import streamlit as st
import json
import datetime
import os
import pandas as pd
import plotly.graph_objects as go
import requests
# ---------------------------------------------------------------------------
# Google Sheets Backend (public sheet, no credentials)
# ---------------------------------------------------------------------------
SHEET_CSV_TMPL = "https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv"
def _get_secret(key, default=""):
"""Read from st.secrets (local/Streamlit Cloud) or env vars (HuggingFace Spaces)."""
try:
return st.secrets.get(key, os.environ.get(key, default))
except FileNotFoundError:
return os.environ.get(key, default)
def _get_sheet_id():
url = _get_secret("sheet_url")
if not url:
return None
parts = url.split("/d/")
if len(parts) < 2:
return None
return parts[1].split("/")[0]
def _get_apps_script_url():
return _get_secret("apps_script_url")
@st.cache_data(ttl=30)
def load_plans() -> dict:
sheet_id = _get_sheet_id()
if not sheet_id:
return {}
try:
csv_url = SHEET_CSV_TMPL.format(sheet_id=sheet_id)
df = pd.read_csv(csv_url)
plans = {}
for _, row in df.iterrows():
try:
data = json.loads(row["data_json"])
plans[row["name"]] = normalize_plan(data)
except (json.JSONDecodeError, KeyError):
continue
return plans
except Exception:
return {}
def save_plan(name: str, data: dict):
url = _get_apps_script_url()
if not url:
raise ValueError("Apps Script URL not configured in secrets")
payload = {
"action": "save",
"name": name,
"author": data.get("author", ""),
"timestamp": data.get("timestamp", ""),
"data_json": json.dumps(data),
}
resp = requests.post(url, json=payload, timeout=15)
if resp.status_code != 200:
raise ValueError(f"Apps Script returned {resp.status_code}")
def delete_plan(name: str):
url = _get_apps_script_url()
if not url:
raise ValueError("Apps Script URL not configured in secrets")
payload = {"action": "delete", "name": name}
resp = requests.post(url, json=payload, timeout=15)
if resp.status_code != 200:
raise ValueError(f"Apps Script returned {resp.status_code}")
def normalize_plan(data):
"""Ensure loaded data works as a plan regardless of version (backward compat)."""
if "version" not in data:
data["version"] = 1
data.setdefault("months_employed", data.get("inputs", {}).get("months_employed", 12))
data.setdefault("attainment_levels", [50, 75, 100, 150, 200])
return data
# ---------------------------------------------------------------------------
# Commission engine
# ---------------------------------------------------------------------------
def calc_commission_attainment(revenue, quota, tiers, retroactive=False):
"""Tiered attainment-based commission.
tiers: list of (upper_attainment_pct | None, rate_pct).
If retroactive=False (marginal): each rate applies only to revenue in that band.
If retroactive=True: the highest tier reached applies to ALL revenue."""
if retroactive:
applicable_rate = tiers[0][1]
for upper_pct, rate in tiers:
if upper_pct is None:
applicable_rate = rate
break
if revenue <= upper_pct * quota / 100:
applicable_rate = rate
break
applicable_rate = rate
last_upper = tiers[-2][0] if tiers[-1][0] is None else tiers[-1][0]
if tiers[-1][0] is None and revenue > last_upper * quota / 100:
applicable_rate = tiers[-1][1]
return revenue * (applicable_rate / 100)
else:
commission = 0.0
prev_boundary = 0.0
for upper_pct, rate in tiers:
if upper_pct is None:
if revenue > prev_boundary * quota / 100:
commission += (revenue - prev_boundary * quota / 100) * (rate / 100)
break
boundary_rev = upper_pct * quota / 100
if revenue <= prev_boundary * quota / 100:
break
taxable = min(revenue, boundary_rev) - (prev_boundary * quota / 100)
if taxable > 0:
commission += taxable * (rate / 100)
prev_boundary = upper_pct
return commission
def calc_commission_deal_rate(deals, deal_rate_tiers, attainment_pct, accel_tiers):
"""Deal-size-based commission with attainment accelerators."""
multiplier = 1.0
for upper_pct, mult in accel_tiers:
if upper_pct is None or attainment_pct <= upper_pct:
multiplier = mult
break
total = 0.0
deal_results = []
for deal in deals:
acv = deal["acv"]
split_pct = deal.get("split_pct", 100) / 100
rate = 0.0
for min_acv, max_acv, r in deal_rate_tiers:
if acv >= min_acv and (max_acv is None or acv <= max_acv):
rate = r / 100
break
payout = acv * rate * multiplier * split_pct
clawback = deal.get("clawback_pct", 0) / 100
net_payout = payout * (1 - clawback)
total += net_payout
deal_results.append({
"Deal": deal.get("name", ""),
"ACV": acv,
"Rate": f"{rate*100:.0f}%",
"Multiplier": f"{multiplier:.1f}x",
"Split": f"{split_pct*100:.0f}%",
"Gross Payout": round(payout, 2),
"Clawback": f"{clawback*100:.0f}%",
"Net Payout": round(net_payout, 2),
})
return total, deal_results
def calc_ramp_adjusted_quota(annual_quota, ramp_pcts, months_employed=12):
monthly_quota = annual_quota / 12
total = 0.0
for m in range(min(months_employed, 12)):
if m < len(ramp_pcts):
total += monthly_quota * (ramp_pcts[m] / 100)
else:
total += monthly_quota
return total
def compute_projection(params, commission_mode, retroactive, attainment_pct, months_employed=12):
"""Compute full results for a plan at a given attainment level."""
annual_quota = params.get("annual_quota", 0)
base_salary = params.get("base_salary", 0)
draw_amount = params.get("draw_amount", 0)
draw_months_val = params.get("draw_months", 0)
draw_recoverable = params.get("draw_recoverable", False)
ramp_pcts = params.get("ramp_pcts", [])
cogs_pct = params.get("cogs_pct", 20.0)
other_cost = params.get("other_cost_per_rep", 0)
effective_quota = calc_ramp_adjusted_quota(annual_quota, ramp_pcts, months_employed)
# Revenue = attainment % of full annual quota (not ramp-adjusted)
actual_revenue = annual_quota * attainment_pct / 100
# Commission
if commission_mode == "Attainment-based rates":
tiers = params.get("commission_tiers", [])
commission = calc_commission_attainment(actual_revenue, annual_quota, tiers, retroactive)
else:
deal_rate_tiers = params.get("deal_rate_tiers", [])
accel_tiers = params.get("accel_tiers", [])
avg_rate = 0.0
for mn, mx, rt in deal_rate_tiers:
if mx is None or actual_revenue / max(1, 12) <= mx:
avg_rate = rt
break
mult = 1.0
for upper, m in accel_tiers:
if upper is None or attainment_pct <= upper:
mult = m
break
commission = actual_revenue * (avg_rate / 100) * mult
# Draw
active_draw_months = min(int(draw_months_val), months_employed)
draw_paid = draw_amount * (active_draw_months / max(int(draw_months_val), 1)) if draw_months_val > 0 else 0
if draw_recoverable:
total_variable = max(commission, draw_paid)
else:
total_variable = commission + draw_paid
prorated_base = base_salary * (months_employed / 12)
total_comp = prorated_base + total_variable
# Company economics
gross_profit = actual_revenue * (1 - cogs_pct / 100)
total_cost_of_rep = total_comp + other_cost * (months_employed / 12)
net_after_rep = gross_profit - total_cost_of_rep
roi_on_rep = (actual_revenue / total_cost_of_rep) if total_cost_of_rep > 0 else 0
return {
"actual_revenue": round(actual_revenue, 2),
"effective_quota": round(effective_quota, 2),
"attainment_pct": round(attainment_pct, 1),
"commission": round(commission, 2),
"draw_paid": round(draw_paid, 2),
"total_variable": round(total_variable, 2),
"total_comp": round(total_comp, 2),
"gross_profit": round(gross_profit, 2),
"total_cost_of_rep": round(total_cost_of_rep, 2),
"net_after_rep": round(net_after_rep, 2),
"roi_on_rep": round(roi_on_rep, 2),
}
# ---------------------------------------------------------------------------
# App
# ---------------------------------------------------------------------------
st.set_page_config(page_title="Sales Comp Plan Builder", layout="wide")
st.title("Sales Comp Plan Builder")
st.markdown("""
Model different compensation plans and compare them side by side.
