Financial Operations

Vantage integrates directly with Stripe, Shopify, and QuickBooks to pull financial data into automated workflows. Build revenue dashboards, reconcile payments, monitor subscription health, and generate financial reports — all from a single platform.

Reconcile Revenue Across Platforms and Generate Reports

Reconcile revenue across multiple payment platforms and generate consolidated reports.

Scenario: A finance team receives payments through Stripe (subscriptions), Shopify (e-commerce), and direct invoices (QuickBooks). They need a single source of truth for daily revenue, reconciled automatically.

Workflow Steps:

1. Schedule Trigger — Run daily at 11 PM
2. List Balance Transactions (Stripe) — Pull all balance transactions for the day: charges, refunds, payouts, fees
3. Shopify — Get Order Stats — Pull completed orders, returns, and order values
4. QuickBooks — List Invoices — Pull invoices paid and outstanding
5. Union — Merge all revenue streams into a single dataset (source, type, amount, currency, customer, timestamp)
6. Aggregation — Sum by source platform, revenue type (new, recurring, one-time), and currency
7. Computed Column — Calculate:
   • Gross revenue = sum of all charges/orders
   • Net revenue = gross - refunds - fees
   • Effective fee rate = fees / gross * 100
8. Data Validation — Cross-check: sum of individual transactions = reported daily total (catch missing or duplicated transactions)
9. Multi-Conditional — Route by reconciliation result:
   • Balanced (variance < $1) → Dashboard Output + DB Write (post to general ledger)
   • Minor variance ($1–$100) → Dashboard Output + Send Message (Slack #finance) with variance detail
   • Major variance (> $100) → Send Email to Controller + Create Issue (Jira) for investigation
10. Write Excel — Generate daily revenue reconciliation workbook with three tabs (Stripe, Shopify, QuickBooks) + Summary
11. Dashboard Output — Populate:
    • Metric Tile — Net revenue today with sparkline
    • Bar Tile — Revenue by platform
    • Waterfall Tile — Gross → refunds → fees → net
    • Comparison Tile — Today vs. same day last week
    • Table Tile — All transactions with drill-down

Key Nodes: Schedule Trigger, List Balance Transactions (Stripe), Shopify Get Order Stats, QuickBooks List Invoices, Union, Aggregation, Computed Column, Data Validation, Multi-Conditional, Write Excel, DB Write, Send Email, Send Message, Dashboard Output

Relevant Integrations: Stripe, Shopify, QuickBooks

Analyze Subscription Health and Predict Churn

Monitor subscription metrics, detect churn risk, and automate retention outreach.

Scenario: A SaaS company wants to track MRR, churn rate, expansion revenue, and customer lifetime value — with automated alerts when accounts show signs of churn.

Workflow Steps:

1. Schedule Trigger — Run daily
2. List Customers (Stripe) — Pull all customers with subscription status, plan, MRR, and billing cycle
3. Search Charges (Stripe) — Pull payment history: successful charges, failed charges, disputes
4. Database Query (PostgreSQL) — Pull product usage metrics: last login, sessions per week, feature adoption
5. Join — Merge billing data with usage data on customer ID
6. Computed Column — Calculate churn risk indicators:
   • Payment failure in last 30 days
   • Usage decline > 30% month-over-month
   • No login in 21+ days
   • Downgrade from higher plan
   • Composite churn risk score (0–100)
7. Filter — Customers with churn risk score > 60
8. AI Enrichment — For high-risk customers, generate a retention recommendation: "Customer Acme Corp's usage declined 45% after their admin left in January. Recommend scheduling an onboarding refresh with their new admin."
9. Multi-Conditional — Route by risk level:
   • Score > 80 (Critical) → Send Email to VP of Customer Success + Create Task (Jira) for urgent outreach
   • Score 60–80 (At Risk) → Send Message (Slack) to assigned CSM
10. Dashboard Output — Populate:
    • Metric Tile — MRR, Net Revenue Retention, Churn Rate (each with sparkline)
    • Line Tile — MRR trend over 12 months
    • Pie Tile — Customer distribution by plan tier
    • Table Tile — At-risk customer list with risk score and recommended action
    • Forecast Tile — MRR projection assuming current churn rate continues
    • Comparison Tile — This month vs. last month churn/expansion

Key Nodes: Schedule Trigger, List Customers, Search Charges (Stripe), Database Query, Join, Computed Column, Filter, AI Enrichment, Multi-Conditional, Send Email, Send Message, Create Task (Jira), Dashboard Output

Optimize Inventory Levels and Maximize Revenue

Analyze product performance, track inventory levels, and optimize pricing and stock allocation.

