35% Year-over-Year lead growth across paid channels for a real estate platform

Scaling lead growth in a competitive real estate market requires more than a budget. By crafting efficient Google Ads and Meta campaigns for a real estate platform, we drove 35% total lead growth year-over-year, with new-build property leads growing by 24%, property sale leads increasing by 42%, and rental leads rising by 41%.

Client

City Expert

Expertise
  • Advertising Strategy
  • Competitive Analysis
  • Budget Management
  • Audience Segmentation
  • Conversion Tracking
  • Performance Monitoring
Year

2023 - 2026

City Expert is Serbia’s first online real estate agency, combining the experience of traditional agents with technology to fully digitize the process of renting, buying, and selling property. With a clear need to grow qualified leads across multiple property segments and cities, City Expert partnered with us to achieve those objectives.

Challenges

  • Positioning in a crowded and fragmented market

    Operating in a market dominated by traditional real estate agencies and classified listing platforms, City Expert faced the challenge of establishing itself as a distinct category: Serbia’s first online real estate agency. Communicating this differentiation through paid advertising required clear and consistent messaging that set City Expert apart from both agency-style competitors and listing-only platforms, without the established strong brand recognition those competitors already held.

  • Attracting property owners to list on the platform

    A core growth objective was acquiring new property owners, both rental owners and sellers, to add their listings directly to City Expert’s platform. Unlike demand-side lead generation, this required reaching a specific audience that was not actively searching for an agency, making targeting and messaging significantly more complex.

  • Implementing conversion tracking across lead categories

    City Expert operates across multiple distinct lead types, including new-build property inquiries, rental listings, and property sale listings for three major cities, each requiring separate tracking. Setting up conversion tracking specific enough to differentiate between these categories was a prerequisite for meaningful campaign optimization. 

    With additional offline conversion tracking and CRM integration we set in place, covering the full funnel from initial lead to final purchase, we were able to use these insights to significantly improve the effectiveness and profitability of our acquisition activities.

    By identifying which traffic sources, campaigns, and targeting strategies generated the highest-quality leads with the strongest purchase intent, we were able to optimize investments toward the activities that delivered the greatest impact on actual business results, not just lead volume.

  • Strategic budget and platform allocation

    With a limited budget and multiple advertising options available, including Google Ads, Meta, various campaign types, and a wide range of audience segments, deciding where to invest required careful analysis. Allocating spend across platforms, campaign types, and audience segments in a way that maximized lead volume without overlapping or cannibalizing performance across categories was an ongoing strategic challenge.

  • Campaign structure and keyword grouping

    Structuring Google Ads campaigns with ad groups that were neither too broad nor too granular was an ongoing challenge. Overly broad groupings diluted ad relevance and quality scores, while overly specific structures became difficult to manage and optimize. Finding the right thematic grouping logic, one that maintained relevance while remaining operationally sustainable, was critical to long-term account performance.

    The previous Meta campaign structure was less efficient due to inconsistent segmentation, with many campaigns primarily optimized for traffic rather than conversions. Some campaigns were too broad, grouping multiple profit centers and locations together, which reduced ad relevance and limited the algorithm’s ability to optimize effectively. This lack of a clear, conversion-focused structure prevented campaigns from being effectively optimized for lead generation.

  • Capturing micro-location search demand

    Real estate search behaviour can be highly localised, with users frequently searching by specific areas or neighbourhoods rather than city-level terms. Ensuring adequate keyword coverage across Belgrade’s micro-locations without creating an unmanageable campaign structure required a systematic and scalable approach to location-based keyword expansion.

  • Seasonal demand spikes in the rental market

    The rental category is subject to strong seasonal demand patterns, with search volume and user intent peaking during specific periods of the year, particularly around the start of the academic year. These peaks also coincide with increased competitor activity during the same windows, driving up advertising costs and making it significantly harder to maintain efficient performance precisely when visibility matters most.