**How to use:**
1. **Set plan parameters** in the sidebar (base salary, quota, commission structure, ramp, draw, etc.)
2. **Explore what-if scenarios** in the Plan Builder tab with any revenue number
3. **Save the plan** and it auto-generates projections at 75%, 100%, 150%, 200% attainment
4. **Compare plans** side by side in the Compare tab
""")
# Check config
sheet_ok = bool(_get_sheet_id())
script_ok = bool(_get_apps_script_url())
if not sheet_ok or not script_ok:
with st.expander("Admin: backend setup required", expanded=False):
st.warning("Add these to `.streamlit/secrets.toml` (local) or Streamlit Cloud Secrets:")
st.code('''sheet_url = "https://docs.google.com/spreadsheets/d/YOUR_SHEET_ID/edit"
apps_script_url = "https://script.google.com/macros/s/YOUR_SCRIPT_ID/exec"''', language="toml")
st.markdown("""
**Quick setup (5 min):**
1. Create a Google Sheet with headers in row 1: `name | author | timestamp | data_json`
2. Share it as **"Anyone with the link" → Editor**
3. Open **Extensions → Apps Script**, paste the script from `apps_script.js` in this repo
4. Deploy as **Web App** → Execute as **Me** → Access **Anyone**
5. Copy the sheet URL and web app URL into secrets
""")
# ---- Sidebar: Plan Parameters ----
st.sidebar.header("Plan Parameters")
# --- Load a saved plan into the sidebar ---
saved_plans = load_plans() if sheet_ok else {}
load_options = ["— New plan —"] + list(saved_plans.keys())
load_choice = st.sidebar.selectbox("Load a saved plan", load_options, key="load_plan",
help="Select a saved plan to load its parameters into the sidebar for editing")
if load_choice != "— New plan —" and load_choice in saved_plans:
if st.sidebar.button("Load into sidebar"):
plan = saved_plans[load_choice]
p = plan.get("params", {})
# Set session state for all sidebar widgets
st.session_state["base"] = p.get("base_salary", 150_000)
st.session_state["quota"] = p.get("annual_quota", 1_250_000)
st.session_state["draw"] = p.get("draw_amount", 0)
st.session_state["draw_months"] = p.get("draw_months", 12)
st.session_state["draw_rec"] = p.get("draw_recoverable", False)
st.session_state["cogs_pct"] = p.get("cogs_pct", 20.0)
st.session_state["other_cost"] = p.get("other_cost_per_rep", 20_000)
# Commission mode
st.session_state["comm_mode"] = plan.get("commission_mode", "Attainment-based rates")
st.session_state["retroactive"] = plan.get("retroactive", False)
# Ramp
ramp = p.get("ramp_pcts", [])
st.session_state["ramp_months"] = len(ramp)
for i, pct in enumerate(ramp):
st.session_state[f"ramp_{i}"] = int(pct)
# Commission tiers
tiers = p.get("commission_tiers") or []
if tiers:
st.session_state["num_tiers"] = len(tiers)
for i, tier in enumerate(tiers):
if tier[0] is not None:
st.session_state[f"at_u_{i}"] = int(tier[0])
st.session_state[f"at_r_{i}"] = float(tier[1])
# Deal-size tiers
deal_tiers = p.get("deal_rate_tiers") or []
if deal_tiers:
st.session_state["num_deal_tiers"] = len(deal_tiers)
for i, tier in enumerate(deal_tiers):
st.session_state[f"dt_mn_{i}"] = int(tier[0])
if tier[1] is not None:
st.session_state[f"dt_mx_{i}"] = int(tier[1])
st.session_state[f"dt_rt_{i}"] = float(tier[2])
# Accelerators
accels = p.get("accel_tiers") or []
if accels:
st.session_state["num_accels"] = len(accels)
for i, tier in enumerate(accels):
if tier[0] is not None:
st.session_state[f"ac_u_{i}"] = int(tier[0])
st.session_state[f"ac_m_{i}"] = float(tier[1])
# Months employed
st.session_state["months_emp"] = plan.get("months_employed", 12)
# Author
st.session_state["author"] = plan.get("author", "")
st.rerun()
st.sidebar.caption("Adjust these to model different comp plan structures. Changes update results instantly.")
def _default(key, fallback):
"""Return {} if key is already in session_state (widget will use that), else set value=fallback."""
if key in st.session_state:
return {}
return {"value": fallback}
with st.sidebar.expander("Compensation Structure", expanded=True):
base_salary = st.number_input("Base Salary ($)", step=5_000, key="base",
help="Annual base salary before any variable compensation",
**_default("base", 150_000))
annual_quota = st.number_input("Annual Quota ($)", step=50_000, key="quota",
help="Full-year revenue target at 100% attainment",
**_default("quota", 1_250_000))
with st.sidebar.expander("Draw", expanded=False):
st.caption(
"A **draw** is guaranteed cash paid to the rep regardless of deals closed — "
"a safety net while pipeline is still building. "
"**Recoverable** = deducted from future commissions (an advance). "
"**Non-recoverable** = paid on top of whatever they earn."
