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Pipeline Value Growth

Definition

Pipeline Value Growth measures the increase in total dollar value of open sales opportunities over a specific period. It helps track pipeline health, deal velocity, and the impact of GTM efforts on revenue generation.

Description

Pipeline Value Growth is a key indicator of revenue momentum and GTM effectiveness, reflecting how your pipeline is expanding over time via new deals, stage progress, or expansion paths.

The relevance and interpretation of this metric shift depending on the model or product:

  • In outbound-led sales, it reflects SDR/AE volume and demo-to-opportunity effectiveness
  • In PLG-assisted sales, it includes usage-based triggers creating new deal opportunities
  • In mid-market or enterprise, it reflects relationship depth and solution maturity

An increasing trend suggests strong demand gen, solid qualification, and larger deal sizes. A plateau or decline may indicate misaligned messaging, campaign fatigue, or poor lead fit. By segmenting by cohort — such as channel, ICP tier, vertical, or campaign source — you can uncover targeting gaps, sales coverage needs, or pipeline maturity signals.

Pipeline Value Growth informs:

  • Strategic decisions, like GTM scaling or lead source expansion
  • Tactical actions, such as prioritizing fast-moving accounts or reallocating SDR effort
  • Operational improvements, including win-back cadences and playbook testing
  • Cross-functional alignment, by connecting signals across PMM, sales, demand gen, and RevOps to support conversion-centric pipeline growth

Key Drivers

These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome

  • Top-of-Funnel Acceleration: If MQLs or SQLs grow, pipeline value usually follows.
  • Deal Sourcing Mix (Inbound vs. Outbound): Outbound tends to drive higher value, inbound drives volume.
  • Sales Enablement and Productivity: Reps who’re enabled with content, tools, and context build better pipeline faster.

Improvement Tactics & Quick Wins

Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.

  • If growth is flat, review deal source performance — scale what drives both volume and value.
  • Add a quarterly pipeline-generation target alongside quota.
  • Run a test with vertical-specific outbound campaigns tied to pain-point messaging.
  • Refine SDR and AE collaboration plays to prioritize mid-market and enterprise tiers.
  • Partner with marketing to map content to pipeline creation velocity by stage.

  • Required Datapoints to calculate the metric


    • Total Pipeline Value at Start of Period
    • Total Pipeline Value at End of Period
    • Timeframe (e.g., month, quarter)
    • Opportunity Stage and Deal Owner (optional)
  • Example to show how the metric is derived


    • Q1 starting pipeline: $2.8M
    • Q1 ending pipeline: $3.6M
    • Formula: ($3.6M − $2.8M) ÷ $2.8M = 28.6% Pipeline Value Growth

Formula

Formula

\[ \mathrm{Pipeline\ Value\ Growth} = \left( \frac{\mathrm{Pipeline\ Value\ End} - \mathrm{Pipeline\ Value\ Start}}{\mathrm{Pipeline\ Value\ Start}} \right) \times 100 \]

Data Model Definition

How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.

cube('PipelineValueGrowth', {
  sql: `SELECT * FROM pipeline_value_growth`,

  measures: {
    totalPipelineValueStart: {
      sql: `total_pipeline_value_start`,
      type: 'sum',
      title: 'Total Pipeline Value at Start of Period',
      description: 'Total dollar value of open sales opportunities at the start of the period.'
    },

    totalPipelineValueEnd: {
      sql: `total_pipeline_value_end`,
      type: 'sum',
      title: 'Total Pipeline Value at End of Period',
      description: 'Total dollar value of open sales opportunities at the end of the period.'
    },

    pipelineValueGrowth: {
      sql: `${totalPipelineValueEnd} - ${totalPipelineValueStart}`,
      type: 'number',
      title: 'Pipeline Value Growth',
      description: 'Increase in total dollar value of open sales opportunities over a specific period.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true,
      title: 'ID',
      description: 'Unique identifier for each record.'
    },

    timeframe: {
      sql: `timeframe`,
      type: 'time',
      title: 'Timeframe',
      description: 'Time period for the pipeline value measurement, e.g., month or quarter.'
    },

    opportunityStage: {
      sql: `opportunity_stage`,
      type: 'string',
      title: 'Opportunity Stage',
      description: 'Stage of the sales opportunity.'
    },

    dealOwner: {
      sql: `deal_owner`,
      type: 'string',
      title: 'Deal Owner',
      description: 'Owner of the sales opportunity.'
    }
  }
});

Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema


Positive & Negative Influences

  • Negative influences


    Factors that drive the metric in an undesirable direction, often signaling risk or decline.

