IOU Financial had a problem most marketing teams would envy: too many leads.
The fintech lender was generating hundreds of leads monthly from paid search, organic, and referral channels. Cost per lead looked good. Volume was climbing. But when their CMO asked herself, “Which campaigns are actually driving closed loans?”—but had no answer.
Google Ads reported one story. The CRM told another. Marketing decisions were based on lead counts, not revenue data.
“We were generating leads from multiple channels, but we had no clear view of which ones were actually turning into closed loans,” said Elizabeth Lowman, Head of Marketing at IOU Financial.
Within months of implementing revenue-based attribution, IOU Financial increased their qualified lead rate by 49% and improved ROAS from 3× to 11×. Not by spending more. By finally seeing which campaigns drove revenue—and reallocating budget accordingly.
Here’s how they did it.
The challenge: lead volume without revenue clarity
IOU Financial generates most of its leads through paid search, with additional traffic from organic, direct, and referral sources. This multi-channel approach drove solid lead volume—but the team couldn’t see which sources produced leads that actually converted into loans.
Before LeadSources, the marketing team relied on Google Ads reporting and Google Analytics. These tools showed how many leads came in. They didn’t show which leads progressed through the sales funnel or converted into revenue.
The result? Three critical blind spots:
1. Budget allocation based on lead volume, not lead quality
Campaigns generating high lead counts received more budget—regardless of whether those leads closed into loans. High-volume campaigns looked successful. Some were. Many weren’t.
2. Attribution mismatch between Google and CRM
Google Ads credited campaigns using last-click attribution. The CRM showed different patterns. Marketing reported success on campaigns that sales said underperformed. Nobody knew which data to trust.
3. No measurement of lead quality
All leads counted equally in reporting. A lead that closed into a $50,000 loan looked identical to a lead that never responded to outreach. The team optimized for quantity because they couldn’t measure quality.
“We were making budget and optimization decisions based solely on raw lead counts, not the quality or revenue impact of those leads,” said Lowman. “Our CRM data didn’t always match Google’s reporting, which made it difficult to know which campaigns were truly performing.”
The core problem: marketing decisions without revenue visibility.
The solution: connecting leads to revenue
IOU Financial implemented LeadSources to close the gap between acquisition data and loan conversions.
The system captured detailed attribution information at every step of the buyer journey and synced it directly into their CRM. For the first time, the team could reconcile CRM records with paid search performance and see which sources actually delivered qualified leads.
Three capabilities changed how they operated:
LeadDNA: complete lead source tracking
LeadDNA captured a full profile for every lead: channel, UTM parameters, device data, and more. This allowed the team to identify which campaigns, keywords, and landing pages produced qualified leads versus unqualified ones.
LeadPath: full customer journey visibility
LeadPath tracked leads across multiple sessions, from first click to final form submission. Instead of seeing only the last touchpoint before conversion, the marketing team could see the complete path: how leads discovered IOU Financial, which pages they visited, and what influenced their decision to apply.
Native CRM integration
LeadSources connected directly to IOU Financial’s custom form and CRM, automatically syncing attribution data for every lead. Marketing could now see which leads progressed through the pipeline and which closed into loans, without manual tagging or data exports.
“Having all the attribution data synced directly into our CRM made it so much easier to see which campaigns were actually driving qualified leads,” said Lowman.
The methodology shift was simple: Stop optimizing for lead counts. Start optimizing for revenue impact.
“LeadSources gave us full visibility into the buyer journey, allowing us to stop optimizing based on lead counts alone and focus on revenue impact.”
The results: 49% more qualified leads, ROAS from 3× to 11×
After implementing LeadSources, IOU Financial increased their qualified lead rate by 49% and improved ROAS from 3× to 11×.
How the improvements compounded:
With full visibility into which campaigns generated qualified leads, the team reallocated budget away from high-volume, low-quality sources and increased investment in campaigns with strong conversion rates.
The data revealed patterns Google Ads couldn’t show: some high-volume campaigns had poor qualification rates, while certain lower-volume campaigns consistently produced leads that closed into loans.
By shifting budget toward proven performers, the qualified lead rate jumped 49%. With more qualified leads entering the pipeline, conversion to closed loans improved, and ROAS accelerated from 3× to 11×.
“With LeadSources, our qualified lead rate for paid search increased by 49%,” said Lowman. “We also improved our ROAS from 3× to 11×, allowing us to invest more strategically in campaigns that actually drive revenue.”
The reporting confidence factor:
Beyond the metrics, IOU Financial gained something harder to quantify: confidence in their own data. CRM records now matched ad platform reporting. Marketing and sales looked at the same numbers. Budget decisions were backed by revenue data, not lead counts.
Key takeaways: what this means for fintech marketing
IOU Financial’s results reveal three lessons applicable to any marketing team managing multi-channel lead generation:
1. Lead volume is not a success metric
Campaigns generating the most leads aren’t always generating the most revenue.
Without tracking lead quality and conversion outcomes, you’re optimizing for the wrong goal.
IOU Financial discovered that some of their highest-volume campaigns had the weakest qualification rates, information that Google Ads and Google Analytics couldn’t surface.
2. Attribution tools need to connect to revenue
Google Ads shows acquisition metrics: clicks, conversions, cost per lead.
It doesn’t show which leads become customers. The gap between “lead generated” and “loan closed” is where the most valuable insights live, and where most marketing teams are flying blind.
3. Full-funnel visibility changes optimization strategy
When you can see the complete customer journey, you optimize differently.
IOU Financial used LeadPath to understand how leads progressed across multiple sessions, which touchpoints influenced decisions, and which sources produced leads that stuck versus dropped off.
The result wasn’t incremental improvement. It was a fundamental shift in how they allocated budget: from assumptions based on lead counts to decisions based on revenue data.
If you want to learn more about the results, read the full case study about IOU Financial.