)
draw_amount = st.number_input("Draw total ($)", step=5_000, key="draw",
help="Total draw amount spread over the draw period",
**_default("draw", 50_000))
draw_months = st.number_input("Draw duration (months)", step=1, key="draw_months",
**_default("draw_months", 12))
draw_recoverable = st.checkbox("Recoverable", key="draw_rec",
help="If recoverable, draw is deducted from earned commissions. If non-recoverable, it's paid on top.",
**_default("draw_rec", False))
st.sidebar.divider()
commission_mode = st.sidebar.radio(
"Commission model",
["Attainment-based rates", "Deal-size rates + accelerators"],
key="comm_mode",
help="**Attainment-based:** Commission rate changes at quota attainment thresholds (e.g. 4% up to 100%, 5% from 100-125%). "
"**Deal-size + accelerators:** Flat commission rate per deal based on ACV size, with a multiplier that kicks in at higher attainment levels.",
)
# -- Attainment-based tiers --
att_tiers = []
deal_rate_tiers = []
accel_tiers = []
avg_rate = 0.0
retroactive_mode = False
if commission_mode == "Attainment-based rates":
with st.sidebar.expander("Commission Tiers (attainment)", expanded=True):
retroactive_mode = st.toggle("Retroactive rates", key="retroactive",
**_default("retroactive", False),
help="**Marginal** (off): each rate applies only to revenue in that band. "
"**Retroactive** (on): once a threshold is crossed, the higher rate applies to ALL revenue from dollar one. "
"Retroactive is much more expensive for the company.")
if retroactive_mode:
st.caption("Retroactive — highest tier reached applies to ALL revenue")
else:
st.caption("Marginal — each rate applies only to revenue in that band")
num_tiers = st.number_input("Number of tiers", 1, 8, key="num_tiers",
**_default("num_tiers", 4))
att_defaults = [(100, 4.0), (125, 5.0), (150, 6.0), (None, 7.0)]
for i in range(int(num_tiers)):
c1, c2 = st.columns(2)
is_last = i == int(num_tiers) - 1
d_upper = att_defaults[i][0] if i < len(att_defaults) and not is_last else None
d_rate = att_defaults[i][1] if i < len(att_defaults) else 5.0
if is_last:
c1.text(f"Tier {i+1}: above prior")
upper = None
else:
upper = c1.number_input(f"Tier {i+1} upper %", step=5, key=f"at_u_{i}",
**_default(f"at_u_{i}", d_upper or 100))
rate = c2.number_input(f"Tier {i+1} rate %", step=0.5, format="%.1f", key=f"at_r_{i}",
**_default(f"at_r_{i}", d_rate))
att_tiers.append((upper, rate))
else:
with st.sidebar.expander("Deal-Size Commission Rates", expanded=True):
num_deal_tiers = st.number_input("Number of deal-size tiers", 1, 6, key="num_deal_tiers",
**_default("num_deal_tiers", 3))
deal_defaults = [(0, 29_999, 20.0), (30_000, 100_000, 40.0), (100_001, None, 40.0)]
for i in range(int(num_deal_tiers)):
c1, c2, c3 = st.columns(3)
d = deal_defaults[i] if i < len(deal_defaults) else (0, None, 40.0)
mn = c1.number_input(f"Tier {i+1} min ACV", step=5_000, key=f"dt_mn_{i}",
**_default(f"dt_mn_{i}", d[0]))
is_last = i == int(num_deal_tiers) - 1
if is_last:
mx = None
c2.text("Uncapped")
else:
mx = c2.number_input(f"Tier {i+1} max ACV", step=5_000, key=f"dt_mx_{i}",
**_default(f"dt_mx_{i}", d[1] or 100_000))
rt = c3.number_input(f"Tier {i+1} rate %", step=1.0, format="%.1f", key=f"dt_rt_{i}",
**_default(f"dt_rt_{i}", d[2]))
deal_rate_tiers.append((mn, mx, rt))
with st.sidebar.expander("Attainment Accelerators", expanded=True):
st.caption("Multiplier applied to deal commission based on annual attainment")
num_accels = st.number_input("Number of accelerator tiers", 1, 6, key="num_accels",
**_default("num_accels", 3))
accel_defaults = [(99, 1.0), (124, 1.3), (None, 1.5)]
for i in range(int(num_accels)):
c1, c2 = st.columns(2)
d = accel_defaults[i] if i < len(accel_defaults) else (None, 1.0)
is_last = i == int(num_accels) - 1
if is_last:
c1.text("Above prior")
upper = None
else:
upper = c1.number_input(f"Accel {i+1} up to %", step=5, key=f"ac_u_{i}",
**_default(f"ac_u_{i}", d[0] or 100))
mult = c2.number_input(f"Accel {i+1} multiplier", step=0.1, format="%.1f", key=f"ac_m_{i}",
**_default(f"ac_m_{i}", d[1]))
accel_tiers.append((upper, mult))
# -- Ramp --
with st.sidebar.expander("Ramp Schedule", expanded=False):
st.caption(
"A **ramp** reduces the rep's quota target during early months — "
"they have a lower bar to hit, making it easier to reach attainment "
"while getting up to speed. Unlike a draw, the rep still has to close "
"deals to earn variable comp. Set each month's quota as a % of full quota."
)
ramp_months = st.number_input("Ramp months", 0, 12, key="ramp_months",
**_default("ramp_months", 9))
ramp_pcts = []
ramp_defaults = [0, 0, 25, 25, 50, 50, 75, 75, 75]
for i in range(int(ramp_months)):
d = ramp_defaults[i] if i < len(ramp_defaults) else 75
pct = st.number_input(f"Month {i+1} quota %", step=5, key=f"ramp_{i}",
**_default(f"ramp_{i}", d))
ramp_pcts.append(pct)
# -- Company economics --
with st.sidebar.expander("Company Economics", expanded=False):
cogs_pct = st.number_input("COGS (% of revenue)", step=5.0, format="%.1f", key="cogs_pct",
**_default("cogs_pct", 20.0))
other_cost_per_rep = st.number_input("Other cost per rep ($)", step=5_000, key="other_cost",
help="Annual cost for benefits, tools, travel, etc. — pro-rated if less than 12 months",
**_default("other_cost", 20_000))
# -- Projection settings --
with st.sidebar.expander("Projection Settings", expanded=False):
st.caption("Attainment levels used when auto-generating plan projections.")
attainment_str = st.text_input("Attainment levels (%)", key="att_levels",
**_default("att_levels", "50, 75, 100, 150, 200"))
attainment_levels = [int(x.strip()) for x in attainment_str.split(",") if x.strip().isdigit()]
if not attainment_levels:
attainment_levels = [50, 75, 100, 150, 200]
# ---- Main tabs (deeplink via ?tab=builder|deals|compare) ----
TAB_KEYS = ["builder", "deals", "compare"]
TAB_LABELS = ["1. Plan Builder", "2. Per-Deal Calculator", "3. Compare Plans"]
TAB_MAP = dict(zip(TAB_KEYS, TAB_LABELS))
qp = st.query_params
initial_tab = qp.get("tab", "builder")
# backward compat for old ?tab=scenario links
if initial_tab == "scenario":
initial_tab = "builder"
if initial_tab not in TAB_KEYS:
initial_tab = "builder"
active_tab = st.radio(
"Navigate",
TAB_KEYS,
index=TAB_KEYS.index(initial_tab),
format_func=lambda k: TAB_MAP[k],
horizontal=True,
key="active_tab",
label_visibility="collapsed",
)
st.query_params["tab"] = active_tab
# ===================== TAB 1: Plan Builder =====================
if active_tab == "builder":
st.caption("Configure the plan in the sidebar, then explore any revenue number below. Save the plan to auto-generate projections.")
