Calculator

Solo Pricing Floor Calculator (Airtable + Sheet): Capacity × Utilization × Ops/LLM Buffer

A build-ready spec for an Airtable/Google Sheets calculator that turns your delivery hours, realistic utilization, and modeled ops/LLM spend into a hard pricing floor with SLA-fit checks. Includes vendor link fields, buffer logic, and two example scenarios.

Use this spec to build a pricing-floor calculator in Airtable or Google Sheets. It converts your delivery hours, realistic utilization, and modeled ops/LLM spend (with a conservative buffer) into a non‑negotiable floor. Add an SLA‑fit multiplier and a hard "reject" gate so you never quote below margin. Link vendor inputs to official pricing pages and record a retrieval date so assumptions stay fresh.

Input: [Deal Name]

Give each deal a short name so you can compare scenarios (mini‑project vs retainer).

Input: [Currency] (e.g., USD, EUR)

Choose your working currency for the outputs. If a vendor shows EUR (e.g., n8n Cloud), set [EUR→USD FX] below or your preferred cross-rate.

Input: [Estimated Delivery Hours]

Hours you expect to spend actively delivering this deal in the billing period (project total or monthly for retainers). Valid range: 1–200. Example defaults: mini‑project 12; retainer 30.

Input: [Utilization Target %]

Your realistic share of time that ends up billable in the period. Default 0.70 (70%). Range: 0.55–0.80 for solos depending on sales/admin load. Note: SPI Research (press release) reported 68.9% average billable utilization, below a 75% target (retrieved 2026‑06‑05).

Input: [Target Effective Hourly Rate ($/hr)]

Your target effective hourly earnings for delivered work, before profit/reserve. This should already reflect your personal draw and overhead. Default: [150] (example). Range: 75–350 depending on market. Optional helper below can compute this from monthly capacity.

Input: [Rate Helper (optional)]

If you don’t have a confident hourly, compute one here and paste it into [Target Effective Hourly Rate].

  • [Monthly Personal Draw $]
  • [Monthly Overhead $] (software, tools, infra, insurance; exclude per‑deal ops/LLM)
  • [Tax Reserve %] (e.g., 0.25)
  • [Profit/Owner Reserve %] on labor (e.g., 0.10–0.20)
  • [Weekly Capacity Hours] (e.g., 35)
  • [Working Weeks/Month] (default 4.33)
  • [Utilization Target %] (reuse) Formulas:
  • Available Billable Hrs/Month = Weekly Capacity × Weeks/Month × Utilization
  • Required Monthly Revenue (pre‑profit) = (Draw + Overhead) × (1 + Tax Reserve)
  • Target Effective Hourly Rate = Required Monthly Revenue ÷ Available Billable Hrs × (1 + Profit/Owner Reserve)

Input: [Currency Conversion] (if applicable)

If any plan cost is shown in EUR, provide a conversion for unified outputs.

  • [EUR→USD FX] (default 1.10) or leave 1.00 to keep vendor currency native.

Input: [Zapier Model]

Decide if you model Zapier for this deal. If no, set Runs/Month = 0.

  • [Zapier Plan Price $/mo] (from pricing slider)
  • [Included Tasks/Month] (from plan)
  • [Tasks per Run] (successful action steps only; triggers/filters often don’t count; see Zapier Help updated 2026‑05‑29)
  • [Runs/Month Attributable to Deal]
  • [Overage Task Unit Price $] (if you buy task add‑ons or use pay‑as‑you‑go)
  • [Share Method] = Pro‑rata by tasks or Flat % allocation Cost logic (monthly, attributable to this deal):
  • Monthly Tasks (deal) = Tasks/Run × Runs/Month
  • Plan Share $ = (Monthly Tasks (deal) ÷ Total Account Tasks) × Plan Price (if pro‑rata)
  • Overage $ = max(Monthly Tasks (account) – Included Tasks, 0) × Overage Unit Price × Deal’s % of overage
  • Zapier Cost $ = Plan Share $ + Overage $

Input: [Make Model]

Decide if you model Make for this deal. If no, set Runs/Month = 0.

  • [Make Plan Price $/mo]
  • [Included Credits/Month]
  • [Credits per Run (non‑AI modules)]
  • [AI Extra Credits per Run] (for AI features; see Make Help: credits vs operations)
  • [Runs/Month Attributable to Deal]
  • [Extra Credit Unit Price $] (if you auto‑purchase or buy packs)
  • [Apply +25% Overage Surcharge?] (toggle; Make Help states extra credits include a 25% additional cost) Cost logic (monthly, attributable):
  • Monthly Credits (deal) = (Credits/Run + AI Extra Credits/Run) × Runs/Month
  • Plan Share $ = (Monthly Credits (deal) ÷ Total Account Credits) × Plan Price (if pro‑rata)
  • Overage $ = max(Monthly Credits (account) – Included Credits, 0) × Extra Credit Unit Price × (1 + 0.25 if surcharge on)
  • Make Cost $ = Plan Share $ + Overage $

