How It Works
Three simple steps to get accurate calculations
1
Enter your volume and time
Monthly questions across chat/email/phone and minutes per question (including wrap‑up).
2
Add labor and bot costs
Cost per hour for your team, bot monthly cost (plan + usage), and one‑time setup.
3
See savings & payback
Net savings, FTE saved (160 h/mo), ROI, and payback months—all from your inputs.
AI Chatbot Savings Calculator
Estimate monthly savings when a bot answers common questions. Simple inputs, clear results—no AI expertise needed.
Share Your Scenario
Copy link with your current inputs
Quick Inputs
Total questions across chat/email per month.
Average time a person spends to resolve one question.
$
Fully loaded hourly cost for your team (wages + overhead).
%
Percent of questions the bot fully resolves without a person.
$
Your plan’s monthly fee (include usage/overage if any).
$
One-time setup, training, and integration cost.
Advanced (Optional)
Spread the setup cost across these months. Default is 12.
When a person still helps, minutes saved by bot (triage, context). Optional.
Results
Net Monthly Savings
$4,666.67
ROI: 583.3% • Payback: 2.1 months
Time Saved
Hours saved (self‑resolved)180.0 h
Hours saved (escalations)0.0 h
Total hours saved180.0 h
FTE saved (≈160 h/mo)1.13
Cost Breakdown
People cost avoided$6,300.00
Bot monthly cost$800.00
Setup amortized / month$833.33
Assumptions: coverage is the share of questions the bot resolves on its own. If a person still helps, the bot may save a few minutes by triaging and collecting context.
Frequently Asked Questions
What if my coverage is low at first?
Start with a conservative percentage (e.g., 30–50%). Train the bot on the top 20–30 intents (FAQs) to increase coverage and revisit the calculator monthly.
How many hours per FTE?
We use 160 hours per month as a simple benchmark (40 hrs/week × 4 weeks). Adjust savings or minutes per question if your baseline differs.
Can I model usage separately?
Yes. If you know usage/overage, include it in your monthly bot cost. For simplicity, the calculator treats it as one monthly amount.
Does this account for off‑hours coverage?
Indirectly. If the bot answers outside business hours, your coverage percentage typically increases—raise “Bot answers on its own (%)” to reflect that.
How should I estimate minutes saved on escalations?
If the bot gathers order info or summarizes the issue before hand‑off, many teams save 2–3 minutes per escalated ticket. Start small (1–3 min) and measure.
What if we have seasonal spikes?
Run scenarios for peak months vs average to size the impact. The calculator shows monthly results; you can average across your seasonality.
How can an AI chatbot help our company beyond cost savings?
A well‑trained chatbot improves First Response Time (FRT) to seconds, offers 24/7 coverage, deflects repetitive tickets (password resets, order status, policy questions), qualifies sales leads (collects firmographics and use case), books meetings, and routes complex issues with context. This lifts CSAT, reduces queue backlog, and shortens sales cycles by handling basic objections and FAQs instantly.
What are the typical use cases by team?
- Support: Order status, shipping & returns, billing questions, password resets, troubleshooting guides, warranty & policy info.
- Sales: Lead capture, qualification (industry, team size, budget), product fit FAQs, pricing guidance, calendar booking, handoff to rep.
- Success: Onboarding checklists, feature education, usage tips, renewal reminders.
- HR/Internal: PTO policy, benefits, IT help, onboarding docs.
How do we set one up (general steps)?
- Pick top 20–30 FAQs: Export the last month of tickets/chats; cluster by topic.
- Assemble a knowledge base: Help center articles, product docs, policies, pricing notes, return rules.
- Choose a platform: Start with a hosted chatbot that supports your channels (web chat, email, helpdesk integration) and guardrails.
- Design escalation: Clear handoff to human agents with transcripts and collected context.
- Launch a pilot: Off‑hours first or a subset of traffic; monitor containment and CSAT.
- Iterate weekly: Add new intents, improve answers, tighten guardrails, expand routing.
What data do we need to train the bot?
Start with public content: knowledge base, docs, shipping/return policies, product feature pages, and support macros. Add structured data where possible (SKU policies, pricing rules). Avoid sensitive data. Keep a change log to refresh the bot when content updates.
How do we measure success?
Track containment (% resolved without human), FRT, Average Handle Time for escalations, CSAT for bot‑handled conversations, and deflection (tickets avoided). For sales flows, track meetings booked, qualified leads, and conversion influenced by faster responses.
What about risk, quality, and compliance?
Use guardrails: restrict to trusted content, provide citations, block unsafe topics, and require human approval for sensitive actions (billing changes, PII). Log conversations for review and add an easy “talk to a person” escape hatch. Ensure your vendor supports SOC 2/GDPR where relevant.
How much does a chatbot cost and how should we budget?
Costs usually include a platform fee plus usage (messages/tokens) and a one‑time setup. Start with a small plan, then right‑size after measuring volume and coverage. This calculator treats costs simply as a monthly fee plus optional setup amortized over 12 months.
When should we escalate to a person?
Escalate for nuanced account issues, identity verification, refunds/exceptions, or when confidence is low. The bot should triage and pass a concise summary so humans save time even on escalations.
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Results are estimates for informational purposes only. Consult professionals for important decisions.