Estimate the financial ROI of deploying an Agentic AI chatbot in a UK contact centre, segmented by customer age demographics. Calculates contained and escalated calls, agent hours saved, labor and overtime savings, AI costs, net benefit, ROI, payback period, and 3-year net benefit.
Contact Centre – Demographic-Based Containment Model
This is a financial model for deploying an Agentic AI conversational chatbot within a UK contact centre.
The chatbot:
• Handles inbound customer interactions
• Resolves issues autonomously (containment)
• Escalates complex cases to human agents
• Provides generationally differentiated adoption and containment
Monthly inbound calls must be segmented into:
• Under 30 years old
• 31–60 years old
• Over 60 years old
Each demographic MUST have its own containment assumption.
All currency must be in GBP (£).
No external benchmarks.
All performance improvements must be explicit user-editable assumptions.
No hidden constants.
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CALCULATOR OBJECTIVE
Estimate:
• Calls contained by AI per demographic
• Escalated calls to human agents
• Agent hours saved
• Labor cost savings
• Overtime reduction
• AI operating costs
• Net annual benefit
• ROI (%)
• Payback period (Months)
• 3-Year Net Benefit
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MANDATORY MODELING RULES
• Heuristic-only mode
• All performance assumptions MUST be explicit inputs
• No hidden constants
• All assumptions must feed a measurable financial output
• All inputs must affect at least one Terminal KPI
• Annualisation MUST be explicit (×12 shown in formulaString)
• Payback MUST use annualised benefit divided to monthly
• No algebraic collapsing
• No unused inputs
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SECTION 1 — BASELINE CALL STRUCTURE
Inputs:
• Calls per Month – Under 30
• Calls per Month – Age 31–60
• Calls per Month – Over 60
• Average Handle Time (minutes)
• Agent Fully Loaded Cost per Year (£)
• Shrinkage (%)
Derived:
Total Monthly Calls =
Under30 + Age31to60 + Over60
Annual Calls =
Total_Monthly_Calls * 12
Productive Hours per FTE per Year =
2080 * (1 - Shrinkage / 100)
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SECTION 2 — DEMOGRAPHIC CONTAINMENT ASSUMPTIONS
All must be explicit and user-editable:
• Assumption: Containment Rate – Under 30 (%)
• Assumption: Containment Rate – Age 31–60 (%)
• Assumption: Containment Rate – Over 60 (%)
Model Requirements:
Containment rate for Under 30 is expected to be higher than Over 60,
but MUST remain user-editable and not hard-coded.
Contained Calls per Demographic =
Calls_per_Month_Demo *
Containment_Rate / 100
Escalated Calls per Demographic =
Calls_per_Month_Demo -
Contained_Calls_Demo
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SECTION 3 — LABOR SAVINGS MODEL
Baseline Monthly Handling Minutes =
Total_Monthly_Calls *
Average_Handle_Time
Post-AI Handling Minutes =
Escalated_Calls_Total *
Average_Handle_Time
Monthly Minutes Saved =
Baseline_Minutes -
Post_AI_Minutes
Annual Hours Saved =
(Monthly_Minutes_Saved / 60) * 12
Annual Labor Savings =
Annual_Hours_Saved *
(Agent_Fully_Loaded_Cost /
Productive_Hours_Per_Year)
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SECTION 4 — OVERTIME REDUCTION
Inputs:
• Overtime Hours per Month
• Overtime Cost Multiplier (%)
Assumption:
• Assumption: Overtime Reduction (%)
Overtime Savings =
Overtime_Hours_per_Month *
12 *
(Agent_Fully_Loaded_Cost /
Productive_Hours_Per_Year) *
Overtime_Multiplier / 100 *
Overtime_Reduction / 100
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SECTION 5 — AI COST STRUCTURE
Inputs:
• AI Platform Cost per Month (£)
• AI Usage Cost per Contained Call (£)
• Implementation Cost (£)
• Support Cost per Month (£)
Derived:
Annual AI Usage Cost =
(Contained_Calls_Total *
AI_Usage_Cost_per_Call) *
12
Annual Recurring Cost =
(AI_Platform_Cost_per_Month * 12)
+
Annual_AI_Usage_Cost
+
(Support_Cost_per_Month * 12)
One-Time Cost =
Implementation_Cost
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SECTION 6 — FINANCIAL STRUCTURE
Total Annual Savings =
Labor_Savings +
Overtime_Savings
Net Annual Benefit =
Total_Annual_Savings -
Annual_Recurring_Cost
Year 1 Net Benefit =
Net_Annual_Benefit -
One_Time_Cost
ROI (%) =
IF((Annual_Recurring_Cost + One_Time_Cost) > 0,
Year_1_Net_Benefit /
(Annual_Recurring_Cost + One_Time_Cost) * 100,
0)
Payback (Months) =
IF(Net_Annual_Benefit / 12 > 0,
One_Time_Cost /
(Net_Annual_Benefit / 12),
0)
3-Year Net Benefit =
(Net_Annual_Benefit * 3) -
One_Time_Cost
Annualisation must remain explicit.
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DEFAULT ASSUMPTIONS (Editable)
Containment – Under 30: 60%
Containment – Age 31–60: 45%
Containment – Over 60: 25%
Overtime Reduction: 40%
All must remain editable and wired into outputs.
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REQUIRED TERMINAL KPI OUTPUTS
• Total Annual Savings (£)
• Total Annual Recurring Cost (£)
• Net Benefit (Year 1) (£)
• ROI (%)
• Payback Period (Months)
• 3-Year Net Benefit (£)