Total ARR (USD) ยท โ€”
$0
Month-over-month โ€” ยท 0 active customers

Revenue by product group

ARR Trend
12M

ARR Trend (USD)

Monthly recurring revenue over time

Product Mix
โ€”

Product Mix (USD)

Revenue by product group

Top Customers
โ€”

Top Customers (USD)

Highest revenue contributors

Dashboards & Reports

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Total ARR Range
$0
Across selected period
Reporting IDs
0
In selected range
Months Selected
0
Time period

ARR Pivot Table

Showing 0-0 of 0 records
Total Tasks
0
Historical runs
Successful
0
Completed successfully
Failed
0
Requires attention
Last Ad Hoc Run
Never
Manual execution
Last Scheduled Run
Never
Automated execution
Next Scheduled Run
Daily at 2:00 AM EST
Automated schedule

Task History

Task Name Execution Type State Scheduled Time Completed Time Duration Error Message
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Total Snapshots
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- completed
Completed
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Successfully created
Failed
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Requires attention
Latest Snapshot
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Snapshot ID Date Type Status Records Total ARR Created By Actions
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Reporting ID Month Product Group Change Type Previous Value Current Value Change Amount Change %
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Alert ID Timestamp Type Severity Message Change Amount Status
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Currency From Currency To Exchange Rate Pending Rate Year Actions
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Reporting ID Reporting Name Customer ID Actions
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SQL Query Configuration

Manage all SQL queries used across the application

Widget Configuration

Configure dashboard widgets and their properties

Table Configuration

Manage table structures and data sources

Slider Configuration

Configure date range sliders and filters

Click Event Configuration

Manage click handlers and event bindings

API Endpoint Configuration

Configure backend API endpoints and their parameters

ARR Calculations

Annual Recurring Revenue (ARR) is calculated by multiplying monthly recurring revenue by 12. This provides a standardized view of recurring revenue on an annual basis.

  • Formula: ARR = MRR ร— 12
  • Currency: All values converted to USD
  • Aggregation: Summed by customer and product
  • Frequency: Updated monthly

DB Month Definition

DB Month represents the database month for which the ARR data is calculated and stored.

  • Format: YYYY-MM-DD (first day of month)
  • Purpose: Time-based data organization
  • Granularity: Monthly snapshots
  • Retention: Historical data maintained

Aggregation Methods

Data is aggregated at multiple levels to provide comprehensive insights.

  • Customer Level: Sum of all products per customer
  • Product Level: Sum of all customers per product
  • Time Level: Monthly, quarterly, and annual views
  • Currency Level: Converted to USD for consistency

Change Detection

Automated detection of ARR changes including upsells, downsells, churn, and price adjustments.

  • New Customer: 0 โ†’ Positive ARR
  • Churn: Positive ARR โ†’ 0
  • Upsell: โ‰ฅ10% increase
  • Downsell: โ‰ค-10% decrease

Gap Analysis

Identification and filling of artificial gaps in ARR data due to delayed billing.

  • Detection: Zero values between active streams
  • Window: 12-month lookback/lookforward
  • Filling: Last known ARR value
  • Limitation: Gaps >12 months considered churn

Data Sources

Primary data sources and integration points for ARR analytics.

  • Snowflake: Primary data warehouse
  • Unified ARR Table: Centralized ARR data
  • Customer Product Months: Monthly snapshots
  • Real-time Updates: Via scheduled tasks

Methodology & Workflows

Data Processing Workflow

  1. Extract raw ARR data from source systems
  2. Apply currency conversions to USD
  3. Aggregate by customer and product
  4. Calculate month-over-month changes
  5. Identify gaps and anomalies
  6. Generate reports and visualizations

Quality Assurance

  1. Validate data completeness
  2. Check for duplicate records
  3. Verify currency conversions
  4. Test aggregation accuracy
  5. Review change detection logic
  6. Document any anomalies

Key Definitions

ARR (Annual Recurring Revenue)

The total value of recurring revenue normalized to a one-year period. Calculated as MRR ร— 12.