Input: [n8n Model] (Cloud or Self‑host)

Choose Cloud or Self‑host. If Cloud and priced in EUR, convert with [EUR→USD FX]. If Self‑host, enter infra costs. Cloud fields:

  • [n8n Cloud Plan Price €/mo]
  • [Included Executions/Month]
  • [Executions per Run]
  • [Runs/Month Attributable to Deal]
  • [Overage Unit Price €] (if applicable) Self‑host fields:
  • [VM/Server $/mo], [Bandwidth $/mo], [Other $/mo] Cost logic (monthly, attributable):
  • Monthly Executions (deal) = Executions/Run × Runs/Month
  • Cloud Plan Share $ = (Executions (deal) ÷ Total Executions) × (Plan Price € × FX)
  • Overage $ = max(Total Executions – Included, 0) × Overage Unit Price × FX × Deal’s % of overage
  • Self‑host $ = Sum of infra costs × Deal’s % allocation
  • n8n Cost $ = Cloud Plan Share $ + Overage $ OR Self‑host $

Input: [OpenAI Model + Batch + Containers]

LLM tokens and optional container sessions for agents/batch jobs.

  • [Model Selector] (e.g., GPT‑5.5 / GPT‑5.4 / GPT‑5.4 mini)
  • [Input $/M tokens], [Output $/M tokens] (from OpenAI Pricing; retrieved 2026‑06‑05)
  • [Batch Mode?] (toggle; Batch API applies 50% discount to token rates when on)
  • [Avg Input Tokens per Run], [Avg Output Tokens per Run]
  • [Runs/Month Attributable to Deal]
  • [Container Price $/session], [Sessions per Run], [Minutes per Session] (OpenAI containers bill per 20‑minute session; pricing changed effective 2026‑03‑31) Cost logic (monthly):
  • Token Cost/Run = ((InputTokens/1e6 × Input $/M) + (OutputTokens/1e6 × Output $/M)) × (0.5 if Batch on else 1)
  • Container Sessions/Run = ceil(Minutes per Run ÷ 20) × Sessions per Run
  • Container Cost/Run = Container Sessions/Run × Container Price
  • LLM Cost/Month (deal) = (Token Cost/Run + Container Cost/Run) × Runs/Month

Input: [Ops/LLM Buffer %] (default 0.30)

A conservative cushion for ops variance and overage mechanics. Default 0.30 (30%). Justification: Make’s extra credits carry a documented +25% surcharge; spikes happen mid‑month and LLM usage varies, so 25–30% protects margin.

Input: [SLA Tier + Feasibility]

Pick the tightest promise you’ll make for this deal. If the tier is infeasible for a solo operator, the calculator will force a hard reject.

  • Standard (next business day response, no uptime guarantee) → Multiplier ×1.00
  • Priority (same‑day response, reasonable hours) → ×1.20
  • Critical (≤4‑hour response, extended hours or on‑call) → ×1.50–2.00 and feasibility gate Feasibility gates (edit to taste):
  • If coverage requires 24×7 or <2‑hour response without shared on‑call → Reject
  • If target availability commitment >99.9% without redundant infra/runbooks → Reject Note: Tighter SLAs shrink error budgets and raise cost (Google SRE guidance).

Input: [Profit/Reserve %]

Owner’s profit or contingency on top of labor+ops. Default 0.20 (20%). Range: 0.10–0.35 depending on risk.

Input: [Rounding + Proposed Price]

Choose how you’ll present the number.

  • [Rounding Rule] = Nearest $50 / $100 / $500
  • [Proposed/Quoted Price $] (optional for Accept/Reject gate)

Output: [Labor Floor $]

Covers non‑billable time so your hours don’t underprice the work. Formula:

  • Utilization Uplift = 1 ÷ [Utilization Target %]
  • Labor Floor $ = [Estimated Delivery Hours] × [Target Effective Hourly Rate] × Utilization Uplift

Output: [Ops/LLM Cost Breakdown $]

Break out by platform to see drivers. Formulas (monthly, attributable to this deal):

  • Zapier Cost $ (see Zapier Model)
  • Make Cost $ (see Make Model)
  • n8n Cost $ (Cloud or Self‑host model)
  • OpenAI LLM Cost $ (tokens + containers)
  • Ops/LLM Subtotal $ = Sum of above
  • Ops/LLM Buffer $ = Ops/LLM Subtotal × [Ops/LLM Buffer %]

Output: [Pre‑SLA Floor + Owner Reserve $]

Pre‑SLA Floor $ = [Labor Floor $] + [Ops/LLM Subtotal $] + [Ops/LLM Buffer $] Owner Reserve Added $ = Pre‑SLA Floor × [Profit/Reserve %] Pre‑Round, Pre‑SLA Total $ = Pre‑SLA Floor + Owner Reserve Added $

Output: [Final Pricing Floor $]

Final Floor (Before Rounding) $ = [Pre‑Round, Pre‑SLA Total $] × [SLA Multiplier] Final Floor (Rounded) $ = Apply [Rounding Rule]

Output: [Deal Status — Accept / Reject / Hard Reject]

If [SLA Tier] violates any feasibility gate → Status = HARD REJECT. Else if [Proposed/Quoted Price $] < [Final Floor (Rounded) $] → Status = REJECT (Below Floor). Else → Status = ACCEPT (Meets Floor).

