- LLPIN: ACD-2052
- GSTIN: 05AFCFS7924L1ZM
Bharat Group of Real Estate, operating under Neev Realators, came to us with a campaign that looked active on paper but was bleeding money in reality. They were running Meta Ads for Gokul Villas, a residential project in Greater Noida West priced from ₹60 Lakh onwards. The campaign was generating 120 leads per month at ₹350 CPL.
Anyone looking at just the lead count would say the campaign was working. The actual numbers told a different story. Site visits from these leads were practically zero. Sales conversions were sitting at zero. Three months of consistent ad spend had produced no revenue.
The root cause was visible once we looked deeper. The targeting was set to “interested in real estate” with a 100 km radius around Greater Noida West. This is the default setup most agencies use, and it kills lead quality. The audience was full of people who scroll real estate ads casually, click on anything that looks pretty, but have no real intent or budget to buy a ₹60 Lakh property.
The funnel was another problem. Every ad was pointing to a “Schedule Site Visit” CTA aimed at cold audiences. In real estate, asking someone to visit a property within 30 seconds of seeing your ad is a one-way ticket to junk leads. Cold traffic needs to be educated, then warmed up, then converted. The earlier campaign skipped both middle steps.
The landing page was the same generic project website used for SEO traffic. No paid traffic optimization, no qualifying lead form, no clear pricing transparency, no trust signals above the fold. Mobile speed was over 4 seconds which on its own kills 40 percent of conversions before the page even loads.
First decision was to throw out the existing audience setup completely. The 40km radius targeting was reaching tier-3 cities, students, low-income segments, and casual browsers who would never realistically buy a ₹60 Lakh property in Greater Noida West.
We rebuilt audiences around three specific buyer profiles based on the project price point. First profile was upgraders moving from rented 2BHK to owned 3BHK in the ₹60 to ₹80 Lakh bracket. Second was IT professionals from Delhi NCR corporate hubs with stable income and home loan eligibility. Third was small business owners and self-employed buyers from Noida and Ghaziabad looking for primary residence with appreciation potential.
For each profile, we layered behavioral targeting on top. Engagement with home loan content, real estate marketplaces, property finance pages, and home decor brands were all signals we used. Lookalike audiences were built using actual past buyers from similar projects (where data was available) and based on website visitors who had spent more than 90 seconds reading content.
Geo-targeting was tightened to specific corridors. Noida sectors, Ghaziabad residential clusters, parts of Delhi East and South within commute distance, and select corporate hubs in Gurgaon for working professionals open to relocation. The radius dropped from 100km to focused 25-30km around target zones.
The single biggest reason the earlier campaign was failing was the funnel structure. Or the lack of it. Cold audiences were being shown “Schedule Site Visit” ads which is asking for marriage on the first date. We rebuilt the campaign with three distinct stages, each with its own creative approach and conversion goal.
Top of Funnel ran video ads built for awareness. Greater Noida West as an emerging residential corridor, Gokul Villas project highlights, location advantages around metro and expressway connectivity, lifestyle imagery showing families enjoying the project amenities. The KPI here was video completion rate and reach, not conversions. Budget allocated was 35 percent of monthly spend.
Middle of Funnel served retargeting ads to people who watched 50 percent or more of the awareness videos, visited the website, or engaged with previous content. These ads showed amenity walkthroughs, floor plans, EMI calculator screenshots, RERA approval details, and possession timeline information. The KPI was engagement and form starts. Budget was 35 percent.
Bottom of Funnel pushed conversion ads to warm audiences who had already engaged through MOF content. These ads featured urgency-led messaging like “Limited 3BHK units available,” strong CTAs to “Book Site Visit,” pricing details, and direct WhatsApp click options. KPI was qualified form fills and site visit bookings. Budget was 30 percent.
This stage-wise budget allocation and audience flow ensured that by the time someone saw a conversion ad, they had already been exposed to brand and project information at least 3-4 times. CPL dropped because the algorithm was optimizing on warm audiences instead of cold cold traffic.
Generic project website was killing conversions. We built a dedicated landing page designed only for paid traffic from this campaign. Every element on the page had a single purpose: convert qualified buyers into site visit bookings.
The landing page started with a strong hero section showing the project from drone view, key USPs (clubhouse, parks, security, location benefits), and pricing prominently displayed as “3BHK starting at ₹60 Lakh.” This pricing display alone acted as a self-qualifying filter. Buyers below this budget bounced. Buyers in this bracket continued reading.