col_in, col_out = st.columns([1, 1.5])
with col_in:
st.subheader("What-If Calculator")
author = st.text_input("Plan author", key="author",
placeholder="e.g. 'Founder', 'VP Sales'",
help="A generic label for who created this plan — avoid real names")
months_employed = st.slider("Months in plan year", 1, 12, key="months_emp",
help="Set to less than 12 for mid-year hires — ramp schedule adjusts the quota automatically",
**_default("months_emp", 12))
effective_quota = calc_ramp_adjusted_quota(annual_quota, ramp_pcts, months_employed)
st.metric("Effective Quota (ramp-adjusted)", f"${effective_quota:,.0f}",
help="Annual quota reduced by the ramp schedule for months where quota is below 100%")
actual_revenue = st.number_input("Total Revenue Closed ($)", step=50_000, key="rev",
help="Actual or projected closed revenue for the period",
**_default("rev", 1_250_000))
attainment_pct = (actual_revenue / effective_quota * 100) if effective_quota > 0 else 0
# Commission uses full annual quota for tier boundaries
commission_quota = annual_quota
# --- Commission calc ---
if commission_mode == "Attainment-based rates":
commission = calc_commission_attainment(actual_revenue, commission_quota, att_tiers, retroactive_mode)
else:
for mn, mx, rt in deal_rate_tiers:
if mx is None or actual_revenue / max(1, 12) <= mx:
avg_rate = rt
break
mult = 1.0
for upper, m in accel_tiers:
if upper is None or attainment_pct <= upper:
mult = m
break
commission = actual_revenue * (avg_rate / 100) * mult
# --- Draw ---
active_draw_months = min(int(draw_months), months_employed)
draw_paid = draw_amount * (active_draw_months / max(int(draw_months), 1))
if draw_recoverable:
total_variable = max(commission, draw_paid)
else:
total_variable = commission + draw_paid
prorated_base = base_salary * (months_employed / 12)
total_comp = prorated_base + total_variable
# Company economics
gross_profit = actual_revenue * (1 - cogs_pct / 100)
total_cost_of_rep = total_comp + other_cost_per_rep * (months_employed / 12)
net_after_rep = gross_profit - total_cost_of_rep
roi_on_rep = (actual_revenue / total_cost_of_rep) if total_cost_of_rep > 0 else 0
with col_out:
st.subheader("Results")
st.markdown("**What the seller earns**")
m1, m2, m3 = st.columns(3)
m1.metric("Quota Attainment", f"{attainment_pct:.1f}%",
help="Revenue closed / effective quota")
m2.metric("Commission Earned", f"${commission:,.0f}",
help="Variable pay from the commission structure")
m3.metric("Total Compensation", f"${total_comp:,.0f}",
help="Base + draw + commission = total cash to the seller")
r1, r2, r3 = st.columns(3)
r1.metric("Base Salary", f"${prorated_base:,.0f}",
help="Pro-rated if less than 12 months")
r2.metric("Draw Paid", f"${draw_paid:,.0f}",
help="Guaranteed draw pro-rated for months employed")
r3.metric("Total Variable", f"${total_variable:,.0f}",
help="Commission + draw (or the greater of the two if recoverable)")
st.markdown("**What it costs the company**")
c1, c2, c3, c4 = st.columns(4)
c1.metric("Revenue", f"${actual_revenue:,.0f}")
c2.metric("COGS", f"${actual_revenue * cogs_pct / 100:,.0f}",
help="Cost of goods sold — set the % in sidebar")
c3.metric("Gross Profit", f"${gross_profit:,.0f}",
help="Revenue minus COGS")
c4.metric("Net After Rep Cost", f"${net_after_rep:,.0f}",
help="Gross profit minus total cost of the rep (comp + overhead)")
d1, d2, d3 = st.columns(3)
d1.metric("Total Rep Cost", f"${total_cost_of_rep:,.0f}",
help="Total comp + benefits/tools/travel overhead")
d2.metric("Rep Cost as % of Revenue", f"{total_cost_of_rep / actual_revenue * 100:.1f}%" if actual_revenue > 0 else "N/A",
help="How much of each revenue dollar goes to the rep")
d3.metric("Revenue ROI on Rep", f"{roi_on_rep:.1f}x",
help="Revenue generated per dollar spent on the rep")
st.markdown("**Commission Curve**")
st.caption("How commission scales with attainment — the red dot is your current what-if.")
rev_pts = [commission_quota * x / 100 for x in range(0, 201, 5)]
if commission_mode == "Attainment-based rates":
comm_pts = [calc_commission_attainment(r, commission_quota, att_tiers, retroactive_mode) for r in rev_pts]
else:
comm_pts = []
for r in rev_pts:
att = (r / effective_quota * 100) if effective_quota > 0 else 0
m_ = 1.0
for up, ml in accel_tiers:
if up is None or att <= up:
m_ = ml
break
comm_pts.append(r * (avg_rate / 100) * m_)
att_pts = [r / effective_quota * 100 if effective_quota > 0 else 0 for r in rev_pts]
total_comp_pts = [prorated_base + draw_paid + c for c in comm_pts]
fig = go.Figure()
fig.add_trace(go.Scatter(x=att_pts, y=comm_pts, mode="lines", name="Commission",
line=dict(color="#2563eb", width=3)))
fig.add_trace(go.Scatter(x=att_pts, y=total_comp_pts, mode="lines", name="Total Comp",
line=dict(color="#16a34a", width=2, dash="dot")))
fig.add_trace(go.Scatter(x=[attainment_pct], y=[commission], mode="markers", name="You",
marker=dict(size=12, color="#dc2626")))
fig.update_layout(xaxis_title="Quota Attainment %", yaxis_title="$",
height=350, margin=dict(l=0, r=0, t=30, b=0))
st.plotly_chart(fig, use_container_width=True)
# --- Live projections table ---
st.divider()
st.subheader("Plan Projections")
st.caption("Auto-generated from current sidebar settings. Updates live as you change parameters.")
current_params = {
"base_salary": base_salary, "annual_quota": annual_quota,
"draw_amount": draw_amount, "draw_months": int(draw_months),
"draw_recoverable": draw_recoverable, "ramp_pcts": ramp_pcts,
"cogs_pct": cogs_pct, "other_cost_per_rep": other_cost_per_rep,
"commission_tiers": att_tiers if commission_mode == "Attainment-based rates" else None,
"deal_rate_tiers": deal_rate_tiers if commission_mode != "Attainment-based rates" else None,
"accel_tiers": accel_tiers if commission_mode != "Attainment-based rates" else None,
}
proj_rows = []
for level in attainment_levels:
proj = compute_projection(current_params, commission_mode, retroactive_mode, level, months_employed)
proj_rows.append({
"Attainment": f"{level}%",
"Revenue": f"${proj['actual_revenue']:,.0f}",
"Base Salary": f"${base_salary * (months_employed / 12):,.0f}",
"Commission": f"${proj['commission']:,.0f}",
"Draw": f"${proj['draw_paid']:,.0f}",
"Total Comp": f"${proj['total_comp']:,.0f}",
"Gross Profit": f"${proj['gross_profit']:,.0f}",
"Net After Rep": f"${proj['net_after_rep']:,.0f}",
"ROI": f"{proj['roi_on_rep']:.1f}x",
})
st.dataframe(pd.DataFrame(proj_rows), use_container_width=True, hide_index=True)
# Live agreement preview
with st.expander("Agreement Preview", expanded=False):
prev_lines = []
prev_lines.append("SALES COMPENSATION PLAN")
prev_lines.append("=" * 60)
prev_lines.append("")
proj_100 = compute_projection(current_params, commission_mode, retroactive_mode, 100, months_employed)
prev_lines.append(f" ${base_salary:,.0f}".ljust(22) + f"~${proj_100['total_comp']:,.0f}".ljust(22))
prev_lines.append(" Base Salary".ljust(22) + "OTE".ljust(22))
prev_lines.append("")
prev_lines.append("1. COMPENSATION OVERVIEW")
prev_lines.append("")
prev_lines.append(f" Base Salary: ${base_salary:,.0f} / year paid semi-monthly")
if draw_amount > 0:
rec_lbl = "recoverable" if draw_recoverable else "non-recoverable"
prev_lines.append(f" Draw: ${draw_amount:,.0f} {rec_lbl} over {int(draw_months)} months (~${draw_amount / max(int(draw_months), 1):,.0f}/mo)")
prev_lines.append(f" OTE: ${proj_100['total_comp']:,.0f} (base + variable at 100% attainment)")
prev_lines.append(f" Commissions are uncapped.")
