, historical investment data, portfolio size, and engagement with financial content, enabling future LTV prediction with up to 95% accuracy.

  • Precision Value-Based Bidding

    AdZeta's platform intelligently automated bid adjustments on Google and Meta advertising platforms. Bids were weighted based on predicted investor LTV, not merely the likelihood of an initial inquiry, ensuring that marketing spend was prioritized towards attracting potential high-net-worth individuals with greater investment capacity.

  • Unified Data Ecosystem & Signal Activation

    A comprehensive view of the investor journey was created by integrating marketing, investor, and transactional data. Predictive LTV signals were then seamlessly transmitted to advertising platforms via API, facilitating real-time optimization across various property categories and campaigns.

  • Continuous Automated Optimization & Adaptive Learning

    AdZeta's AI-powered system featured continuous learning capabilities. It automatically refined and adapted bidding strategies in response to evolving investor behavior patterns and dynamic market conditions, ensuring sustained optimal performance for Horizon Properties.

Control Group Optimizing towards Business-as-usual event: Property Inquiry CPA Experiment Group Optimizing towards tROAS with predictions powered by AdZeta: Investor LTV & Portfolio Growth A/B Test

81%

Increase in Ad Spend

Achieved while maintaining target profitability

67%

Growth in Average Investment Value

Across all property categories

53%

Uplift in LTV

Per acquired investor

2.9X

ROAS

Return on Advertising Spend

MEASURABLE IMPACT

Attracting High-Value Investors, Minimizing Waste, Maximizing ROI

AdZeta's predictive LTV methodology fundamentally transformed Horizon Properties' investor acquisition framework. By prioritizing LTV, Horizon cultivated a higher-caliber investor base, fostering more predictable revenue streams and sustainable long-term growth.

This data-driven confidence allowed them to scale advertising investments effectively, knowing they were directly contributing to profitability.

With AdZeta's AI platform, we've been able to scale our ad spend effectively—by 2.9X in key campaigns—while significantly increasing the acquisition of high-net-worth investors who make multiple property investments. The predictive LTV insights gave us the confidence to expand into luxury development markets we previously thought were too competitive for our digital-first approach. We're now connecting with qualified investors who appreciate our curated property opportunities and are ready to make significant, repeated investments.
Client
Alexander Morgan Chief Investment Officer, Horizon Properties

Ready to Build Similar Growth for Your Proptech Business?

If you're looking to move beyond basic ad metrics and build a truly profitable, scalable investor acquisition engine, AdZeta's Predictive AI and Value-Based Bidding can help.

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