Output: [Quote Notes]

Auto‑generate plain‑language notes to paste in your quote:

  • "Floor assumes [Model] with [Batch on/off], avg [InputTokens]/[OutputTokens] tokens per run."
  • "Ops buffer set to [X%] to cover Make/Zapier/n8n overage variance."
  • "SLA tier: [Standard/Priority/Critical]; price includes ×[multiplier]."
  • "Vendor pricing pages checked on [Retrieved Date] — links in calculator."

Logic: [Formula Map]

Pseudocode you can copy into a Sheet or Airtable formula fields.

  • Uplift = 1 / Utilization
  • Labor$ = Hours × Rate × Uplift
  • Zapier$ = Zap_PlanShare$ + Zap_Overage$
  • Make$ = Make_PlanShare$ + Make_Overage$
  • n8n$ = n8n_CloudShare$ + n8n_Overage$ OR n8n_SelfHost$
  • TokenRun$ = ((InTok/1e6 × In$/M) + (OutTok/1e6 × Out$/M)) × IF(Batch, 0.5, 1)
  • ContainerRun$ = CEILING(MinPerRun / 20) × SessionsPerRun × Container$/Session
  • LLM$ = (TokenRun$ + ContainerRun$) × RunsPerMonth
  • OpsSubtotal$ = Zapier$ + Make$ + n8n$ + LLM$
  • Buffer$ = OpsSubtotal$ × Buffer%
  • PreSLA$ = Labor$ + OpsSubtotal$ + Buffer$
  • WithReserve$ = PreSLA$ × (1 + ProfitReserve%)
  • FinalFloor$ = ROUND_TO(WithReserve$ × SLAMultiplier, RoundingRule)
  • Status = IF(HardGate, "HARD REJECT", IF(Quoted < FinalFloor$, "REJECT", "ACCEPT"))

Examples: [12‑hour Mini‑project] and [30‑hour Retainer]

Use these to sanity‑check your build. Replace numbers with your own. Scenario A — 12‑hour mini‑project:

  • Hours = 12; Utilization = 0.70; Rate = $180/hr ⇒ Labor$ = 12 × 180 × (1/0.70) = $3,086
  • Zapier: 2 tasks/run × 120 runs = 240 tasks (pro‑rata share from plan) ⇒ Zapier$ = $[calc]
  • Make: 5 credits/run × 60 runs = 300 credits ⇒ Make$ = $[calc]
  • n8n: not used ⇒ $0
  • OpenAI: 2k in/800 out tokens/run × 120 runs; Model = 5.4 mini; Batch = on ⇒ LLM$ = $[calc]
  • OpsSubtotal$ = Sum platform costs; Buffer = 30%
  • Profit/Reserve = 20%; SLA = Standard ×1.00
  • Final Floor (Rounded $100) ≈ $[result] Scenario B — 30‑hour monthly retainer:
  • Hours = 30; Utilization = 0.65; Rate = $160/hr ⇒ Labor$ = 30 × 160 × (1/0.65) = $7,385
  • Zapier: 3 tasks/run × 300 runs = 900 tasks (see Zapier Help example pattern)
  • Make: 4 credits/run (non‑AI) + 1 AI credit/run × 200 runs = 1,000 credits
  • n8n Cloud in EUR: 1 execution/run × 600 runs = 600 executions (convert via FX)
  • OpenAI: 4k in/1k out tokens/run × 200 runs; Model = 5.4; Batch = off
  • Buffer = 30%; Profit/Reserve = 20%; SLA = Priority ×1.20
  • Final Floor (Rounded $100) ≈ $[result] Note: The [calc]/[result] cells are computed by your sheet from the live vendor inputs you paste in. Do not hardcode vendor prices here.

Maintenance: [Updates + Sources]

  • Link fields to official pages and set [Retrieved Date].
  • Re‑check OpenAI, Zapier, Make, n8n pages quarterly or before large quotes.
  • If this deal will consume most of an account’s plan allowance, switch from pro‑rata to direct attribution for fairness.
  • Log actual tokens/tasks/credits for 2–4 weeks post‑launch; adjust buffer and model mix. Official references (paste into your calculator’s "Sources" sheet):
  • OpenAI API Pricing — models, Batch, containers (retrieved 2026‑06‑05)
  • Zapier Help — task measurement and plan selection example (updated 2026‑05‑29; retrieved 2026‑06‑05)
  • Make Help — credits and +25% extra‑credit cost (retrieved 2026‑06‑05)
  • n8n — pricing and "executions" definition (retrieved 2026‑06‑05)
  • SPI Research press release — utilization 68.9% (retrieved 2026‑06‑05)
  • Google SRE Book — SLA/SLO trade‑offs (evergreen)