AI Phone Ordering ROI Calculator: A Simple Model
Estimate recovered revenue and labor savings from AI phone ordering in minutes.
If you want to justify AI phone ordering, you need a simple, credible ROI model. Use the framework below and swap in your real numbers.
Step 1: Calculate recovered revenue
recovered_revenue = missed_calls_per_day × average_ticket × days_open_per_yearIf you miss 5 calls per day and the average ticket is $35:
5 × 35 × 365 = $63,875Step 2: Calculate labor time saved
hours_saved = (total_calls_per_day × avg_handle_time_minutes) ÷ 60Even saving 1-2 hours per day can reduce overtime and burnout.
Step 3: Add upsell lift (optional)
If AI suggests add-ons consistently, apply a modest lift:
upsell_lift = completed_orders_per_day × avg_ticket × lift_percentStart with 3-5% if you want a conservative estimate.
Step 4: Compare to AI cost
Compare annual savings to the AI plan cost to estimate payback period.
Quick Takeaways
- Use real call volume and average ticket size.
- Keep assumptions conservative to avoid inflated ROI.
- Validate with a short pilot before scaling.
- Ready to test? Try the demo.
FAQs
What inputs do I need for the ROI model?
Call volume, missed-call rate, average ticket size, and average handle time.
Does this include labor savings?
Yes. It estimates hours saved from reduced call handling and re-entry.
How should I validate the results?
Run a 2-week pilot and compare actual calls, orders, and staff time.
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