Solution

  • Differentiating City Expert through ad copy and creative

    We identified and communicated the key distinctions that set City Expert apart from traditional agencies and classified platforms directly within ad copy and visual creatives. For users searching to rent, we highlighted the absence of agency commission as a primary value proposition. For those interested in a property, we emphasized detailed property presentation, including professional photos, videos, 360-degree walkthroughs, and floor plans, giving prospective renters and buyers a level of detail unavailable on competing platforms.

  • Dedicated campaigns for property owner acquisition

    We configured conversion tracking specifically for the lead form targeting property owners, enabling it to serve as a dedicated conversion goal within campaigns. Separate search campaigns were built around keywords that differentiated property owners from buyers and renters. Given the lower search demand in this segment, we expanded reach through display remarketing and Performance Max campaigns, using broader channel coverage to allow the algorithm to identify and reach the right audience beyond direct search intent.

    We implemented Meta campaigns for property owner acquisition using Instant Forms as the primary conversion mechanism, enabling efficient lead capture directly within the platform.

    Lead growth by city (y-o-y)

  • Conversion tracking by city and lead category

    Each city and category, covering new-build properties, rentals, and property sales, has a dedicated form that triggers when a user schedules a property viewing, the strongest intent signal before a final decision. By creating separate conversion actions for each of these forms, we were able to align campaign structures directly with specific business goals and optimize each campaign toward the lead type it was designed to generate.

    Lead growth by platform (y-o-y)

  • Data-driven budget management

    We built a reporting dashboard that consolidated data from Google Ads, Meta, and Google Analytics into a single view, giving us a clear picture of performance across channels, categories, and markets. This allowed us to make informed decisions about when and where to allocate budget based on actual demand and performance. Some categories consistently outperformed others, and certain markets required larger budget allocations based on their size and competitive dynamics. The dashboard also helped us identify which categories responded better to Google Ads and which performed more efficiently on Meta, allowing us to distribute spend accordingly.

  • Thematic campaign structure by search intent

    Initial keyword research revealed a wide spectrum of search behaviour across all categories, from high-intent searches to broader, exploratory queries. Users searched by price, by location, by a combination of both, and by property characteristics such as property size. To address this, we built two distinct campaign layers. The first targeted generic, city-level keywords combined with relevant subcategories such as apartment size or price range. The second targeted area-specific searches within each city, using website filters to direct users to listings filtered by neighbourhood or city district, ensuring landing page relevance for each search type.

  • Meta campaign restructure

    Meta campaigns were restructured based on profit centers and key cities to improve budget control and ad relevance. Campaigns were segmented into core business areas: new developments, sales, rentals, and property owners. Within the new developments segment, specific project types such as featured and exclusive listings were separated and consolidated into dedicated campaigns for key cities, allowing for more precise optimization, tailored creatives, and clearer audience communication.

  • Dynamic search campaigns for micro-location coverage

    To capture the significant volume of highly specific, micro-location searches, including individual street names and small neighbourhood queries, we created dedicated dynamic Search ad campaigns. Each DSA campaign was assigned its own page feed specific to a given city and category, allowing us to match ad content precisely to the listings available for that location. This approach enabled us to cover long-tail search demand that would be impractical to address through manually built keyword lists, while maintaining the flexibility to reallocate budgets toward the best-performing campaigns on a week-by-week basis.

  • Seasonal budget planning for the rental category

    We developed a seasonal budget framework for the rental category that anticipated demand peaks in advance rather than reacting to them after they occurred. By analysing historical performance data and search demand trends, we identified the specific periods when rental search activity surged and pre-allocated increased budgets for those windows. This allowed strong visibility during peak periods without being outbid by competitors who activated at the same time, while keeping spending efficient during lower-demand periods.