prev_lines.append("")
prev_lines.append("2. COMMISSION STRUCTURE")
prev_lines.append("")
if commission_mode == "Attainment-based rates" and att_tiers:
if retroactive_mode:
prev_lines.append(" Retroactive — highest tier reached applies to ALL revenue.")
else:
prev_lines.append(" Marginal — each rate applies only to revenue in that band.")
prev_lines.append("")
prev_lines.append(f" {'Attainment Level':<24} {'Commission Rate':<18}")
prev_lines.append(f" {'-' * 22:<24} {'-' * 16:<18}")
for i, tier in enumerate(att_tiers):
upper_val, rate_val = tier[0], tier[1]
if upper_val is None:
prev_upper = int(att_tiers[i-1][0])
prev_lines.append(f" {prev_upper}%+{'':<19} {rate_val:.1f}%")
elif i == 0:
prev_lines.append(f" 0% – {int(upper_val)}%{'':<14} {rate_val:.1f}%")
else:
prev_upper = int(att_tiers[i-1][0])
prev_lines.append(f" {prev_upper}% – {int(upper_val)}%{'':<12} {rate_val:.1f}%")
prev_lines.append("")
ramp_list_preview = ramp_pcts
if ramp_list_preview:
prev_lines.append("3. QUOTA RAMP SCHEDULE")
prev_lines.append("")
monthly_q = annual_quota / 12
ramp_groups_p = []
idx_p = 0
while idx_p < len(ramp_list_preview):
pct_p = ramp_list_preview[idx_p]
start_p = idx_p + 1
while idx_p + 1 < len(ramp_list_preview) and ramp_list_preview[idx_p + 1] == pct_p:
idx_p += 1
end_p = idx_p + 1
ramp_groups_p.append((start_p, end_p, pct_p))
idx_p += 1
for start_p, end_p, pct_p in ramp_groups_p:
ml = f"{start_p}–{end_p}" if start_p != end_p else str(start_p)
tgt = monthly_q * pct_p / 100
prev_lines.append(f" {ml:<10} {int(pct_p)}% quota ${tgt:,.0f}/mo")
if len(ramp_list_preview) < 12:
prev_lines.append(f" {len(ramp_list_preview)+1}–12 100% quota ${monthly_q:,.0f}/mo")
prev_lines.append("")
section_n = 4
else:
section_n = 3
prev_lines.append(f"{section_n}. ILLUSTRATIVE EARNINGS SCENARIOS")
prev_lines.append("")
prev_lines.append(f" {'Attainment':<14} {'Revenue':<16} {'Commission':<16} {'Total Comp':<16} {'Net After Rep'}")
prev_lines.append(f" {'-'*12:<14} {'-'*14:<16} {'-'*14:<16} {'-'*14:<16} {'-'*14}")
for level in attainment_levels:
proj = compute_projection(current_params, commission_mode, retroactive_mode, level, months_employed)
prev_lines.append(f" {level}%{'':<10} ${proj['actual_revenue']:,.0f}{'':<4} ${proj['commission']:,.0f}{'':<6} ${proj['total_comp']:,.0f}{'':<6} ${proj['net_after_rep']:,.0f}")
st.code("\n".join(prev_lines), language=None)
# --- Save plan ---
st.divider()
st.subheader("Save This Plan")
st.caption("Save the plan configuration. Projections at each attainment level are generated automatically.")
# Build plan data (config only, no baked-in results)
plan_data = {
"version": 2,
"author": author,
"timestamp": datetime.datetime.now().isoformat(),
"commission_mode": commission_mode,
"retroactive": retroactive_mode,
"months_employed": months_employed,
"attainment_levels": attainment_levels,
"params": {
"base_salary": base_salary, "annual_quota": annual_quota,
"draw_amount": draw_amount,
"draw_months": int(draw_months), "draw_recoverable": draw_recoverable,
"ramp_pcts": ramp_pcts, "cogs_pct": cogs_pct,
"other_cost_per_rep": other_cost_per_rep,
"commission_tiers": att_tiers if commission_mode == "Attainment-based rates" else None,
"deal_rate_tiers": deal_rate_tiers if commission_mode != "Attainment-based rates" else None,
"accel_tiers": accel_tiers if commission_mode != "Attainment-based rates" else None,
},
}
st.warning(
"**Privacy:** Saved plans are stored in a shared Google Sheet. "
"Do NOT use real names, company names, or any identifying information "
"in plan names or the author field. Use generic labels "
"(e.g. 'Plan A - aggressive', 'Option 2 - conservative').",
icon="🔒",
)
scol1, scol2 = st.columns(2)
with scol1:
plan_name = st.text_input("Plan name", key="save_name",
placeholder="e.g. 'plan-a-aggressive'")
if st.button("Save Plan", type="primary"):
if plan_name.strip():
try:
save_plan(plan_name.strip(), plan_data)
st.success(f"Saved '{plan_name.strip()}'")
load_plans.clear()
st.rerun()
except Exception as e:
st.error(f"Failed to save: {e}")
else:
st.warning("Enter a plan name")
# ===================== TAB 2: Per-Deal Calculator =====================
if active_tab == "deals":
st.subheader("Per-Deal Payout Calculator")
st.caption("See exactly what the seller earns on each individual deal. "
"Useful for modeling specific pipeline deals or understanding payout ranges by deal size.")
if commission_mode == "Attainment-based rates":
st.info("This tab requires **Deal-size rates + accelerators** mode. "
"Switch the commission model in the sidebar to enable it.")