    • Lead Quality: Poor lead quality can result in lower conversion rates, negatively affecting pipeline value growth.
    • Sales Cycle Length: Longer sales cycles can delay the conversion of opportunities, hindering pipeline value growth.
    • Market Conditions: Adverse market conditions can reduce the number of opportunities and their value, negatively impacting pipeline growth.
    • Resource Allocation: Inefficient allocation of resources can lead to missed opportunities and lower pipeline value.
    • Competitive Pressure: Increased competition can reduce win rates and deal sizes, negatively affecting pipeline value growth.
  • Positive influences


    Factors that push the metric in a favorable direction, supporting growth or improvement.

    • Top-of-Funnel Acceleration: An increase in MQLs or SQLs typically leads to a higher pipeline value as more qualified leads enter the sales process.
    • Deal Sourcing Mix (Outbound): Outbound efforts often result in higher value deals, which can significantly boost pipeline value growth.
    • Sales Enablement and Productivity: Enhanced sales enablement and productivity allow sales reps to build pipeline more effectively, increasing the overall pipeline value.
    • Deal Velocity: Faster deal velocity means quicker conversion of opportunities, contributing to pipeline value growth.
    • GTM Efforts: Effective go-to-market strategies can enhance the quality and quantity of opportunities, positively impacting pipeline value growth.

Involved Roles & Activities


Funnel Stage & Type

  • AAARRR Funnel Stage


    This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:

    Revenue

  • Type


    This KPI is classified as a Lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.


Supporting Leading & Lagging Metrics

  • Leading


    These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.

    • Deal Velocity: Deal Velocity measures how quickly deals move through the sales pipeline and is a leading indicator of Pipeline Value Growth. Increases in deal velocity suggest that opportunities are advancing faster, which typically precedes and drives increases in the total pipeline value and its growth over time.
    • Product Qualified Leads: Product Qualified Leads (PQLs) represent users who have demonstrated strong intent and engagement, indicating a high likelihood of becoming sales opportunities. Growth in PQLs signals a future increase in pipeline value, as more high-quality leads are likely to enter the pipeline and contribute to its expansion.
    • Sales Pipeline Growth: Sales Pipeline Growth directly precedes Pipeline Value Growth, as it tracks the increase in the total value, volume, or number of opportunities in the pipeline. A surge in pipeline growth generally forecasts higher subsequent pipeline value growth, making it a foundational leading signal.
    • SQL-to-Opportunity Conversion Rate: SQL-to-Opportunity Conversion Rate reflects the effectiveness of moving Sales Qualified Leads into the opportunity stage. A higher conversion rate means more deals are entering the pipeline, thus driving future increases in pipeline value growth.
    • Pipeline Value: Pipeline Value is the current total potential revenue in the pipeline. Increases in this metric act as a leading indicator for Pipeline Value Growth, as higher pipeline value today typically leads to measurable growth in the next period.
  • Lagging


    These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.

    • Conversion Rate: Conversion Rate quantifies how effectively pipeline opportunities turn into closed deals or desired outcomes. Tracking this helps confirm the impact of pipeline value growth on actual business results, validating whether increases in pipeline value translate into revenue or other key outcomes.
    • Net Revenue Retention: Net Revenue Retention measures the ability to retain and expand revenue from existing customers, confirming if pipeline value growth is contributing to sustainable business growth and downstream revenue impact.
    • Average Deal Size: Average Deal Size amplifies the impact of Pipeline Value Growth by quantifying whether increased pipeline value is due to larger deals or simply more deals. It explains the broader business impact of pipeline growth on potential revenue.
    • Revenue Growth: Revenue Growth is a lagging metric that quantifies the real impact of pipeline value growth on company revenue. Increases in pipeline value should eventually be reflected here, providing confirmation of the pipeline's business impact.
    • Customer Acquisition Cost: Customer Acquisition Cost (CAC) can be used to explain the efficiency of Pipeline Value Growth. If pipeline value grows but CAC also increases disproportionately, it may indicate inefficiencies or future risks, helping to contextualize the business impact after the fact.