Atom Mobility’s Google Ads campaigns brought in plenty of demo requests. The problem was that most of them weren’t worth a sales call. Atom Mobility makes customizable mobile technology for vehicle sharing, rental and taxi businesses, and for them the real challenge was lead quality, not volume. At ePPC, we took on this challenge by developing a bespoke AI-driven lead prediction model that not only improved campaign performance but also became a finalist in the Search Engine Land Awards 2025.
The Lead Quality Problem
When Atom Mobility first partnered with us, they were seeing a strong flow of demo requests from their Google Ads campaigns. But there was a problem:
- only about 10% of those demo requests were actually sales-ready leads.
Meanwhile, 90% were low-quality or spam leads, and the long sales cycle slowed down campaign learning and optimization. That meant Google Ads could not learn quickly enough what worked, holding back performance growth.
Marketing goal
The company has two primary product verticals.
- Vehicle Sharing → Reduce the Offline CPA by 55%
- Ride Hailing → Reduce the Offline CPA by 22%
The Old Customer Journey
In this system, demo requests would go through the sales rep. for the assessment, and good quality leads would be sent to Google Ads. The assessment would take weeks or months. Thus, we would not get enough offline conversions within enough time to optimize our campaigns.
The New Customer Journey and Google Ads Optimizations
To tackle this, our team, including account managers and a data scientist, built a custom AI lead prediction model to assess incoming leads. This model automated the scoring of lead quality and worked as part of an updated customer journey.
Under the new system:
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Leads were assessed based on both the AI model’s prediction and sales team feedback.
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The AI model updated its assessments every 24 hours, providing near-real-time insights.
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Google Ads was optimized not just for conversions, but for AI-predicted conversions as well as sales-qualified conversions.
This meant campaigns could learn faster, with more accurate signals about which audiences and keywords were driving genuinely valuable engagement, not just clicks.
What We Optimized and Why It Mattered
With lead quality scoring feeding into campaign intelligence, we also executed a series of tactical improvements:
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Keyword Optimization: Instead of bidding purely on volume or broad performance metrics, we analyzed which keywords delivered higher-quality leads according to the AI scoring and CRM data.
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Landing Page Enhancements: Copy, design, and user experience were improved with insights from Microsoft Clarity, helping ensure that ad clicks didn’t fall off before users completed demo requests.
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Campaign Restructuring: Budgets were reallocated away from markets that generated clicks but not contracts, focusing investment on more promising segments.
These combined efforts brought measurable gains across the board.
Real Results That Changed the Game
Once the AI model and strategy changes were in place, Atom Mobility’s performance metrics began to improve significantly:
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Lead quality and conversion signals increased by 54%
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CPA dropped significantly (with reductions of 56% in certain cost metrics)
These results helped Atom Mobility not only make smarter decisions about where to invest marketing dollars but also speed up learning cycles that were previously constrained by slow, manual lead assessments.
Industry Recognition: Awards and Accolades
The work didn’t go unnoticed. The campaign was recognized at multiple industry award shows, including:
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Search Engine Land Awards 2025 (Finalist in B2B Search Marketing)
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Golden Parrot B2B Awards 2025 (Winner: Best Lead Generation Campaign)
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Digitegu 2024 (Winner in Data-Driven Marketing, Use of AI, and Innovative Digital Marketing categories)
It is rare to see such a clear combination of AI innovation and tangible business impact in PPC campaigns, but Atom Mobility’s example shows what is possible when performance marketing teams embrace smarter data tools.
Team behind the success
The success of this project was driven by a cross-functional team at ePPC Digital with expertise spanning project leadership, account management, and data science.
Karl PaeProject Manager
Gertrud ReiAccount Manager
Daniella PredeinaAccount Manager
Chinmay KulkarniData Scientist