else:
current_attainment = st.number_input("Current annual attainment %", value=100.0, step=5.0,
key="deal_attainment",
help="Determines which accelerator multiplier applies — "
"e.g. above 100% attainment, deals may pay at 1.3x")
st.markdown("**Enter deals:**")
num_deals = st.number_input("Number of deals", 1, 50, 3, key="num_deals")
deals = []
for i in range(int(num_deals)):
with st.expander(f"Deal {i+1}", expanded=(i < 3)):
dc1, dc2, dc3, dc4 = st.columns(4)
name = dc1.text_input("Name", value=f"Deal {i+1}", key=f"deal_name_{i}")
acv = dc2.number_input("ACV ($)", value=60_000, step=5_000, key=f"deal_acv_{i}")
split = dc3.number_input("Your split %", value=100, step=10, key=f"deal_split_{i}")
claw = dc4.number_input("Clawback %", value=0, step=10, key=f"deal_claw_{i}",
help="% clawed back (e.g. 90-day churn)")
deals.append({"name": name, "acv": acv, "split_pct": split, "clawback_pct": claw})
total_deal_comm, deal_details = calc_commission_deal_rate(
deals, deal_rate_tiers, current_attainment, accel_tiers
)
st.markdown("**Deal Payouts**")
st.dataframe(pd.DataFrame(deal_details), use_container_width=True, hide_index=True)
st.metric("Total Commission from Deals", f"${total_deal_comm:,.0f}")
# ===================== TAB 3: Compare Plans =====================
if active_tab == "compare":
st.subheader("Compare Plans")
st.caption("Each plan auto-generates projections at multiple attainment levels. "
"Compare different plan structures to see how they perform across scenarios.")
if not sheet_ok:
st.warning("Configure your Google Sheet URL in secrets to enable plan saving.")
else:
if st.button("Refresh from Google Sheets"):
load_plans.clear()
st.rerun()
plans = load_plans()
if plans:
col_a, col_b = st.columns(2)
with col_b:
to_delete = st.selectbox("Delete a plan", [""] + list(plans.keys()), key="del_sel")
if st.button("Delete"):
if to_delete:
try:
delete_plan(to_delete)
load_plans.clear()
st.success(f"Deleted '{to_delete}'")
st.rerun()
except Exception as e:
st.error(f"Failed to delete: {e}")
all_names = list(plans.keys())
tc1, tc2 = st.columns([3, 1])
with tc2:
if st.button("Clear all"):
st.session_state["compare_sel"] = []
st.rerun()
if st.button("Select all"):
st.session_state["compare_sel"] = all_names
st.rerun()
with tc1:
selected = st.multiselect("Filter plans", all_names,
default=all_names, key="compare_sel")
if selected:
# Build comparison table with projections at each attainment level
rows = []
for name in selected:
plan = plans[name]
p = plan.get("params", {})
months = plan.get("months_employed", 12)
levels = plan.get("attainment_levels", [50, 75, 100, 150, 200])
retro = plan.get("retroactive", False)
mode = plan.get("commission_mode", "Attainment-based rates")
row = {
"Plan": name,
"Author": plan.get("author", ""),
"Mode": mode + (" (retro)" if retro else ""),
"Base": f"${p.get('base_salary', 0):,.0f}",
"Quota": f"${p.get('annual_quota', 0):,.0f}",
}
for level in levels:
proj = compute_projection(p, mode, retro, level, months)
row[f"{level}% Comm"] = f"${proj['commission']:,.0f}"
row[f"{level}% Total"] = f"${proj['total_comp']:,.0f}"
row[f"{level}% Net"] = f"${proj['net_after_rep']:,.0f}"
rows.append(row)
st.dataframe(pd.DataFrame(rows), use_container_width=True, hide_index=True)
# Chart: total comp at each attainment level per plan
st.markdown("**Total Compensation by Attainment**")
fig = go.Figure()
# Use the union of all attainment levels across selected plans
all_levels = sorted(set(
lvl for name in selected
for lvl in plans[name].get("attainment_levels", [50, 75, 100, 150, 200])
))
for name in selected:
plan = plans[name]
p = plan.get("params", {})
months = plan.get("months_employed", 12)
retro = plan.get("retroactive", False)
mode = plan.get("commission_mode", "Attainment-based rates")
comps = []
for level in all_levels:
proj = compute_projection(p, mode, retro, level, months)
comps.append(proj["total_comp"])
fig.add_trace(go.Bar(
name=name,
x=[f"{l}%" for l in all_levels],
y=comps,
))
fig.update_layout(barmode="group", height=400,
xaxis_title="Attainment", yaxis_title="Total Comp ($)",
margin=dict(l=0, r=0, t=30, b=0))
st.plotly_chart(fig, use_container_width=True)
# Net after rep chart
st.markdown("**Net After Rep Cost by Attainment**")
fig2 = go.Figure()
for name in selected:
plan = plans[name]
p = plan.get("params", {})
months = plan.get("months_employed", 12)
retro = plan.get("retroactive", False)
mode = plan.get("commission_mode", "Attainment-based rates")
nets = []
for level in all_levels:
proj = compute_projection(p, mode, retro, level, months)
nets.append(proj["net_after_rep"])
fig2.add_trace(go.Bar(
name=name,
x=[f"{l}%" for l in all_levels],
y=nets,
))
fig2.update_layout(barmode="group", height=400,
xaxis_title="Attainment", yaxis_title="Net After Rep ($)",
margin=dict(l=0, r=0, t=30, b=0))
st.plotly_chart(fig2, use_container_width=True)
# --- Plan detail view ---
st.divider()
st.markdown("**Plan Details**")
st.caption("Select a plan to view agreement-ready compensation terms.")
detail_name = st.selectbox("View details for", [""] + selected, key="detail_sel")
if detail_name and detail_name in plans:
s = plans[detail_name]
p = s.get("params", {})
months = s.get("months_employed", 12)
retro = s.get("retroactive", False)
mode = s.get("commission_mode", "Attainment-based rates")
levels = s.get("attainment_levels", [50, 75, 100, 150, 200])
# Compute 100% projection for OTE reference
proj_100 = compute_projection(p, mode, retro, 100, months)
# Build agreement text
lines = []
deal_types = p.get("deal_types")
illustrative = p.get("illustrative_scenarios")
policies = p.get("policies")
equity = p.get("equity")
lines.append("SALES COMPENSATION PLAN")
lines.append("=" * 60)
lines.append("")
# Header summary
lines.append(f" ${p.get('base_salary', 0):,.0f}".ljust(22) + f"~${proj_100['total_comp']:,.0f}".ljust(22))
lines.append(" Base Salary".ljust(22) + "OTE".ljust(22))
draw_amt = p.get("draw_amount", 0)
if draw_amt > 0 or equity:
line_l = f" ${draw_amt:,.0f}" if draw_amt > 0 else ""
line_r = f" {equity.get('pct', '')}%" if equity else ""
lines.append(line_l.ljust(22) + line_r.ljust(22))
line_l2 = f" Draw ({p.get('draw_months', 0)} mo.)" if draw_amt > 0 else ""
line_r2 = f" Equity (Options)" if equity else ""
lines.append(line_l2.ljust(22) + line_r2.ljust(22))
lines.append("")
# 1. Compensation Overview
lines.append("1. COMPENSATION OVERVIEW")
lines.append("")
lines.append(" Base Salary")
lines.append(f" • ${p.get('base_salary', 0):,.0f} / year paid semi-monthly")
lines.append(f" • Full benefits eligibility from day 1")
lines.append("")
if draw_amt > 0:
draw_mo = p.get("draw_months", 0)
rec_label = "recoverable" if p.get("draw_recoverable", False) else "non-recoverable"
monthly_draw = draw_amt / max(draw_mo, 1)
lines.append(" Signing Draw")
lines.append(f" • ${draw_amt:,.0f} {rec_label} draw")
lines.append(f" • Paid over {draw_mo} months in equal installments ~${monthly_draw:,.0f}/mo.")
