AHQ Documentation

Appearance

Widgets ​

Understanding the Dashboard ​

Dashboard Header ​

Data Freshness Indicators:

Dashboard as of: Jan 31, 2026  |  Last updated: Feb 3, 2026 14:23 CET
  • "as of" date - The last complete month of financial data
  • "Last updated" - When KPIs were last calculated
  • "Refresh KPIs" button - Manually recalculate all metrics

When to Refresh:

  • After uploading new financial data
  • If dashboard feels outdated (> 1 week old)
  • After correcting financial data errors

Core Metrics Widgets ​

1. Cash Runway ​

What it shows: How long your company can operate with current cash before running out.

Key Metrics:

  • Current Cash Balance - Total cash available today
  • Monthly Burn Rate - Average cash spent per month (last 6 months)
  • Runway in Months - Cash ÷ Burn Rate
  • Trend - Whether runway is improving, stable, or declining
  • 6-Month Trend Chart - Visual history of runway changes

How to Read:

Current Cash: $500,000
Monthly Burn: $50,000
Runway: 10 months
Trend: Stable

Alert Levels:

  • 🔴 Critical (< 3 months) - Urgent action needed, fundraising or cost cuts required
  • 🟡 Warning (3-6 months) - Start planning for fundraising or profitability
  • 🟢 Healthy (6-12 months) - Good position, monitor regularly
  • ⚪ Strong (> 12 months) - Excellent position, focus on growth

Action Items by Runway:

  • < 3 months: Immediate fundraising, freeze hiring, cut non-essential costs
  • 3-6 months: Start fundraising process, optimize spending
  • 6-12 months: Monitor closely, plan next fundraising round
  • > 12 months: Invest in growth, maintain discipline

2. Revenue Bridge ​

What it shows: How your Monthly Recurring Revenue (MRR) changed from last month to this month.

Components:

  • Starting MRR - MRR at beginning of month
  • New MRR - Revenue from new customers acquired
  • Expansion MRR - Additional revenue from existing customers (upsells, upgrades)
  • Contraction MRR - Lost revenue from downgrades
  • Churned MRR - Lost revenue from cancelled customers
  • Ending MRR - MRR at end of month

How to Read:

Starting MRR: $100,000
+ New: $15,000
+ Expansion: $5,000
- Contraction: $2,000
- Churn: $8,000
= Ending MRR: $110,000

Net Growth: +$10,000 (+10%)

Waterfall Chart: Shows visual flow from starting to ending MRR.

What Good Looks Like:

  • New MRR consistently positive (growing customer base)
  • Expansion MRR > 0 (existing customers spending more)
  • Churn MRR < 5-7% of starting MRR (healthy retention)
  • Net Growth positive every month

Red Flags:

  • Churn > 10% monthly (unsustainable)
  • Contraction > Expansion (customers downgrading)
  • New MRR declining month-over-month
  • Net growth negative (shrinking)

3. Financial Summary ​

What it shows: High-level snapshot of financial performance for the most recent month.

Metrics:

  • Total Revenue - All revenue for the month
  • Revenue Growth - Month-over-month change (%)
  • Gross Margin - (Revenue - COGS) / Revenue as %
  • Net Income - Revenue - All Expenses (can be negative)
  • Operating Expenses - Total OpEx excluding COGS
  • EBITDA - Earnings before interest, taxes, depreciation, amortization

How to Read:

Total Revenue: $100,000
Revenue Growth: +15.5% MoM
Gross Margin: 75.5%
Net Income: -$25,000 (loss)
Operating Expenses: $80,000
EBITDA: $20,000

Interpretation:

  • Gross Margin 75.5% - Good for SaaS (target: 70-80%)
  • Net Income -$25,000 - Losing money but investing in growth
  • EBITDA $20,000 - Positive unit economics, losses from D&A or financing

SaaS Benchmarks:

  • Gross Margin: 70-80% (excellent), 60-70% (good), < 60% (concerning)
  • Revenue Growth: > 20% MoM (hypergrowth), 10-20% (strong), < 10% (slow)
  • Operating Expenses: Should be < Revenue if profitable, > Revenue if growth stage

4. P&L Variance (Budget vs Actual) ​

What it shows: How actual performance compared to your budget.

