Calculator Inputs
Example Data Table
| Scenario | Sessions | Orders | Pre-sale Rate | Post-sale Rate | Return Rate | Deflection | Estimated Tickets |
|---|---|---|---|---|---|---|---|
| Baseline month | 50,000 | 1,400 | 1.2 / 100 sessions | 14 / 100 orders | 9% | 18% | 972.94 |
| Holiday push | 92,000 | 2,944 | 1.8 / 100 sessions | 18 / 100 orders | 11% | 16% | 2,219.67 |
| Improved self-service | 50,000 | 1,400 | 1.2 / 100 sessions | 14 / 100 orders | 9% | 30% | 830.69 |
Formula Used
Estimated Orders = Sessions × (Conversion Rate ÷ 100), unless an order override is entered.
Pre-sale Tickets = Sessions × (Pre-sale Contact Rate ÷ 100).
Post-sale Tickets = Orders × (Post-sale Contact Rate ÷ 100).
Return Tickets = Orders × (Return Rate ÷ 100) × Return Contact Multiplier.
Gross Tickets = Pre-sale Tickets + Post-sale Tickets + Return Tickets.
Repeat Adjusted Tickets = Gross Tickets × (1 + Repeat Contact Rate ÷ 100).
Net Tickets = Repeat Adjusted Tickets × Campaign Multiplier × Seasonal Multiplier × (1 − Deflection Rate ÷ 100).
Agent Hours = Net Tickets × Average Handle Time ÷ 60.
Agents Needed = Agent Hours ÷ Productive Hours per Agent.
How to Use This Calculator
- Enter the number of days in your forecast period.
- Add expected sessions and your conversion rate.
- Enter an order override only when you already know order volume.
- Estimate pre-sale and post-sale contact rates from historical support data.
- Adjust return rate, repeat contact rate, and multipliers for promotions or seasonality.
- Set your self-service deflection rate to reflect help center or bot performance.
- Split ticket share across email, chat, and phone channels.
- Enter average handle time and productive hours to estimate staffing demand.
- Press the calculate button to see results above the form.
- Use the export buttons to save the result summary as CSV or PDF.
FAQs
1. What does this calculator estimate?
It estimates ecommerce support ticket demand for a chosen period. The model combines traffic, order volume, pre-sale inquiries, post-sale issues, return activity, repeat contacts, and self-service deflection.
2. When should I use an order override?
Use it when your order forecast is already known from planning data, campaign modeling, or finance targets. Leaving it blank lets the tool estimate orders from sessions and conversion rate.
3. How do I choose pre-sale and post-sale rates?
Review your historical support logs. Divide pre-sale contacts by sessions, and divide post-sale contacts by orders. Multiply each ratio by 100 to convert them into input rates.
4. What is the return contact multiplier?
Some returns create more than one conversation, such as label requests, refund checks, and exchange questions. The multiplier captures the average number of contacts created by each return case.
5. Why is self-service deflection important?
Deflection reduces projected ticket demand by counting issues solved through FAQs, chatbots, order tracking pages, or automated account tools before an agent becomes involved.
6. What happens if channel shares do not total 100?
The calculator normalizes the values automatically. This keeps the result usable while preserving the relative weighting between email, chat, and phone channels.
7. Can this help with staffing plans?
Yes. By combining ticket count with average handle time and productive hours per agent, the calculator estimates total workload hours and approximate agent demand.
8. Is this calculator suitable for daily and monthly planning?
Yes. It returns period totals and normalizes output into daily, weekly, and monthly views, making it useful for scheduling, budgeting, and campaign readiness checks.