What is Average Ticket Size?
Average ticket size (also called average check size) is the mean dollar amount customers spend per transaction. In QSR drive-thrus, this metric directly reflects revenue efficiency: higher average tickets mean more revenue from the same number of customers. Voice AI systems can increase average ticket size by 1.5%+ through consistent, intelligent upselling on every order.
The formula is simple: total revenue divided by total transactions. But the strategies to improve it require sophistication, especially at scale across hundreds of locations.
Why Average Ticket Size Matters for QSRs
Drive-thru traffic is relatively fixed. You can only serve so many cars per hour. Once you’ve optimized throughput, the primary lever for revenue growth is getting more from each transaction.
The math of small improvements:
A 1.5% increase in average ticket size sounds modest, but consider a location doing $1.5M annual drive-thru revenue:
- 1.5% increase = $22,500 additional revenue per year
- Across 500 locations = $11.25M additional annual revenue
- With minimal additional cost (upsells have high margins)
This is why consistent upselling matters more than aggressive upselling. Small gains on every transaction compound dramatically.
How Voice AI Increases Average Ticket Size
Consistent Upsell Execution
Human employees upsell inconsistently. They forget during busy periods, skip it when tired, or vary in enthusiasm. Voice AI offers every guest an upsell opportunity, every time, without fail.
Human upsell patterns:
- Morning shift (fresh): 70% upsell attempt rate
- Rush hour (stressed): 30% upsell attempt rate
- Late night (tired): 40% upsell attempt rate
Voice AI upsell pattern:
- All shifts: 100% upsell attempt rate
This consistency alone drives ticket size increases, even before considering optimization.
Intelligent Upsell Selection
Voice AI doesn’t just offer upsells; it offers the right upsells based on:
Order context:
- Burger ordered → offer fries and drink
- Combo ordered → offer dessert or size upgrade
- Multiple items → offer family meal deal
Time-based logic:
- Breakfast → coffee add-on
- Afternoon → snack items
- Late night → value deals
Location-based rules:
- Regional preferences
- Local promotions
- Inventory-aware suggestions
Automated Backoff
During peak times, aggressive upselling can slow throughput and cost more revenue than it generates. Smart Voice AI systems:
- Detect long lines (via vehicle detection or timing)
- Reduce upsell aggressiveness automatically
- Prioritize speed over ticket size when appropriate
- Resume full upselling when lines clear
This balance maximizes total revenue rather than optimizing a single metric.
Average Ticket Size Benchmarks
| Metric | Typical Range |
|---|---|
| QSR average ticket | $8-15 depending on brand |
| Human upsell conversion | 15-25% |
| Voice AI upsell conversion | 25-40% |
| Ticket lift from Voice AI | 1.5-3% |
Hi Auto customers see average ticket increases of 1.5%+ through consistent upsell execution and intelligent offer selection.
Measuring Ticket Size Impact
Before/After Comparison
The cleanest measurement compares the same locations before and after Voice AI deployment:
1. Establish baseline average ticket (3+ months of data)
2. Deploy Voice AI
3. Measure new average ticket (after stabilization period)
4. Calculate lift percentage
Control Group Testing
For larger deployments, compare Voice AI locations against non-Voice AI locations:
- Match locations by volume, demographics, and region
- Run parallel measurement periods
- Attribute difference to Voice AI impact
Isolating Variables
Ticket size changes can come from many sources:
- Menu price changes
- New product launches
- Seasonal patterns
- Economic conditions
- Promotional activity
Proper measurement controls for these factors to isolate Voice AI’s contribution.
Strategies to Maximize Ticket Size with Voice AI
Optimize Upsell Scripts
Test different upsell phrasings:
- “Would you like to make that a large?” vs. “Large drink for just 50 cents more?”
- Direct offers vs. assumptive suggestions
- Single option vs. choice between two options
A/B Test Offers
Run controlled tests on:
- Which products to upsell
- When to offer upgrades vs. add-ons
- How many upsell attempts per order
- Timing within the conversation
Leverage Daypart Optimization
Different times call for different strategies:
- Breakfast: Coffee upsells, combo completions
- Lunch rush: Speed over upselling
- Afternoon: Snack and dessert adds
- Dinner: Family meal suggestions
- Late night: Value bundles
Common Misconceptions About Average Ticket Size
Misconception: “Higher ticket size is always better.”
Reality: Ticket size must be balanced against throughput. An extra $1 per order isn’t worth it if it adds 30 seconds to order time and you lose 2 cars per hour. Total revenue optimization requires considering both metrics.
Misconception: “Aggressive upselling maximizes ticket size.”
Reality: Overly aggressive upselling annoys guests and can reduce return visits. The best approach is relevant, helpful suggestions that feel like service rather than sales pressure.
Misconception: “Voice AI upselling feels robotic and pushy.”
Reality: Well-designed Voice AI upsells are conversational and contextual. “That’s a great choice. Would you like to add a chocolate chip cookie for dessert?” feels natural, not robotic.