if not p.get("draw_recoverable", False):
lines.append(f" • Not subject to clawback — protects ramp period")
lines.append("")
if equity:
lines.append(" Equity Grant")
lines.append(f" • {equity.get('pct', '')}% of company in stock options")
lines.append(f" • {equity.get('vesting', '4-year vest with 1-year cliff')}")
lines.append(f" • Strike price = FMV at grant date")
lines.append("")
lines.append(" On-Target Earnings (OTE)")
lines.append(f" • ${p.get('base_salary', 0):,.0f} base + ~${proj_100['commission']:,.0f} variable = ~${proj_100['total_comp']:,.0f} OTE")
lines.append(f" • Uncapped — no ceiling on commissions")
lines.append("")
# 2. Commission Structure
lines.append("2. COMMISSION STRUCTURE")
lines.append("")
comm_tiers = p.get("commission_tiers")
deal_tiers_data = p.get("deal_rate_tiers")
accel_t = p.get("accel_tiers")
if deal_types:
lines.append(" Commission is paid on all closed-won deals. Rates vary by deal type:")
lines.append("")
lines.append(f" {'Deal Type':<14} {'ACV Range':<22} {'Rate':<10} {'Per-Deal Range':<20} {'Notes'}")
lines.append(f" {'-'*13:<14} {'-'*20:<22} {'-'*8:<10} {'-'*18:<20} {'-'*20}")
for dt in deal_types:
acv_range = f"${dt['acv_min']:,.0f} – ${dt['acv_max']:,.0f}" if dt.get('acv_max') else f"${dt['acv_min']:,.0f}+"
payout_lo = dt['acv_min'] * dt['rate'] / 100
payout_hi = (dt.get('acv_max', dt['acv_min']) * dt['rate'] / 100) if dt.get('acv_max') else 0
payout_range = f"${payout_lo:,.0f} – ${payout_hi:,.0f}" if payout_hi else f"${payout_lo:,.0f}+"
lines.append(f" {dt['name']:<14} {acv_range:<22} {dt['rate']:.0f}%{'':<7} {payout_range:<20} {dt.get('notes', '')}")
lines.append("")
lines.append(" Timing: Commissions earned upon fully-executed contract and first invoice")
lines.append(" issued. Paid on the first payroll cycle of the following month.")
lines.append(" Churn within 90 days triggers a proportional clawback.")
elif comm_tiers:
is_retro = retro
if is_retro:
lines.append(" Commission rates are applied retroactively. Once a higher attainment")
lines.append(" threshold is crossed, that rate applies to ALL revenue from dollar one.")
else:
lines.append(" Commission rates are applied on a marginal basis. Each rate applies")
lines.append(" only to revenue earned within that attainment band.")
lines.append("")
lines.append(f" {'Attainment Level':<24} {'Commission Rate':<18}")
lines.append(f" {'-' * 22:<24} {'-' * 16:<18}")
for i, tier in enumerate(comm_tiers):
upper_val, rate_val = tier[0], tier[1]
if upper_val is None:
prev_upper = int(comm_tiers[i-1][0])
lines.append(f" {prev_upper}%+{'':<19} {rate_val:.1f}%")
elif i == 0:
lines.append(f" 0% – {int(upper_val)}%{'':<14} {rate_val:.1f}%")
else:
prev_upper = int(comm_tiers[i-1][0])
lines.append(f" {prev_upper}% – {int(upper_val)}%{'':<12} {rate_val:.1f}%")
elif deal_tiers_data:
lines.append(" Commission is calculated as a percentage of deal ACV based on deal size.")
lines.append("")
lines.append(f" {'Deal ACV Range':<28} {'Commission Rate':<18}")
lines.append(f" {'-' * 26:<28} {'-' * 16:<18}")
for tier in deal_tiers_data:
mn_v, mx_v, rt_v = tier[0], tier[1], tier[2]
if mx_v is None:
lines.append(f" ${mn_v:,.0f}+{'':<19} {rt_v:.1f}%")
else:
lines.append(f" ${mn_v:,.0f} – ${mx_v:,.0f}{'':<8} {rt_v:.1f}%")
lines.append("")
# Deal Targets (if present in legacy data)
deal_targets = p.get("deal_targets")
section_num = 3
if deal_targets:
lines.append(f"{section_num}. ANNUAL QUOTA & DEAL TARGETS")
lines.append("")
lines.append(f" On-target quota is ${p.get('annual_quota', 0):,.0f} ACV.")
lines.append("")
lines.append(f" {'Segment':<14} {'# Deals':<10} {'Avg ACV':<14} {'Total ACV':<14} {'Rate':<8} {'Commission'}")
lines.append(f" {'-'*13:<14} {'-'*8:<10} {'-'*12:<14} {'-'*12:<14} {'-'*6:<8} {'-'*12}")
total_deals = 0
total_acv = 0
total_comm_dt = 0
for dt in deal_targets:
t_acv = dt['num_deals'] * dt['avg_acv']
t_comm = t_acv * dt['rate'] / 100
total_deals += dt['num_deals']
total_acv += t_acv
total_comm_dt += t_comm
lines.append(f" {dt['segment']:<14} {dt['num_deals']:<10} ${dt['avg_acv']:,.0f}{'':<6} ${t_acv:,.0f}{'':<6} {dt['rate']:.0f}%{'':<5} ${t_comm:,.0f}")
lines.append(f" {'Total':<14} {total_deals:<10} {'—':<14} ${total_acv:,.0f}{'':<6} {'—':<8} ~${total_comm_dt:,.0f}")
lines.append("")
section_num += 1
# Ramp
ramp_list = p.get("ramp_pcts", [])
if ramp_list:
lines.append(f"{section_num}. QUOTA RAMP SCHEDULE")
lines.append("")
lines.append(f" Commission rates remain constant throughout the ramp. Only the quota")
lines.append(f" hurdle changes, giving time to build pipeline without sacrificing")
lines.append(f" earnings on early deals closed.")
