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Generative AI > Google Gemini API > Sales Incentive Agent

Sales Incentive Agent

Author: Venkata Sudhakar

Calculating sales commissions at ShopMax India involves quota attainment, product mix multipliers, and accelerator tiers for overachievement - and disputes arise when reps feel the calculation is opaque. A Sales Incentive Agent automates the monthly commission run: it calculates each rep's payout, shows a transparent breakdown, flags anomalies, and generates a statement the rep can trust.

This tutorial builds a Sales Incentive Agent using Google ADK and Gemini 2.0 Flash. The agent applies the incentive plan rules to each rep's monthly bookings, calculates tiered commissions, and produces a detailed incentive statement.

The below example shows the Sales Incentive Agent calculating the April 2026 commission for a rep in the Bangalore territory.

from google.adk.agents import Agent
from google.adk.tools import FunctionTool
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.genai.types import Content, Part

# Incentive plan structure
INCENTIVE_PLAN = {
    "base_rate_pct": 2.5,        # 2.5% commission on all bookings
    "accelerator_tiers": [
        {"min_attainment": 100, "max_attainment": 120, "rate_pct": 4.0},
        {"min_attainment": 120, "max_attainment": 999, "rate_pct": 6.0},
    ],
    "product_multipliers": {
        "servers": 1.2,    # 20% bonus for server deals
        "services": 1.5,   # 50% bonus for services/AMC
        "accessories": 0.8 # reduced for accessories
    }
}

def calculate_commission(rep_name: str, monthly_quota_lakh: float,
                          bookings: list) -> dict:
    """Calculate commission for a rep based on bookings and quota.
    bookings: list of dicts with keys: deal_id, value_lakh, product_type
    """
    total_bookings = sum(b["value_lakh"] for b in bookings)
    attainment_pct = round(total_bookings / monthly_quota_lakh * 100, 1)

# Calculate base commission with product multipliers
    base_commission = 0
    deal_breakdown = []
    for b in bookings:
        multiplier = INCENTIVE_PLAN["product_multipliers"].get(b["product_type"], 1.0)
        effective_rate = INCENTIVE_PLAN["base_rate_pct"] * multiplier / 100
        deal_commission = b["value_lakh"] * effective_rate
        base_commission += deal_commission
        deal_breakdown.append({
            "deal_id": b["deal_id"],
            "value_lakh": b["value_lakh"],
            "product_type": b["product_type"],
            "multiplier": multiplier,
            "commission_lakh": round(deal_commission, 3)
        })

# Apply accelerator if quota attained >= 100%
    accelerator_bonus = 0
    accelerator_applied = None
    if attainment_pct >= 100:
        for tier in INCENTIVE_PLAN["accelerator_tiers"]:
            if tier["min_attainment"] <= attainment_pct < tier["max_attainment"]:
                # Accelerator applies to all bookings at the higher rate
                extra_rate = (tier["rate_pct"] - INCENTIVE_PLAN["base_rate_pct"]) / 100
                accelerator_bonus = total_bookings * extra_rate
                accelerator_applied = tier["rate_pct"]
                break

total_commission = base_commission + accelerator_bonus
    return {
        "rep": rep_name,
        "monthly_quota_lakh": monthly_quota_lakh,
        "total_bookings_lakh": round(total_bookings, 2),
        "quota_attainment_pct": attainment_pct,
        "base_commission_lakh": round(base_commission, 3),
        "accelerator_rate_pct": accelerator_applied,
        "accelerator_bonus_lakh": round(accelerator_bonus, 3),
        "total_commission_lakh": round(total_commission, 3),
        "total_commission_rs": round(total_commission * 100000),
        "deal_breakdown": deal_breakdown
    }

def check_disputes(rep_name: str, calculated_commission_rs: float) -> dict:
    """Check if there are any pending disputes for this rep."""
    # Simulated disputes database
    disputes = {
        "Priya": {"deal_id": "D092", "disputed_amount_rs": 12000,
                  "reason": "Deal D092 was a team deal - split credit pending"}
    }
    if rep_name in disputes:
        d = disputes[rep_name]
        return {"has_dispute": True, "dispute": d,
                "net_payable_rs": calculated_commission_rs - d["disputed_amount_rs"]}
    return {"has_dispute": False, "net_payable_rs": calculated_commission_rs}

commission_tool = FunctionTool(func=calculate_commission)
dispute_tool = FunctionTool(func=check_disputes)

incentive_agent = Agent(
    model="gemini-2.0-flash",
    name="sales_incentive_agent",
    instruction="""
        You are a Sales Incentive Agent for ShopMax India.
        When given rep bookings for the month:
        1. Calculate the commission using the incentive plan
        2. Check for any pending disputes
        3. Generate a transparent incentive statement:
           - Quota vs attainment summary
           - Deal-by-deal commission breakdown
           - Accelerator tier explanation if applicable
           - Any disputes and their impact
           - Final net payable amount in Rs
        The statement must be clear enough that the rep can self-verify.
    """,
    tools=[commission_tool, dispute_tool]
)

session_service = InMemorySessionService()
runner = Runner(agent=incentive_agent, app_name="incentive", session_service=session_service)

session = session_service.create_session(app_name="incentive", user_id="sales_ops")
prompt = """
    Calculate April 2026 commission for Priya (Bangalore).
    Monthly quota: Rs 150 lakhs
    Bookings:
    - D089: Rs 60 L, product_type: servers
    - D090: Rs 45 L, product_type: services
    - D091: Rs 35 L, product_type: accessories
    - D092: Rs 25 L, product_type: servers
"""
message = Content(role="user", parts=[Part(text=prompt)])
for event in runner.run(user_id="sales_ops", session_id=session.id, new_message=message):
    if event.is_final_response():
        print(event.content.parts[0].text)

It gives the following output,

INCENTIVE STATEMENT - Priya (Bangalore)
Period: April 2026
========================================

Quota vs Attainment
  Monthly Quota   : Rs 150.00 lakhs
  Total Bookings  : Rs 165.00 lakhs
  Quota Attainment: 110%  -> Accelerator Tier 1 activated (4.0% rate)

Deal Breakdown
Deal   Value     Product      Multiplier  Commission
D089   Rs 60 L   Servers      x1.2        Rs 1,800
D090   Rs 45 L   Services     x1.5        Rs 1,688
D091   Rs 35 L   Accessories  x0.8        Rs  700
D092   Rs 25 L   Servers      x1.2        Rs  750
Base Commission Total: Rs 4,938

Accelerator Bonus
  Attainment 110% qualifies for 4.0% rate
  Extra rate applied: (4.0 - 2.5)% = 1.5% on Rs 165 L
  Accelerator Bonus: Rs 2,475

Gross Commission  : Rs 7,413

Disputes on Record
  Deal D092 is a team deal - split credit pending
  Amount withheld  : Rs 12,000

Net Payable This Month: Rs 59,413
(Dispute amount will be released once split is confirmed)

The Sales Incentive Agent brings transparency and speed to commission processing. Run it at month-end across all reps in a batch loop and post individual statements automatically. Extend it to handle SPIFs (special incentive funds), multi-product quota splits, and team deal credit allocation to cover the full complexity of enterprise sales compensation plans.

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