Property Finder Disrupts Real Estate Marketing with AI-Generated SuperAgent Avatars, Boosting Business for Agents and Driving 1000% Daily Lead Surge
Property Finder, the leading property portal in the MENA region, is rewriting the rules of real estate marketing with the launch of the industry’s first AI-powered campaign proven to deliver client value, spotlighting top-performing SuperAgents through the creation of dynamic digital avatars.
In a bold, tech-first move, the company has harnessed advanced AI tools to create personalised content at scale, delivering a 1000%+ surge in daily seller leads for participating SuperAgents and setting a new benchmark in partner value.
In a competitive real estate market, Property Finder’s SuperAgent feature helps home-seekers connect with top performing agents, while incentivising positive agent behaviours. To spotlight these standout professionals, Property Finder placed agent dedication to their clients at the heart of its latest campaign, by creating AI-generated agent avatars.
These AI avatars were developed entirely in-house, bringing agents’ real-world expertise to life through dynamic, personalised content. From a two-minute photoshoot, Property Finder’s creative team built dozens of tailored assets including social-ready videos, stills, and branded visuals.
Every asset reflects the individual agent’s persona and professionalism set against their community of choice and expertise, underpinned by a rigorous avatar verification process. Not only have the agents been recreated, the scenes themselves accurately reflect the communities down to the square meter.
The results speak for themselves. Aiden Doyle, a SuperAgent at Strada Real Estate, reported a staggering 1,070% increase in daily seller leads since launching his avatar content. “It gave me a lot of credibility in the market and a discussion point with clients helping solidify their trust and assurance to work with me,” he explains. “People started to notice me more flagging that they saw me on this campaign advert.”
By integrating AI motion, voice synthesis, and storytelling into avatar content, Property Finder completed each asset in under five days, optimising a process that would typically take six weeks. The result is nearly $1 million saved in production value and a repeatable model for agent empowerment.
“This isn’t just a marketing campaign, it’s a shift in how we drive results for our partners,” said Sevgi Gür, Chief Marketing Officer at Property Finder. “We didn’t want to limit our use of AI to simply driving cost savings and production efficiencies, instead we set out to leverage the technology available today to put dynamic, high-quality content in agents’ hands faster than ever before.
AI has moved from experiment to impact, and I’m eager to push the boundaries of story-telling further, enhance talent visibility, create narratives that resonate and deliver real business outcomes.”
In parallel, Property Finder continues to explore the creative frontiers of AI through initiatives like Tiny Tenant, the region’s first AI-generated property podcast voiced by digital characters. Originally designed for consumer engagement, the format is now attracting industry-wide interest from agency owners seeking innovative brand exposure.
“Property Finder as always is ahead of the curve, bridging the gap between technology and creativity. My appearance on the Tiny Tenant podcast goes beyond innovation – it’s a stepping stone to a future where we redefine how we connect with our audiences. More customers want bold, forward-thinking experiences and I am excited to be on the journey with Property Finder, to deliver these“, shared Kika Pavese, Managing Director at MD Real Estate.
This latest campaign cements Property Finder’s position as the region’s most innovative real estate platform, where cutting-edge AI is not just a talking point, but a tool for tangible growth, agent success, and creative disruption.
Campaign visuals and assets can be found here, while the initial episodes of the Tiny Tenant podcast can be viewed here, here and here.
