1. Sales Forecasting & Revenue Prediction
Goal: Predict next quarter’s revenue based on pipeline, conversion rates, and payments.
Data Sources: CRM (HubSpot / Zoho / Salesforce), Accounting (QuickBooks / Xero), Marketing (Google Ads / LinkedIn)
What It Does:
- Calculates probability of deal closure and expected close dates.
- Aggregates historical pipeline and invoice data to forecast future revenue.
- Highlights sales reps or regions likely to miss targets.
Impact: Enables accurate revenue forecasts and better resource planning for SMB leadership.
High-Level Steps:
- Extract CRM and accounting data via APIs.
- Clean and align deal and invoice data.
- Engineer features (deal stage, source, velocity).
- Train regression or boosting models to forecast revenue.
- Visualize forecasts inside Power BI or a custom dashboard.
2. Cash Flow Risk Predictor
Goal: Forecast cash shortages or liquidity risks weeks in advance.
Data Sources: Accounting (QuickBooks / Xero), Payroll (Gusto / ADP), CRM (forecasted deals)
What It Does:
- Combines incoming receivables, outgoing expenses, and forecasted deals.
- Predicts weekly cash balance trends.
- Flags upcoming shortfalls before they occur.
Impact: Gives SMBs financial foresight to avoid cash crunches and manage growth with confidence.
High-Level Steps:
- Extract invoices, bills, and payroll data.
- Aggregate inflows/outflows by week.
- Apply time-series models to predict future cash.
- Set alert thresholds for shortfalls.
- Display projections and alerts on a financial dashboard.
3. Customer Churn Prediction
Goal: Identify customers likely to stop doing business soon.
Data Sources: CRM, Support (Zendesk / Freshdesk), Billing (Stripe / Recurly), Product Usage Logs
What It Does:
- Analyzes support frequency, sentiment, and usage activity.
- Scores customers based on likelihood of churn.
- Pushes risk alerts back into CRM for proactive outreach.
Impact: Helps SMBs retain high-value customers through early intervention and personalized engagement.
High-Level Steps:
- Merge CRM, support, and billing data by customer ID.
- Label churned vs. active customers.
- Engineer behavioral features (activity, sentiment, ticket volume).
- Train classification models to predict churn risk.
- Deploy results as CRM risk scores or dashboard metrics.
4. Inventory Demand Forecasting
Goal: Predict demand and optimize reorder timing for inventory.
Data Sources: ERP / Inventory (Zoho / Odoo), CRM, Marketing Campaign Data, Accounting Costs
What It Does:
- Forecasts SKU-level sales volume and demand spikes.
- Highlights products trending toward overstock or stockout.
- Calculates optimal reorder quantities based on lead times.
Impact: Reduces excess inventory costs and prevents out-of-stock losses.
High-Level Steps:
- Aggregate SKU-level sales and stock data.
- Include seasonality and promotional variables.
- Use Prophet or ARIMA models per SKU.
- Set reorder alerts and visualize in dashboard.
5. Marketing Spend Optimization
Goal: Recommend optimal ad budget allocation across channels for maximum ROI.
Data Sources: Ad Platforms (Google / Meta / LinkedIn), CRM (deals, leads), Accounting (revenue)
What It Does:
- Links ad spend → leads → deals → revenue.
- Calculates true ROI per campaign.
- Recommends optimal next-period budget distribution.
Impact: Turns marketing from cost center to profit engine with real ROI attribution.
High-Level Steps:
- Merge ad and CRM data using campaign IDs or UTMs.
- Aggregate spend, conversions, and deal value.
- Train regression models to predict ROI by channel.
- Simulate “what-if” budget reallocations.
- Show recommended allocations in a marketing dashboard.
6. Employee Attrition Prediction
Goal: Identify employees at risk of leaving before they resign.
Data Sources: HR (BambooHR / Gusto), Time Tracking (Clockify / Harvest), Engagement Surveys, Project Tools
What It Does:
- Analyzes workload, overtime, and engagement trends.
- Predicts which employees may churn.
- Provides HR with early alerts for intervention.
Impact: Reduces turnover costs and preserves institutional knowledge within small teams.
High-Level Steps:
- Combine HR, time tracking, and survey data by employee ID.
- Engineer workload and sentiment features.
- Train classification models for attrition risk.
- Visualize top risk factors in dashboard.
7. Profitability & Margin Prediction
Goal: Forecast project or client profitability before completion.
Data Sources: CRM (deals, pricing), Time Tracking, Accounting (expenses), Project Management
What It Does:
- Calculates projected vs. actual margins per client.
- Identifies projects trending toward cost overruns.
- Highlights profit drivers and risk factors.
Impact: Helps SMBs manage pricing, effort, and profitability proactively.
High-Level Steps:
- Merge CRM, time, and accounting data by project.
- Engineer cost and performance metrics.
- Train regression model to forecast margin.
- Embed predictions into a BI dashboard.
