Case Study · Health Insurance Brokerage
LGG Media replaced ten third-party lead vendors with proprietary phone tracking and offline conversion infrastructure to make profitable scaling possible at every spend level.
When this national health insurance brokerage came to LGG Media, it was spending $5K per day (about $150K/month) acquiring customers through ten third-party lead vendors. The premium-to-cost ratio (PTC), the core profitability metric in this industry, ran between 0.6 and 0.8 at that spend level.
The structural problem was lead exclusivity. Third-party health insurance leads are sold to multiple competing brokers at once. The brokerage was paying for the same prospects its competitors were calling.
Managing ten vendors with inconsistent data quality and no unified attribution left no reliable way to tell which spend produced profitable customers. Every attempt to increase volume pushed the PTC ratio lower.
The ceiling at $5K per day (about $150K/month) was not a budget constraint. It was a data quality limitation. More spend through vendor channels produced diminishing PTC ratios, with no way to identify which vendor, keyword, or segment created value.
Seventy-five percent of conversions came through Google Ads call extensions rather than web forms. Call extensions are limited to static conversion values.
The algorithm received an identical signal for a customer enrolling in a $300 per month plan as for a customer enrolling in a $1,500 per month plan. It was optimizing for call volume, not premium value.
Scaling spend produced more calls, not more $1,500 per month customers.
The only path forward was to capture the gclid from each call, match it to the policy enrolled, pull the actual monthly premium from the CRM, and pass that premium back to Google as a dynamic conversion value. No off-the-shelf platform could do this. The infrastructure was built from the ground up. See the mechanics in our Google Ads call tracking guide.
The foundation was a proprietary phone tracking system built and owned by LGG Media: a pool of over 500 numbers with device fingerprinting and session-based call attribution. Every inbound call was matched to the exact visitor fingerprint shown that number, tied to the original ad click, and logged against the lead record.
A revenue collection process tracked individual policy sales. When a customer enrolled, the CRM recorded the policy details and monthly premium. That data synced to LGG Media's tracking server, which matched the premium to the original click via the fingerprint and click ID.
LGG Media's phone system integrates with Google's supported call-tracking mechanism for native gclid capture, enabling direct capture of the click ID from call extensions.
Why this works: with native gclid capture in place, the actual enrolled premium could be passed as the dynamic conversion value for every call-generated enrollment. At peak, the account reached 92% exact click attribution across all transactional events. For the mechanics behind this tracking, see how attribution infrastructure works →
Before the native integration, Google Ads received an identical conversion signal for every enrolled customer, regardless of premium. After it, every call-generated enrollment passed the actual enrolled premium as the dynamic conversion value.
The algorithm could now differentiate a $300 per month customer from a $1,500 per month customer. Bid strategy shifted from optimizing for call volume to optimizing for premium value.
The algorithm identified which keywords, audiences, and query patterns produced high-value enrollments, and allocated budget accordingly. The account reached $15K per day (about $460K/month) within six weeks, a 3x increase from the prior $5K ceiling, with customer acquisition cost holding between $400 and $600.
The off-season baseline, after Open Enrollment concluded, settled at $25K to $45K per day (about $760K to $1.4M/month) rather than returning to $5K. The algorithm had accumulated 12+ months of accurate premium-value signal. That signal does not reset when a campaign pauses. More on this in our Google Ads offline conversion tracking guide.
The account scaled from $5K to $15K per day (about $150K to $460K/month) within six weeks of the native integration going live. By November 2025, all ten third-party lead vendors had been replaced by owned acquisition infrastructure. December 2025 saw sustained spend above $100K per day (about $3M/month) throughout Open Enrollment, with a single peak day reaching $130K without losing profitability.
The off-season baseline settled at $25K to $45K per day (about $760K to $1.4M/month), five to nine times higher than the third-party baseline. Customer acquisition cost held at $400 to $600 consistently across all spend levels. Customer volume went from roughly 10 per day to 50 to 125 per day depending on season.
Google published the results from this account in a case study in 2025, naming LGG Media and Juan Colicchio as agency partner. View the Google-published case studies →
Published by Google Ads: Google released an official case study on Central Health Advisors, a health insurance client of LGG Media, covering 23% revenue growth driven by AI Max text customization. Read Google's official case study (PDF) →
The jump from $5K to $130K per day (about $150K to $4M/month) happened over six weeks once the native gclid integration went live. That compression is accurate. What it omits is the 21 months of infrastructure development that made the integration possible.
The 500+ number pool, the device fingerprinting system, the CRM revenue sync, and the Google whitelist authorization were all prerequisites. None could have been assembled in six weeks. The whitelist authorization alone required a demonstrated track record of accurate attribution data before Google would authorize native integration.
Health insurance PPC accounts that try to scale without this infrastructure hit the same ceiling this brokerage had at $5K per day (about $150K/month). The ceiling is a data quality limitation, not a budget limitation.
The off-season baseline settling at $25K to $45K per day (about $760K to $1.4M/month), five to nine times higher than the pre-engagement floor, reflects accumulated algorithm learning, not campaign activity alone. That learning is durable. It is the compounding return on 21 months of infrastructure investment.
Explore the approach: Health insurance lead generation → · Lead generation → · Pay-per-click management → · All client results →
Next Step
If call volume is increasing but premium quality is inconsistent, the conversion signal reaching your algorithm is the problem.
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