Scenario: An e-commerce operations team needs to identify top-selling products, flag slow-moving inventory, and project when popular items will run out of stock.

Workflow Steps:

1. Schedule Trigger — Run daily
2. Shopify — List Products — Pull all products with current price, inventory quantity, and status
3. Shopify — Get Order Stats — Pull order volume, revenue, and return rate by product over the last 30 days
4. Shopify — Get Inventory Levels — Pull current stock levels across all fulfillment locations
5. Join — Merge product catalog with sales performance and inventory data
6. Computed Column — Calculate:
   • Sell-through rate: units_sold / (starting_inventory + units_received) * 100
   • Days of inventory remaining: current_stock / average_daily_sales
   • Revenue per unit: total_revenue / units_sold
   • Inventory turnover ratio: cost_of_goods_sold / average_inventory_value
7. Sort — By days of inventory remaining (ascending — lowest stock first)
8. Filter — Products with < 14 days of stock and sales velocity > 5 units/day
9. AI Enrichment — Generate a reorder recommendation: suggested reorder quantity, optimal reorder point, and projected stockout date
10. Multi-Conditional — Route by urgency:
    • < 7 days of stock → Send Email to procurement manager (urgent reorder) + Dashboard Output (red alert)
    • 7–14 days of stock → Send Message (Slack #inventory) + Dashboard Output (yellow warning)
11. Dashboard Output — Populate:
    • Table Tile — Product performance scorecard (revenue, velocity, margin, stock)
    • Scatter Tile — Revenue vs. inventory (identify overstocked underperformers)
    • Forecast Tile — Revenue projection by product category
    • List Tile — Reorder queue with recommended quantities
    • Metric Tile — Overall inventory turnover, stockout risk count

Key Nodes: Schedule Trigger, Shopify List Products, Shopify Get Order Stats, Shopify Get Inventory Levels, Join, Computed Column, Sort, Filter, AI Enrichment, Multi-Conditional, Send Email, Send Message, Dashboard Output

Accelerate Accounts Receivable and Payment Collection

Track outstanding invoices, automate payment reminders, and monitor collection performance.

Scenario: A finance team needs to manage outstanding receivables: send automated payment reminders at scheduled intervals, escalate overdue accounts, and track collection rates.

Workflow Steps:

1. Schedule Trigger — Run daily at 8 AM
2. QuickBooks — List Invoices — Pull all outstanding invoices with amount, due date, customer, and days outstanding
3. List Customers (Stripe) — Cross-reference with payment methods on file
4. Join — Merge invoice data with customer payment profiles
5. Computed Column — Calculate days overdue: CURRENT_DATE - due_date
6. Multi-Conditional — Route by aging bucket:
   • Due in 7 days (upcoming) → Send Email (friendly reminder with payment link)
   • 1–15 days overdue → Send Email (firm reminder) + Send Message (Slack) to account manager
   • 16–30 days overdue → Send Email (urgent, cc: finance director) + Create Task (Jira) for collection call
   • > 30 days overdue → Send Email to CFO for escalation + Dashboard Output (bad debt risk list)
7. Aggregation — Sum outstanding by aging bucket and by customer
8. Dashboard Output — Populate:
   • Bar Tile — Outstanding receivables by aging bucket (current, 1–15, 16–30, 30+)
   • Metric Tile — Total AR balance, DSO (Days Sales Outstanding), collection rate %
   • Table Tile — Customer aging detail with last contact date
   • Comparison Tile — AR balance this month vs. last month
   • Predictive Insights Tile — Projected collections based on historical payment patterns

Key Nodes: Schedule Trigger, QuickBooks List Invoices, List Customers (Stripe), Join, Computed Column, Multi-Conditional, Aggregation, Send Email, Send Message, Create Task (Jira), Dashboard Output

Example Dashboard: Financial Control Center

Build this dashboard to give your finance team real-time visibility into revenue, receivables, subscription health, and budget performance.

Row 1 — Revenue Snapshot

Row 2 — Revenue Detail

Row 3 — Subscription & Customer

Row 4 — Receivables & Collections

Row 5 — Forecasting & Inventory

Getting Started

To build financial operations workflows:

1. Connect payment platforms — Authenticate Stripe, Shopify, and/or QuickBooks under Integrations
2. Build a reconciliation workflow — Use Schedule Trigger + data pull nodes + Union + Aggregation to consolidate revenue
3. Add validation — Use Data Validation to catch reconciliation discrepancies automatically
4. Set up alerts — Multi-Conditional to route by severity: variances, overdue invoices, stockout risks
5. Create financial dashboards — Metric, Bar, Waterfall, and Forecast tiles for at-a-glance financial health