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Mountain View Royal Park Case Study

Project Overview

Mountain View Royal Park is a premium villa community offering 3 and 4 BHK neo-classical villas near the Narasapura Industrial Hub, off NH75.

Growthians Marketing managed a performance-led Meta Ads strategy designed to reach serious homebuyers and real estate investors, generate qualified enquiries and build project awareness.

The campaign combined lead generation, audience segmentation and creative testing to improve acquisition efficiency in a competitive real estate market.

Objective

The campaign focused on generating qualified property enquiries while maintaining control over acquisition costs.

The key objectives were to:

  • Reach relevant homebuyer and investor audiences.
  • Generate qualified leads through Meta Instant Forms.
  • Build awareness for the villa project.
  • Improve campaign efficiency through structured audience and creative testing.
  • Maintain a competitive cost per lead while identifying opportunities to scale.

Challenges Faced

The project presented several challenges that required a structured advertising approach.

Limited Creative Assets

Real construction footage was unavailable, leaving 3D architectural renders as the primary visual material for campaign creatives.

High Lead Acquisition Costs

Existing campaigns had elevated lead costs and lacked a structured framework for audience segmentation and creative testing.

Two Distinct Buyer Personas

The campaign needed to appeal to both prospective homeowners and investors, each with different motivations and buying considerations.

Differentiating the Investment Proposition

Pre-launch pricing needed to create interest and urgency without making the ads feel like generic real estate promotions.

Strategy Implemented

Meta Ads Campaign Strategy

We structured the campaigns around lead generation, audience segmentation and continuous performance optimisation.

Key actions included:

  • Launching Meta Instant Form campaigns targeting investor-focused audiences across Bengaluru and surrounding areas.
  • Shifting messaging towards an investment-led proposition highlighting NH75 connectivity and the Narasapura growth corridor.
  • Running a separate awareness campaign to build project visibility while keeping its budget distinct from lead generation.
  • Structuring more than 18 ad sets across manual, interest-based and retargeting audiences.
  • Monitoring performance and shifting budget towards better-performing ad sets.

Creative Strategy & Testing

With no real construction footage available, we used the project’s 3D architectural renders to develop cinematic AI-generated video creatives.

The creative approach included:

  • Producing cinematic video Reels designed to look more photorealistic than conventional CGI presentations.
  • Using curiosity-driven opening hooks to capture attention quickly.
  • Developing static creatives highlighting pre-launch pricing and villa exteriors.
  • Testing Reel and static formats across ad sets to compare lead volume and acquisition costs.

These tests helped guide creative decisions using observed campaign performance rather than assumptions.

Results

The Meta Ads campaigns generated 238 qualified leads, reaching 37,557 people across the reported lead-generation campaigns.

Campaign Performance

238 qualified leads generated

₹520.49 average cost per lead

37,557 people reached

3.00 average frequency

₹1,23,875.49 total campaign spend

Ad-Set Performance

Ad Set — 1 May 2026

  • Leads generated: 104
  • Reach: 25,804
  • Average CPL: ₹551.48
  • Spend: ₹57,353.92

Ad Set — 22 April 2026

  • Leads generated: 134
  • Reach: 18,814
  • Average CPL: ₹496.43
  • Spend: ₹66,521.57

Together, these two ad sets accounted for all 238 reported leads and ₹1,23,875.49 in campaign spend.

Best-Performing Ads

Reel — 1 May

Generated 98 leads at an average CPL of ₹542.65, making it the strongest of the highlighted creatives for lead volume.

Static — 18 May

Generated 65 leads at a CPL of ₹407.32, the lowest individual CPL among the listed creatives.

Reel — 30 April

Generated 52 leads at an average CPL of ₹546.63.

The results showed that different creative formats contributed differently to campaign performance: Reels delivered strong lead volume, while the highlighted static creative achieved a lower cost per lead.

Overall Impact

The campaign established a more structured approach to real estate lead generation by bringing together investor-focused positioning, audience segmentation, creative testing and performance-based budget allocation.

The reported outcomes included:

  • 238 qualified leads generated through Meta Instant Forms.
  • An average cost per lead of ₹520.49 across the main lead-generation campaigns.
  • 37,557 people reached across the reported campaigns.
  • A lowest individual CPL of ₹407.32 among the highlighted creatives.

AI-generated cinematic Reels helped address the lack of real construction footage, while static creative testing provided an alternative route to efficient lead acquisition.

Together, these elements created a clearer framework for evaluating audiences, comparing creative formats and reallocating spend based on performance.

Key Takeaways

Audience Strategy Shapes Lead Quality

Different buyer personas respond to different propositions. Audience strategies should reflect buyer motivations and the factors influencing their decisions.

Creative Doesn’t Have to Start with Live Footage

When real project footage isn’t available, architectural renders can provide a foundation for producing campaign creatives, including AI-assisted video content.

Test Formats, Not Assumptions

Reels delivered the highest lead volume among the highlighted creatives, while a static ad recorded the lowest CPL. Performance data—not format preference—should guide creative decisions.

Separate Awareness from Lead Generation

Distinct campaign objectives help clarify budget allocation and make it easier to evaluate awareness activity alongside direct lead acquisition.

Optimisation Is an Ongoing Process

Audience refinement, creative testing and budget reallocation allow campaigns to evolve based on observed performance rather than remain fixed after launch.