Custom SSP Development for Real Estate Marketplace Monetization

About the Client

The client is a US-based real estate marketplace with over 10 million visits per month from renters, buyers, and property investors. Alongside property discovery, the platform actively runs advertising across the user journey to monetize high-intent traffic.

They offer a mix of placements, including banner ads, sponsored search results listings, featured property cards, and native modules. The client’s team uses a third-party SSP to run standard display campaigns. For complex placements, they rely on manual processes, including direct negotiations and tag-based delivery.

Client Challenges

The client runs a high-traffic real estate marketplace, but the current workflows cannot fully capture the value of ad inventory and audiences:

• High-value campaigns are mostly manual, which slows updates and optimizations.
• Ads across different inventory types lack centralized control.
• Placements don’t use location or regional context, despite strong geographic intent.
• Revenue, eCPM, and fill rates are fragmented across inventory types.
• The ad stack cannot optimize inventory across placements and formats, limiting revenue potential.

Technologies Used

Goals

The client wanted to maximize the revenue potential of their ad inventory by improving targeting, control, and efficiency:

• Streamline ad operations to reduce manual work and speed up updates.
• Manage all placement types consistently through a unified system.
• Deliver ads using contextual geo and listing-level signals to reach relevant users.
• Track and report core revenue metrics in real-time.
• Optimize inventory across all formats to increase fill rates and eCPMs.

Work Description

As the client’s goals required more than standard ad serving, the project centered around developing a custom SSP for real estate. The platform combined RTB auction capabilities with advanced inventory and placement logic, replacing fragmented ad server workflows and centralizing control over monetization.

Stage 1. Discovery and planning

• Duration: 3 weeks.
• Team: Business Analyst, Project Manager.

We collaborated with the client to document high-level requirements for their custom SSP for real estate, focusing on leveraging contextual geo-targeting and inventory optimization. The team analyzed existing ad operations, inventory types, and data sources to define key performance metrics. We also evaluated the limitations of the existing SSP and planned the migration of campaigns that required more advanced targeting and inventory control.

Mockups and system diagrams were created to visualize the SSP workflow, auction logic, and programmatic integrations. A dedicated PM formalized the roadmap, prioritized features, and planned resources to prepare for the development phase.

Stage 2. Iterative development

• Duration: 4,5 months.
• Team: back-end and front-end developers, QA engineers.

Geomotiv’s team of developers delivered the envisioned software in sprints. Based on specifications approved by the client, we delivered the following modules for the SSP:

• Inventory management layer

The team organized all ad placements by type, position, format, device, and listing-level metadata, creating a unified catalog. We implemented rules for exposure, frequency, and allocation across inventory types to protect the user experience.

The system structured inventory to support geo-targeted delivery, so relevant ads could reach users in specific regions. Our developers tagged and segmented inventory by location and property attributes.

• Yield and deal engine

The developers implemented dynamic auction logic, floor management, and inventory scoring to allocate impressions efficiently. The platform ranked placements by value, prioritizing premium inventory for campaigns with the highest competition and yield potential. It used non-PII location and user behavior signals to match campaigns with the most relevant audience.

• Reporting module

Geomotiv’s team created real-time dashboards that tracked eCPM, impression volume, and traffic quality across all placements. The dashboards displayed inventory performance, auction results, and geo-targeting efficiency. Our client accessed metrics instantly, monitored trends, and adjusted strategies based on data-driven insights.

• Programmatic integration

Our developers connected the SSP to programmatic buyers using RTB gateways, so the system could process bids from open and private marketplaces.They then added a Prebid-based demand orchestration layer to manage multiple programmatic buyers simultaneously. It drove higher competition for premium inventory and enforced placement rules for private deals.

Stage 3. Release and support

• Duration: ongoing after deployment.
• Team: Project Manager, DevOps, QA.

After the release, the custom SSP went live and began systematically managing all ad inventory according to automated rules and geo-targeting logic. DevOps specialists monitored performance under peak load and multi-format inventory scenarios to verify system stability.

The team connected additional programmatic partners to expand access to high-quality demand. Continuous QA and incremental improvements refined contextual geo targeting and automated inventory allocation, even as load increased.

Future development stages will introduce advanced auction dashboards that consolidate inventory, bids, geo-data, and non-PII user behavior into a single interface. These dashboards will help track auctions, analyze outcomes, and optimize placements across the entire real estate marketplace.

Results

The custom SSP for real estate delivered measurable value for the client’s business. It centralized inventory, automated ad allocation across placements, and applied contextual geo-targeted delivery. Ads reached the right users in relevant regions, campaign management became faster, and yield per impression increased, driving revenue growth.

The client accessed real-time dashboards showing revenue, fill, and targeting performance, which helped refine strategies and make informed decisions.

Key gains for the client:

• 30% increase in average eCPMs for location-based placements.
• 60% faster campaign setup across all inventory types.
• 25% growth in active programmatic buyers.