Display:

  • Period - Which month is being compared
  • Category Breakdown - Each budget category (Revenue, Marketing, Engineering, etc.)
  • Budget Amount - What you planned to spend/earn
  • Actual Amount - What you actually spent/earned
  • Variance - Difference ($ and %)

How to Read:

Revenue:      Budget: $100,000  |  Actual: $110,000  |  Variance: +$10,000 (+10%) 🟢
Marketing:    Budget: $20,000   |  Actual: $25,000   |  Variance: -$5,000 (-25%) 🔴
Engineering:  Budget: $50,000   |  Actual: $48,000   |  Variance: +$2,000 (+4%) 🟢

Color Coding:

  • 🟢 Green - Favorable variance (revenue higher, costs lower)
  • 🔴 Red - Unfavorable variance (revenue lower, costs higher)
  • 🟡 Yellow - Within 10% tolerance

Action Items:

  • Large red variances (> 20%) - Investigate immediately, adjust budget or spending
  • Consistent pattern - If marketing always over budget, increase budget allocation
  • Revenue misses - Review sales forecast assumptions, adjust targets

Note: Requires budget data to be uploaded. If no budget exists, widget shows "No budget data available."

Advanced Metrics Widgets ​

5. Customer Cohorts ​

What it shows: Customer retention analysis grouped by acquisition month.

Metrics:

  • Cohort Table - Shows retention % for each cohort at M0, M1, M3, M6
  • Retention Chart - Visual comparison of cohort retention curves
  • Average Retention - Average retention rate across all cohorts at month 6
  • LTV - Estimated Lifetime Value based on retention

How to Read:

Jan 2026 Cohort:
M0: 100% (all start at 100%)
M1: 95% (5% churned in first month)
M3: 88% (12% total churn by month 3)
M6: 83% (17% total churn by month 6)

What Good Looks Like:

  • M1 retention > 90% - Strong onboarding
  • M6 retention > 80% - Excellent product-market fit
  • Improving cohorts - Newer cohorts retain better (product improvements working)

Red Flags:

  • M1 retention < 80% (onboarding issues)
  • M6 retention < 60% (weak product-market fit)
  • Declining cohorts (newer cohorts worse than old)

Data Requirements: Requires customer-level data or revenue by customer. If not available, shows "Requires customer data."

6. Unit Economics ​

What it shows: Customer acquisition efficiency and profitability.

Metrics:

  • CAC - Customer Acquisition Cost (Sales & Marketing / New Customers)
  • LTV - Lifetime Value (ARPU × Gross Margin / Churn Rate)
  • LTV:CAC Ratio - How much value per dollar spent acquiring
  • Payback Period - Months to recover CAC
  • Gross Margin % - Profitability per dollar of revenue

How to Read:

CAC: $500
LTV: $2,500
LTV:CAC Ratio: 5.0x
Payback Period: 6.5 months
Gross Margin: 75.5%

Ratio Assessment:

  • LTV:CAC ≥ 5.0x - Excellent (can invest aggressively in growth)
  • LTV:CAC ≥ 3.0x - Good (healthy unit economics)
  • LTV:CAC ≥ 1.0x - Break-even (not sustainable long-term)
  • LTV:CAC < 1.0x - Poor (losing money on every customer)

Payback Period Benchmarks:

  • < 6 months - Excellent (fast cash recovery)
  • 6-12 months - Good (standard SaaS)
  • 12-18 months - Acceptable (enterprise SaaS)
  • > 18 months - Concerning (high risk)

Action Items:

  • Low LTV:CAC (< 3.0x) - Reduce CAC (optimize marketing) or increase LTV (reduce churn, upsell)
  • Long payback (> 12 months) - May struggle to scale without capital
  • Improving trend - Continue current strategies

7. Pipeline Health ​

What it shows: Sales pipeline performance and conversion rates.

Metrics:

  • Total Pipeline Value - Sum of all open deals
  • Weighted Pipeline - Pipeline × probability of close
  • Conversion Rate - % of leads that become customers
  • Average Deal Size - Mean contract value
  • Sales Cycle Length - Days from lead to close
  • Pipeline by Stage - Breakdown by sales stage (Lead, Qualified, Demo, Proposal, Negotiation)

How to Read:

Total Pipeline: $500,000
Weighted Pipeline: $150,000 (assumes 30% close rate)
Conversion Rate: 25%
Avg Deal Size: $10,000
Sales Cycle: 45 days

Pipeline by Stage:
- Leads: $200,000 (40%)
- Qualified: $150,000 (30%)
- Demo: $100,000 (20%)
- Proposal: $50,000 (10%)

What Good Looks Like:

  • Pipeline 3x+ revenue target - Enough deals to hit goals
  • Conversion rate > 20% - Efficient sales process
  • Balanced stages - Healthy flow through pipeline
  • Sales cycle decreasing - Process improving over time

Red Flags:

  • Pipeline < 2x target (not enough deals)
  • Conversion < 10% (poor lead quality or sales execution)
  • Bottom-heavy pipeline (deals stuck in proposal/negotiation)
  • Sales cycle increasing (process breaking down)

Data Requirements: Requires sales/CRM data. If not available, shows "Requires pipeline data."