Results

  • 34.9% Total lead growth across all key events (Y-o-Y)
  • 24% Increase in new-build property leads (Y-o-Y)
  • 41.9% Growth in property sale leads (Y-o-Y)
  • 41% Increase in rental leads (Y-o-Y)
  • 59.6% Growth in property listing leads (Y-o-Y)

Project Journey

00 Initial audit

We began with a comprehensive audit of the existing Google Ads and Meta accounts, evaluating campaign structure, keyword coverage, audience targeting, budget distribution, and conversion tracking setup. The audit identified key structural gaps, including insufficient differentiation between lead categories, missing conversion signals for specific audience segments, and keyword coverage that was either too broad or too tightly structured to capture the full range of relevant search intent. These findings formed the basis of our roadmap for both platforms.

01 Conversion tracking setup

In parallel with the initial campaign work, we configured a conversion tracking architecture. Each city and lead category received its own dedicated conversion action, triggered when a user submitted a form to schedule a property viewing. This gave us clean, category-level performance data from the outset, allowing campaigns to be optimized toward specific business goals rather than generic lead volume. Separate tracking was also implemented for the property owner acquisition flow, enabling it to serve as a distinct optimization target within dedicated campaigns.

02 Campaign restructuring

With the tracking foundation in place, we improved the Google Ads campaign structure. Campaigns were organized across two structural layers. The first covered generic, city-level search intent, targeting keywords across each market, combined with relevant subcategories such as apartment size and price range. The second layer addressed location intent, capturing searches for specific city areas with users landing on pre-filtered listing pages matching their search context. This dual-layer structure ensured comprehensive search coverage without sacrificing keyword relevance or Quality Scores.

03 Dynamic search ads and page feed implementation

Following the core search restructure, we expanded coverage through Dynamic Search Ad campaigns. Each DSA campaign was assigned a dedicated page feed scoped to a specific city and lead category, enabling the system to match ads to highly specific search queries, including street-level and micro-neighbourhood searches, that would be impractical to address manually. This layer complemented the keyword-based campaigns and significantly extended the account’s reach into long-tail search demand.

04 Property owner acquisition campaigns

In parallel, we built dedicated campaigns targeting property owners looking to list their properties for rent or sale. Keyword research focused on identifying search terms that separated owners from buyers and renters. Given the lower search volume in this segment, we supplemented the search campaigns with display remarketing and Performance Max campaigns, using broader coverage and allowing the algorithm to identify and reach the right audience beyond direct search intent.

Meta campaigns for property owners were structured to target property owners through both general messaging and more tailored communication focused on selling and renting, allowing us to address different owner intents more effectively.

05 Meta campaign launch

Meta campaigns were reorganized around profit centers and key cities. The campaigns were specifically optimized for lead generation, enabling a stronger focus on capturing inquiries and improving conversion performance. Dedicated lead generation campaigns were launched for each core segment, new developments, sales, rentals, and property owners, allowing for more focused optimization, tailored messaging, and improved lead quality across each business area.

06 Meta audience strategy

As part of the restructuring, we introduced a more systematic audience testing approach. This included leveraging lookalike audiences based on website visitors for new developments and sales segments, allowing us to scale beyond existing demand. In later phases, we expanded testing within the sales segment by introducing lookalike audiences built from customer lists, with a focus on improving lead quality and conversion rates.

07 Meta dynamic ads & feed optimization

Although dynamic ads and product feeds were already active, their initial setup was too broad, with product sets grouped at a high level (e.g., all new developments combined). We restructured feed segmentation by dividing product sets based on sector and city, enabling more relevant ad delivery and better alignment with user intent. This resulted in improved performance through more granular control and stronger matching between listings and audience signals.

08 Reporting dashboard development

We built a consolidated reporting dashboard that pulled performance data from Google Ads, Meta, and Google Analytics into a single view. The dashboard provided a breakdown by platform, campaign type, lead category, and market, giving us the visibility needed to make informed budget allocation decisions on an ongoing basis. This was particularly important for identifying which categories and markets responded better to Google Ads versus Meta, and for tracking performance shifts across the different lead types.

09 Ongoing monitoring and reporting

A structured performance management cadence was established with daily account reviews to monitor key metrics, identify optimization opportunities, and respond to performance shifts across campaigns, categories, and markets.