Modeling Conversion Values for Non-eCommerce Funnels: A Practical Guide
In many performance campaigns—especially those for services, appointments, or referrals—traditional eCommerce-style conversion tracking falls short. There’s often no clear “purchase” to assign value to. Yet, behind every contact form or engagement is a potential high-value outcome. That’s where conversion value modeling becomes essential.
Why Default Conversion Tracking Isn’t Enough
Google Ads’ Smart Bidding strategies like Maximize Conversion Value and Target ROAS rely on accurate conversion values to allocate budget efficiently. While defaults may work in low-stakes campaigns, high-value service funnels need precise signals to avoid wasted spend and under-optimization.
The good news? You can assign value even when the transaction happens offline. With a bit of math, you can quantify micro-conversions like form fills, tool usage, and content views—all based on historical or estimated conversion rates to revenue.
Revenue Modeling: The Math
Let’s say the average value of a completed engagement—after a full sales cycle—is $1,700. While that revenue isn’t captured directly online, it’s strongly correlated with specific digital behaviors.
Step 1: Identify High-Signal Actions
- Key informational content views
- Use of a tool or directory to locate a provider
- Submission of a form to initiate contact or service
Step 2: Estimate Conversion Rates to Revenue
Using historical data or CRM feedback:
- Form submissions convert to revenue 20% of the time
- Tool engagements: 5%
- Info views: 2%
Step 3: Multiply Rates by Value
| Conversion Action | Estimated Rate to Revenue | Calculation | Assigned Value |
|---|---|---|---|
| Form Submission | 20% | 1700 × 0.20 | $340 |
| Tool Engagement | 5% | 1700 × 0.05 | $85 |
| Page View | 2% | 1700 × 0.02 | $34 |
Step 4: Implement in Google Ads
Assign each of these values to their respective conversions under Tools & Settings > Conversions. This tells Google what each behavior is worth, even without a transaction.
Why This Math Works
When you feed real value data into your campaigns, Google’s bid algorithms begin favoring the behavior that statistically leads to revenue—not just clicks or form fills. Campaigns shift spend toward better-qualified traffic, and smart bidding decisions happen in real-time based on predictive value rather than just volume.
Key Benefits:
- Data-backed allocation of ad budget
- Prioritization of high-converting traffic
- Cleaner feedback loops for scaling
Bottom Line: Smarter Inputs = Smarter Outputs
ROAS bidding isn’t just for products—it’s for anyone who can model value from engagement to revenue. If your campaign has a meaningful offline outcome, there’s a way to quantify it. And once you do, Google Ads becomes a true performance platform, not just an expensive guessing game.
Need help modeling your funnel and assigning real value? Let’s connect—we build systems that optimize for outcomes, not impressions.