Common Questions ​

Why do I see "No KPI data available"? ​

Possible reasons:

  1. KPIs haven't been calculated yet - Click "Refresh KPIs"
  2. Less than 3 months of financial data - Upload more data
  3. Missing required report types - Upload Balance Sheet and P&L

Solution: Check dashboard info bar for data coverage, then click "Refresh KPIs."

How often should I refresh KPIs? ​

Automatic refresh: KPIs auto-calculate when you upload new financial data.

Manual refresh needed when:

  • You correct errors in uploaded data
  • You delete and re-upload a month
  • Dashboard feels stale (hasn't updated in 7+ days)

Recommended frequency: Monthly after uploading new month's financials.

Why do some widgets show errors? ​

Phase 2 widgets require specific data:

  • Customer Cohorts - Needs customer-level revenue data
  • Unit Economics - Needs marketing spend and customer acquisition data
  • Pipeline Health - Needs sales/CRM data

Solution: These are advanced metrics that require data beyond standard financial statements. Phase 1 widgets work with just Balance Sheet and P&L.

Can I customize which widgets to show? ​

Not currently. All 7 widgets are always displayed. If data is unavailable for a widget, it shows an info message.

Future: Custom dashboard layouts planned for Q3 2026.

How accurate are the AI calculations? ​

Very accurate for numerical calculations. The AI follows strict formulas and is validated against test datasets.

Potential issues:

  • Data quality - Garbage in, garbage out. Ensure uploaded data is accurate.
  • Categorization - AI infers COGS vs OpEx. Review first time to ensure correct.
  • Estimates - Some metrics use estimates when exact data unavailable (noted in widget).

Best practice: Review first calculation closely, then trust ongoing automated updates.

What if my numbers look wrong? ​

Troubleshooting steps:

  1. Check source data - Navigate to Financial Data and verify uploaded data is correct
  2. Review categorization - Ensure expenses are categorized correctly (COGS vs OpEx)
  3. Check date ranges - Verify "as of" date matches your expectations
  4. Recalculate - Click "Refresh KPIs" to trigger fresh calculation
  5. Contact support - If still incorrect, reach out with specific widget and expected values

Can I export the dashboard? ​

Yes! Navigate to Reports page to:

  • Download PDF - Professional investor report with all KPIs
  • Download CSV - Raw data for Excel analysis
  • Generate Web Link - Share live dashboard with investors (no login required)

See Investor Reports User Guide for details.

Tips for Success ​

1. Upload Data Consistently ​

  • Upload monthly data within 5 days of month-end
  • Maintain consistent format and categorization
  • Include all 3 report types (BS, P&L, CF) for best results

2. Review First Calculation Closely ​

  • When KPIs first calculate, review each widget carefully
  • Verify formulas match your accounting practices
  • Check that categorization aligns with your books

3. Monitor Trends, Not Absolutes ​

  • Single month fluctuations are normal
  • Focus on 3-6 month trends
  • Watch for sudden changes that indicate issues

4. Use Alerts for Action ​

  • Cash runway < 6 months → Start planning
  • Churn > 10% → Investigate customer success
  • LTV:CAC < 3.0x → Optimize acquisition or retention

5. Share with Leadership ​

  • Export monthly PDF for board meetings
  • Use web links for async investor updates
  • Discuss variance analysis with department heads

Keyboard Shortcuts ​

  • r - Refresh KPIs (same as clicking button)
  • d - Navigate to Dashboard
  • Alt+r - Navigate to Reports page

Troubleshooting ​

Dashboard loads slowly ​

Causes:

  • Large dataset (24+ months)
  • First time loading (no cache)
  • Network issues

Solutions:

  • Wait 2-5 seconds on first load
  • Subsequent loads are < 1 second (cached)
  • Refresh browser if stuck > 10 seconds

"Calculation failed" error ​

Causes:

  • Insufficient data (< 3 months)
  • Missing required report types
  • AI service temporarily unavailable

Solutions:

  • Verify data coverage (check info bar)
  • Wait 1 minute and retry "Refresh KPIs"
  • If persists, contact support

Widgets show different "as of" dates ​

This is normal. All widgets use the same "as of" date (last complete month). If you see different dates, it's a bug - please report.