AI Search Revenue at Risk Calculator
Four inputs. One number. See how much annual revenue your brand could lose as ChatGPT, Google AI, Perplexity, and Gemini answer queries your customers used to search.
Your inputs
Four numbers. That is all.
Total monthly organic sessions across your site — the same number GA4 shows under Organic Search.
How much of your organic volume is absorbed by AI answers this year. 30–45% is the planning range most enterprise teams use; 40% is a reasonable midpoint.
Session-to-customer rate. SaaS typically lands near 2%. Long-cycle enterprise B2B often sits between 0.3–0.8%.
Annual contract value for SaaS or average order value for commerce. Use LTV if CAC payback is multi-year.
If you do nothing
$144K
per year, across the next 12 months
- Traffic lost to AI search (annual)
- 12,000
- Customers lost
- 12
- Revenue lost per month
- $12K
Copy the live calculator link with your inputs pre-filled.
How the calculator works
Annual Revenue at Risk = Monthly Organic Traffic × AI-Search Decline Rate × Conversion Rate × Deal Size × 12
Why 40% is the default decline
Public reporting from HubSpot in 2026 showed roughly 58% organic decline on queries that now trigger a Google AI Overview. Across a blended portfolio of AI and non-AI queries, 30–45% is the planning band most enterprise teams work with. We default to a conservative midpoint.
Why conversion rates stay as-is
When a brand is indexed in the model, AI-referred traffic tends to convert at rates similar to classical organic. The shrinkage is on the volume side, not intent. Hold conversion steady and let the traffic input carry the shock.
What is NOT modeled
Brand and navigational search is more durable than informational queries. Direct traffic absorbs some of the loss. Paid media can backfill, though at rising CPCs. This calculator models the gross exposure, not the net figure after substitution.
Why this is a planning tool
Treat the output as a ceiling of exposure, not a forecast. Use it to size the problem and justify an investment. For the actual forecast you need share-of-model measurement, citation-frequency baselines, and roughly sixty days of observation.
FAQ