Model chatbot cost, retained human work, net benefit, and first-year ROI using your own support data.
Enter your scenario, then calculate to see the result.
This model treats containment as an input, keeps handoffs and quality work visible, and compares the full first-year benefit with the AI investment. Run more than one scenario before using it in a decision.
Take conversation volume and handle time from the same recent period. Multiply those hours by a fully loaded labor cost that reflects your actual team—not a public benchmark.
Uncontained conversations still need their current handle time. Add review minutes for AI-contained conversations plus monthly QA, knowledge, testing, and maintenance hours.
Monthly AI operating cost is the platform fee plus variable cost per conversation. First-year investment adds twelve months of that cost to setup and rollout work.
Compare conservative, expected, and upside cases. Change containment, review time, and maintenance effort first; those assumptions often decide whether the estimate remains attractive.
These are arithmetic examples, not BoundBot results or industry benchmarks. Replace every number with your own measured costs and pilot assumptions.
“1,000 chats × 6 minutes × $22/hour creates a $2,200 baseline. At 45% containment, 0.75 review minutes, 10 QA hours, and $329 monthly AI cost, estimated monthly net benefit is $317.25.”
WHY IT WORKS // Makes review and ongoing QA visible instead of valuing every contained chat as pure savings.
“300 chats × 8 minutes × $20/hour creates an $800 baseline. At 40% containment, 1 review minute, 8 QA hours, and $314 monthly AI cost, estimated monthly net benefit is −$194.”
WHY IT WORKS // Shows that a chatbot is not automatically economical when volume is low and fixed work remains.
“At 2,000 chats, 8 minutes, and $25/hour, moving containment from 65% down to 50% reduces estimated monthly net benefit from $3,403.50 to $2,466.”
WHY IT WORKS // Containment is an assumption to validate in a pilot, not a guaranteed outcome.
“Using the default scenario, increasing QA and maintenance from 12 to 30 hours lowers monthly net benefit by $450 at a $25 loaded hourly cost.”
WHY IT WORKS // Turns the often-hidden cost of maintaining approved answers into a visible planning variable.
“For 2,000 monthly conversations, variable AI cost rising from $0.03 to $0.12 per conversation adds $180 per month and reduces first-year net benefit by $2,160.”
WHY IT WORKS // Separates usage-sensitive costs from the recurring platform fee.
“The default inputs produce $39,342 in first-year net benefit and $5,808 in first-year AI investment, for an estimated 677.4% ROI.”
WHY IT WORKS // Uses net benefit divided by the modeled AI investment; it is an illustration, not a forecast or guarantee.
Create a BoundBot workspace, choose one repeatable support job, ground the bot in approved knowledge, and measure containment, review effort, and handoffs against the assumptions you modeled here.
Start free. Results depend on your use case, data, configuration, traffic, team process, and connected channels.
The calculator is intentionally simple enough to audit. These answers define the formulas, the assumptions, and what still needs human review.
Baseline cost is monthly conversations multiplied by current handle time and loaded hourly cost. Post-launch human cost includes full handling for uncontained conversations, review time on contained conversations, and monthly QA and maintenance. Monthly net benefit subtracts post-launch human cost and AI operating cost from the baseline.
The denominator is the one-time setup and rollout cost plus twelve months of platform and variable AI operating costs. First-year ROI is first-year net benefit divided by that investment. This is a planning convention, so use the investment definition your finance team approves.
Automation still needs exception handling, transcript sampling, knowledge updates, testing, and workflow maintenance. Leaving that work out can overstate the benefit, especially during a new rollout.
A contained conversation reaches an acceptable outcome without a human taking over. Define the outcome and exclusions before measuring it. A pilot containment rate is more useful than an unverified industry average.
No. The model values support labor and the costs you enter. It does not predict incremental sales, customer lifetime value, churn reduction, taxes, financing, or implementation risk, and no result is guaranteed.
Treat it as useful evidence. Check whether the use case is too small, the fixed cost is too high, or retained work is underestimated. A narrower workflow, a lower-cost setup, or a non-financial service goal may be more appropriate—but validate that separately.
No. The deterministic formulas run in your browser. The page may record aggregate tool events such as calculate or copy, but the numeric values you enter are not included in those events.
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