Spreadsheet Sale Management

Key points

• • Direct connection to Sales Orders, Quotations, Customers, Products

• • Dashboard auto-updates in real-time

• • Analyze revenue by product, team, salesperson, time period

• • Track KPIs: conversion rate, average deal size, sales cycle

• • Forecast revenue based on pipeline and historical data

• • Compare performance between sales teams and individuals

• • Analyze customer behavior and buying patterns

• • Create custom reports for management and stakeholders

Terminology

Steps

• 1. Create new spreadsheet or use "Sales Dashboard" template

• 2. Connect to sales data: =ODOO.LIST("sale.order", fields, domain)

• 3. Create KPI cards: Total Revenue, Orders Count, Average Deal Size

• 4. Add charts: Revenue by Month (line chart), Top Products (bar chart)

• 5. Create pivot table: Revenue by Salesperson and Product Category

• 6. Apply conditional formatting to highlight performance

• 7. Add filters: Date Range, Sales Team, Salesperson

• 8. Share dashboard with management team

KPIs

Key points

• • By time: Daily, Weekly, Monthly, Quarterly, Yearly trends

• • By product: Top selling products, product categories, new vs existing

• • By customer: Top customers, customer segments, new vs repeat

• • By salesperson: Individual performance, team comparison

• • By region: Geographic distribution, regional performance

• • By source: Marketing channels, lead sources

• • Comparison: YoY growth, MoM growth, vs target, vs forecast

• • Breakdown: Product mix, customer mix, channel mix

Key points

• • =ODOO.LIST("sale.order", "name,partner_id,amount_total,state", [["state","=","sale"]]) - Fetch confirmed orders

• • =ODOO.LIST("sale.order.line", "product_id,product_uom_qty,price_subtotal") - Fetch order line details

• • =ODOO.PIVOT("sale.order", "partner_id", "amount_total:sum") - Pivot revenue by customer

• • =ODOO.PIVOT("sale.order", "user_id", "amount_total:sum", [["date_order",">=","2026-01-01"]]) - Revenue by salesperson

• • =ODOO.LIST("crm.lead", "name,expected_revenue,probability,stage_id") - Fetch opportunities

• • =ODOO.FILTER("sale.order", [["date_order",">=",A1],["date_order","<=",A2]]) - Filter by date range

Key points

• • Use conditional formatting to highlight top performers

• • Create leaderboard to motivate healthy competition

• • Analyze gap between teams to identify best practices

• • Track improvement over time with trend charts

Team Performance

Key points

• • Top selling products: Best sellers by quantity and revenue

• • Product growth: Growth of each product over time

• • Product mix: Contribution ratio of each product to total revenue

• • Margin analysis: Compare revenue vs cost to find high-profit products

• • Seasonal trends: Detect seasonal patterns to plan inventory

• • Cross-sell opportunities: Products often bought together

• • Slow movers: Slow-selling products needing action (discount, discontinue)

• • New product performance: Evaluate newly launched products

Key points

• • Top customers: Customers contributing most revenue

• • Customer segmentation: Classify by RFM (Recency, Frequency, Monetary)

• • Purchase frequency: Purchase frequency of each customer segment

• • Customer lifetime value: Total value customer brings

• • Churn risk: Customers at risk of leaving (no purchase for long time)

• • Upsell opportunities: Customers with potential to buy more

• • Customer acquisition trend: New customers over time

• • Repeat purchase rate: Rate of customers returning to buy

Steps

• 1. Fetch pipeline data: opportunities with expected revenue and probability

• 2. Calculate weighted forecast: =expected_revenue × probability

• 3. Analyze historical conversion rates by stage

• 4. Apply seasonality factors based on last year data

• 5. Calculate best case, most likely, worst case scenarios

• 6. Compare forecast vs actual to improve accuracy

• 7. Update forecast weekly based on pipeline changes

Key points

• • Daily sales report: Yesterday's revenue and orders

• • Weekly pipeline review: Opportunities status and forecast

• • Monthly performance report: KPIs, team performance, product analysis

• • Quarterly business review: Strategic overview and trends

• • Ad-hoc reports: Reports on demand for specific questions

• • Scheduled email: Auto-send PDF/Excel at fixed times

• • Dashboard links: Share live dashboard for real-time access

Key points

• • Create master dashboard with overview, drill-down to separate sheets for details

• • Use dynamic date filters (This Month, Last Quarter, YTD) instead of hard-coded dates

• • Apply conditional formatting to highlight KPIs below target (red) and above target (green)

• • Create separate sheets for raw data, calculations, and presentation

• • Use named ranges for important metrics for easy reference

• • Document complex formulas with comments so team understands logic

• • Refresh data before meetings to have latest numbers

• • Backup important dashboards by exporting to Excel periodically

• • Share view-only version with stakeholders to avoid accidental edits

• • Create templates for recurring reports to save time

• • Use pivot tables instead of complex formulas when possible

• • Track changes over time by snapshotting data to separate sheets

Key points

• • ODOO.LIST returns empty: Check domain filters and permissions on model

• • Numbers don't match Odoo UI: Check if date range and filters are the same

• • Dashboard loads slowly: Reduce number of ODOO functions, cache data to separate sheet

• • Forecast not accurate: Review probability settings and historical conversion rates

• • Charts not updating: Refresh spreadsheet or check data range

• • Permission denied: Ensure user has read permission on sales data in Odoo

• • Data mismatch between sheets: Use named ranges and cell references instead of copying values

• • Formulas break when adding rows: Use dynamic ranges (A:A) instead of fixed ranges (A1:A100)