Trust signals were placed above the fold. RERA registration number, possession date guarantee, builder credentials with past projects, and bank loan approvals from major banks. These elements collectively reduced the perceived risk of considering the project.
The middle section had floor plans for both 3BHK and 4BHK options, amenity walkthroughs with high quality renders, location advantages showing distance to metro stations and expressways, and EMI calculator with realistic monthly outgo for a typical buyer.
Lead capture form was the most important element. We added budget range as a dropdown with options below ₹60L, ₹60-80L, ₹80L-1Cr, and above ₹1Cr. We added timeline for purchase: within 3 months, 3-6 months, 6+ months. We added purpose: end-use vs investment. These three filters alone removed 40 percent of casual fillers from the form completion stage. Yes, fewer people completed the form. But the ones who did were 5x more likely to actually buy.
Page load speed was optimized to under 1.8 seconds on mobile. Sticky “Book Site Visit” CTA on mobile kept the conversion path one tap away throughout scrolling.
Real estate creatives in India fall into two failed categories. First is the “limited offer” panic creatives that scream “Last 3 units left!” which buyers see through immediately. Second is the bland corporate ad with stock images and zero personality. We avoided both.
Our creative strategy was built on transparency and lifestyle aspiration. Over 30 creative variations were tested across the funnel. For TOF, we used aspirational lifestyle videos showing families living at Gokul Villas, kids playing in parks, evening walks around the project, weekend gatherings in the clubhouse. These created emotional pull without being sales-y.
For MOF, we used informational creatives. Video walkthroughs of model apartments showing actual room sizes, finishes, kitchen layouts, balcony views. Carousel ads breaking down 3BHK floor plans by room. Static ads with EMI breakdown showing realistic monthly costs. RERA number, builder credentials, and possession timeline were always visible.
For BOF, we used direct conversion creatives. “Live in Greater Noida West with 3BHK at ₹60 Lakh.” “Schedule a site visit this weekend.” “Limited inventory in current pricing slab” used carefully and only when actually true. Strong CTAs with urgency that was real, not manufactured.
Creatives were refreshed every 7-10 days. Best performers were scaled, underperformers were paused without sentimental attachment. Algorithm was given clean signals on what was working so it could optimize aggressively.
Standard pixel-only setup loses 30-40 percent of conversion data after iOS 14 changes. For a real estate campaign where every conversion data point matters, this loss directly translates to slower algorithm learning and higher CPL. We implemented Conversion API alongside the pixel from day one.
Server-side events were configured for the full conversion journey. Form fill tracked initial leads. Qualified lead (passed budget filter) tracked sales-ready prospects. Site visit booking tracked actual property visits. Site visit completed tracked physical attendance. This four-stage event tracking gave Meta a complete picture of conversion quality, not just form completion.
For the first 30 days, we ran manual bidding with cost cap to build clean conversion data. Algorithm needs at least 50 conversions per ad set per week to optimize properly. By week three, we had enough data to switch to automated bidding focused on highest value events (site visits, not just form fills).
By week 8, the algorithm had identified clear patterns in qualified buyer behavior. CPL started dropping consistently each week. Lead quality stayed high because the system was now optimizing on actual buyers, not form-fillers. By month 3, CPL had stabilized at ₹40 with 1200+ monthly leads coming in steady.
120 Leads at ₹350 CPL
Lead count looked acceptable on paper but the cost was eating into margins.
0% Site Visit Rate
Leads were filling forms but not showing up at the property. Sales pipeline empty.
0% Sales Conversion
Three months of ad spend with zero closures. Pure budget burn.
100km Radius Targeting
Audience reach included tier-3 cities, students, casual browsers with no real buying intent.
Cold Audience to Site Visit CTA
No funnel logic. Cold traffic was being asked to schedule site visits without any awareness or trust building.
Generic Landing Page
Same SEO website used for paid traffic. No qualifying form, no pricing transparency, slow mobile speed.
1200+ Leads at ₹40 CPL
10X scale in monthly lead volume with 89 percent reduction in cost per lead.
23% Site Visit Rate
Genuine buyers driving to the project for actual property tours. Real intent confirmed.
2.8% Sales Conversion
From zero closures to industry-leading conversion rate within 3 months.
Buyer-Specific Audiences
Custom audiences built around actual homebuyer profiles. Lookalikes scaling without quality drop.
Three-Stage Funnel Working Smoothly
TOF for awareness, MOF for consideration, BOF for conversion. Each stage hitting its KPIs.
Self-Qualifying Lead Form
Budget filter at form stage means only sales-ready buyers reach the sales team.
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