Healthcare Provider
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    Salesforce
    Attribution
    Data Ops

    Healthcare Provider

    Building a Salesforce-Based Attribution System

    November 2025

    Key Results

    Revenue Visibility

    0%0%

    Pipeline per Ad Dollar

    0x+0x+

    ROAS Improvement

    0%0%

    Performance Over Time

    The Challenge

    A multi-location dental implant provider was spending $50-80k/month on digital ads but couldn't prove ROI. Their patient management system was completely disconnected from their marketing data, 0% of revenue was traceable to a specific campaign.

    The disconnect created a classic blame game:

    Marketing Team: "We sent 2,000 leads this month!"

    Sales Team: "The leads are trash. None of them convert."

    CEO: "I'm cutting the marketing budget."

    Without data connecting ad spend to actual patient revenue, everyone was operating on assumptions.


    The Solution

    We built a bridge between ad platforms and clinic revenue using Salesforce as the central hub. The goal: track every dollar from first click to final payment.


    Implementation

    Phase 1: UTM Standardization

    We enforced a strict UTM naming convention across all channels:

    ParameterPurposeExample
    utm_sourcePlatformgoogle, facebook, bing
    utm_mediumCampaign typecpc, social, display
    utm_campaignCampaign nameimplants_q4_2025
    utm_contentAd variationvideo_testimonial_v2
    utm_termKeyworddental implants near me

    Phase 2: Click ID Capture

    We implemented hidden fields on every form to capture:

    • GCLID (Google Click ID)
    • FBCLID (Facebook Click ID)
    • MSCLKID (Microsoft Click ID)

    These IDs are the key to connecting anonymous clicks to identified patients.

    Phase 3: Salesforce as the Brain

    The magic happened in Salesforce:

    1. Lead Creation: Form submission triggers automatic capture of all UTMs and Click IDs
    2. Opportunity Tracking: Attribution data follows leads through the sales funnel
    3. Revenue Trigger: Treatment completion (Closed Won) fires a webhook
    4. Offline Conversion: Webhook sends revenue value back to ad platforms

    The Customer Journey Flow:

    Ad Click ➜ Form Fill ➜ Lead Created ➜ Patient Scheduled ➜ Treatment Complete ➜ Revenue ➜ Sent Back to Ad Platform


    The Results

    100% Revenue Visibility

    For the first time, the team could see exactly how much revenue each campaign generated, not just leads, but actual dollars collected, at full campaign-level attribution.

    A Multi-Million Dollar Treatment Pipeline, 15x+ Per Ad Dollar

    Ads generated a multi-million dollar treatment pipeline in plans presented, over 15x pipeline value per ad dollar, with the best months reaching 25x. Smart Bidding, now optimizing on real revenue instead of form fills, improved ROAS by 40% within 60 days of go-live.

    Channel Truth Revealed

    Attribution exposed what each channel's consults are actually worth:

    ChannelAvg Collections per Consult
    Facebook/Meta$2,100
    Google$1,800
    Organic/Direct$980

    Ruthless Reallocation

    The data revealed which spend wasn't producing patients:

    • TikTok killed after one month: strong lead volume, near-zero consults, $0 in sold treatment
    • Generic search cut ($59-68 CPL) in favor of brand search ($6-18 CPL) and Meta lead-gen
    • $15k+/month reallocated from awareness campaigns that looked great on paper but produced no revenue

    Aligned Teams

    Marketing and Sales finally had a shared source of truth. The finger-pointing stopped because the data was undeniable.


    Key Takeaways

    If you can't see revenue in your ad account, you're flying blind. Optimizing for leads when you should be optimizing for revenue leaves massive value on the table.

    Offline conversion tracking is essential for service businesses. If your sale happens offline (phone call, in-person visit), you need this infrastructure.

    Salesforce is more than a CRM. It can be the central hub for your entire revenue operations stack.

    Data alignment fixes culture problems. When everyone looks at the same numbers, the blame game ends.

    Want Results Like This?

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