MRR (Monthly Recurring Revenue)

The predictable monthly revenue generated from subscription-based customers.

Churn

When a customer's ARR drops to zero, indicating they have cancelled their subscription.

Upsell

An increase in ARR of 10% or more, indicating customer expansion or additional purchases.

Downsell

A decrease in ARR of 10% or more, indicating customer contraction or reduced purchases.

New Customer

A customer with zero ARR in the previous month but positive ARR in the current month.

Gap Analysis

Identifies and fills artificial gaps in ARR data where revenue temporarily drops to zero but resumes within the visible date range.

  • Detection Logic: Active before + Active after + Not end-of-stream
  • Visual Indicators: Orange background, bold text, distinctive border
  • Purpose: Distinguish temporary billing issues from actual churn
  • Animation: 3-second visual confirmation when applied

Change Tracking

Monitors month-over-month ARR changes to identify significant business events and customer behavior patterns.

  • Upsell: ARR increase โ‰ฅ10% month-over-month
  • Downsell: ARR decrease โ‰ฅ10% month-over-month
  • Churn: ARR drops to zero (complete cancellation)
  • New Customer: ARR increases from zero to positive

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Total Revenue

$0.00

+0.0%

Active Customers

0

+0

Total ARR

0

+0

Growth Rate

0.0%

vs last period

Financial Revenue Report

Date Customer Department Class Subsidiary Business Unit Account Number Account Name Split Item Name Amount Currency Exchange Rate Service Start Date Service End Date Source Rev Entity Source Rev Amount Entity (Line)

Total Customers

0

Total TCV

$0

Total ARR

0

Avg Transaction Value

$0

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Total Opportunities
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Pipeline Value
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Win Rate
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Avg Deal Size

๐Ÿ“Š Pipeline Health Analytics

๐Ÿš€ Pipeline Progression & Regression

๐Ÿ“Š Product Breakdown

โฑ๏ธ Stage Velocity

๐ŸŽฏ Forecast Accuracy

๐Ÿ” Pipeline Funnel

๐Ÿ’ฐ Revenue & Performance Analytics

๐Ÿ“ˆ Revenue Forecasting

๐Ÿ‘ฅ Rep Performance

๐Ÿ“Š Pipeline Trends

๐ŸŽฏ Pipeline Progression

๐Ÿ” Advanced Pipeline Metrics

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Progression Rate
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Regression Rate
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Avg Stage Duration
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Pipeline Coverage
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Push Frequency
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Commit Accuracy
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Pipeline Health Summary

๐Ÿ“… Latest Snapshot Only Showing data from most recent snapshot date

๐Ÿ“Š Pipeline Metrics Explanation

โฑ๏ธ Avg Days in Stage

Calculation: DATEDIFF(day, previous_stage_date, current_stage_date)

What it measures: Actual time spent in each stage based on snapshot transitions

Methodology: Uses LAG() functions to track stage changes over time from snapshot data

๐Ÿ’ฐ Pipeline Value

Calculation: SUM(amount) per stage from latest snapshot

What it measures: Total dollar value of opportunities in each stage

Data source: Latest snapshot from DATA_LAKE.SALESFORCE_ARCHIVE

๐Ÿ“ˆ Progression Rate

Calculation: (Opportunities that progressed / Total opportunities) * 100

What it measures: Percentage of opportunities that moved to next stage

Methodology: Tracks actual stage transitions using temporal snapshot analysis

๐ŸŽฏ Closure Rate

Calculation: (Opportunities that closed / Total opportunities) * 100

What it measures: Percentage of opportunities that reached Closed Won/Lost

Methodology: Based on actual stage progression tracking over time

Data Source: DATA_LAKE.SALESFORCE_ARCHIVE | Methodology: Temporal snapshot analysis with LAG() functions for stage transition tracking | Update Frequency: Real-time based on latest snapshot data

Stage Opportunities Pipeline Value Avg Deal Size Avg Days in Stage Win Probability Health Score
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