lines.append("")
monthly_quota = p.get('annual_quota', 0) / 12
lines.append(f" {'Month':<10} {'Quota %':<12} {'Monthly Target':<18} {'Ann. Run Rate':<16} {'Notes'}")
lines.append(f" {'-'*8:<10} {'-'*10:<12} {'-'*16:<18} {'-'*14:<16} {'-'*20}")
ramp_groups = []
idx = 0
while idx < len(ramp_list):
pct_val = ramp_list[idx]
start = idx + 1
while idx + 1 < len(ramp_list) and ramp_list[idx + 1] == pct_val:
idx += 1
end = idx + 1
ramp_groups.append((start, end, pct_val))
idx += 1
ramp_notes = {0: "Onboarding, no quota", 25: "First demos, early pipeline",
50: "Close first deals", 75: "Full funnel operating", 100: "Full quota in effect"}
for start, end, pct_val in ramp_groups:
month_label = f"{start}–{end}" if start != end else str(start)
target = monthly_quota * pct_val / 100
run_rate = target * 12
note = ramp_notes.get(int(pct_val), "")
lines.append(f" {month_label:<10} {int(pct_val)}%{'':<9} ${target:,.0f}{'':<8} ${run_rate:,.0f}{'':<6} {note}")
if len(ramp_list) < 12:
month_label = f"{len(ramp_list)+1}–12"
lines.append(f" {month_label:<10} 100%{'':<8} ${monthly_quota:,.0f}{'':<8} ${monthly_quota*12:,.0f}{'':<6} Full quota in effect")
lines.append("")
section_num += 1
# Accelerators (for deal-size mode)
if accel_t:
lines.append(f"{section_num}. ACCELERATORS & OVERACHIEVEMENT")
lines.append("")
lines.append(f" {'Attainment':<18} {'Rate / Multiplier':<22} {'Notes'}")
lines.append(f" {'-'*16:<18} {'-'*20:<22} {'-'*20}")
for i, tier in enumerate(accel_t):
upper_val, mult_val = tier[0], tier[1]
if upper_val is None:
prev_upper = int(accel_t[i-1][0])
lines.append(f" {prev_upper}%+{'':<14} {mult_val:.1f}x multiplier")
elif i == 0:
lines.append(f" 0% – {int(upper_val)}%{'':<9} {mult_val:.1f}x (base rate)")
else:
prev_upper = int(accel_t[i-1][0])
lines.append(f" {prev_upper}% – {int(upper_val)}%{'':<7} {mult_val:.1f}x multiplier")
lines.append("")
section_num += 1
# Illustrative earnings — auto-generated from projections
lines.append(f"{section_num}. ILLUSTRATIVE EARNINGS SCENARIOS")
lines.append("")
if illustrative:
lines.append(f" {'Scenario':<22} {'Deal Mix':<20} {'Total ACV':<14} {'Commission':<14} {'Total Cash':<14} {'Notes'}")
lines.append(f" {'-'*20:<22} {'-'*18:<20} {'-'*12:<14} {'-'*12:<14} {'-'*12:<14} {'-'*20}")
for sc in illustrative:
lines.append(f" {sc['label']:<22} {sc.get('deal_mix', '—'):<20} ${sc['acv']:,.0f}{'':<4} ${sc['commission']:,.0f}{'':<4} ${sc['total_cash']:,.0f}{'':<4} {sc.get('notes', '')}")
else:
lines.append(f" {'Attainment':<16} {'Revenue':<16} {'Commission':<16} {'Total Comp':<16} {'Net After Rep'}")
lines.append(f" {'-'*14:<16} {'-'*14:<16} {'-'*14:<16} {'-'*14:<16} {'-'*14}")
for level in levels:
proj = compute_projection(p, mode, retro, level, months)
lines.append(f" {level}%{'':<12} ${proj['actual_revenue']:,.0f}{'':<4} ${proj['commission']:,.0f}{'':<6} ${proj['total_comp']:,.0f}{'':<6} ${proj['net_after_rep']:,.0f}")
lines.append("")
section_num += 1
# Policies
lines.append(f"{section_num}. KEY POLICIES & TERMS")
lines.append("")
if policies:
for key, val in policies.items():
lines.append(f" {key:<24} {val}")
else:
lines.append(" Commission Earned Upon fully-executed contract and recognized revenue.")
lines.append(" Commission Paid First payroll cycle following the month of close.")
lines.append(" Clawback Proportional if customer churns within 90 days.")
lines.append(" Split Deals Agreed upfront in writing; default 50/50.")
lines.append(" Plan Changes Company may update at each FY with 30 days notice.")
if draw_amt > 0:
lines.append(f" Draw Period {p.get('draw_months', 0)} months from start. Ceases if employment ends.")
if equity:
lines.append(f" Equity Vesting {equity.get('vesting', '4-year vest, 1-year cliff')}.")
lines.append(" Territory As assigned by Company. May be refined as team grows.")
lines.append("")
section_num += 1
# Acknowledgment
lines.append(f"{section_num}. ACKNOWLEDGMENT & ACCEPTANCE")
lines.append("")
lines.append(" By signing below, both parties agree to the terms of this")
lines.append(" Sales Compensation Plan.")
lines.append("")
lines.append(" ________________________________________")
lines.append(" Account Executive Signature Date")
lines.append("")
lines.append(" ________________________________________")
lines.append(" Authorized Signatory Date")
agreement_text = "\n".join(lines)
st.code(agreement_text, language=None)
st.download_button(
label="Download as text file",
data=agreement_text,
file_name=f"comp-plan-{detail_name.replace(' ', '-').lower()}.txt",
mime="text/plain",
)
else:
st.info("No saved plans yet. Save one from the Plan Builder tab.")
import streamlit as st
import json
import datetime
import os
import pandas as pd
import plotly.graph_objects as go
import requests
# ---------------------------------------------------------------------------
# Google Sheets Backend (public sheet, no credentials)
# ---------------------------------------------------------------------------
SHEET_CSV_TMPL = "https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv"
def _get_secret(key, default=""):
"""Read from st.secrets (local/Streamlit Cloud) or env vars (HuggingFace Spaces)."""
try:
return st.secrets.get(key, os.environ.get(key, default))
except FileNotFoundError:
return os.environ.get(key, default)
def _get_sheet_id():
url = _get_secret("sheet_url")
if not url:
return None
parts = url.split("/d/")
if len(parts) < 2:
return None
return parts[1].split("/")[0]
def _get_apps_script_url():
return _get_secret("apps_script_url")
def load_plans() -> dict:
sheet_id = _get_sheet_id()
if not sheet_id:
return {}
try:
csv_url = SHEET_CSV_TMPL.format(sheet_id=sheet_id)
df = pd.read_csv(csv_url)
plans = {}
for _, row in df.iterrows():
try:
data = json.loads(row["data_json"])
plans[row["name"]] = normalize_plan(data)
except (json.JSONDecodeError, KeyError):
continue
return plans
except Exception:
return {}
def save_plan(name: str, data: dict):
url = _get_apps_script_url()
if not url:
raise ValueError("Apps Script URL not configured in secrets")
payload = {
"action": "save",
"name": name,
"author": data.get("author", ""),
"timestamp": data.get("timestamp", ""),
"data_json": json.dumps(data),
}
resp = requests.post(url, json=payload, timeout=15)
if resp.status_code != 200:
raise ValueError(f"Apps Script returned {resp.status_code}")
def delete_plan(name: str):
url = _get_apps_script_url()
if not url:
raise ValueError("Apps Script URL not configured in secrets")
payload = {"action": "delete", "name": name}
resp = requests.post(url, json=payload, timeout=15)
if resp.status_code != 200:
raise ValueError(f"Apps Script returned {resp.status_code}")
def normalize_plan(data):
"""Ensure loaded data works as a plan regardless of version (backward compat)."""
if "version" not in data:
data["version"] = 1
data.setdefault("months_employed", data.get("inputs", {}).get("months_employed", 12))
data.setdefault("attainment_levels", [50, 75, 100, 150, 200])
return data
# ---------------------------------------------------------------------------
# Commission engine
# ---------------------------------------------------------------------------
def calc_commission_attainment(revenue, quota, tiers, retroactive=False):
"""Tiered attainment-based commission.
tiers: list of (upper_attainment_pct | None, rate_pct).
If retroactive=False (marginal): each rate applies only to revenue in that band.