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Sales Performance & Pipeline Analytics

Developed a Power BI KPI framework to track pipeline performance, bookings, and win rates with accurate alignment between snapshot data and close-date logic for consistent executive reporting.

The Problem

Sales leadership lacked a consistent and reliable view of pipeline performance and bookings. Reporting varied depending on how data was filtered, particularly when comparing current vs prior periods, leading to misalignment in decision-making.

Objective

Design a reporting framework that standardizes pipeline and bookings metrics while ensuring accurate time-based comparisons across current and prior periods.

Solution

Built a Post KPI / CPQ analytics model in Power BI that aligns snapshot-based reporting with close-date logic, delivering a consistent and trusted view of pipeline performance across reporting periods.

Technical Approach

  • Designed KPI framework for bookings, win rate, and pipeline performance

  • Leveraged snapshot fact tables to ensure historical accuracy (Post KPI / CPQ)

  • Built advanced time intelligence logic for CY vs LY comparisons

  • Designed logic to eliminate discrepancies between snapshot reporting and close-date performance views

  • Implemented disconnected date tables to control reporting windows

  • Used DAX to align ReportDate context with CloseDate behavior

  • Applied filter logic to ensure consistent executive-level reporting

Impact

  • Provided leadership with a consistent and trusted view of pipeline performance

  • Eliminated discrepancies between reporting views

  • Enabled accurate period-over-period comparisons

  • Supported data-driven decision making for sales strategy

  • Improved confidence in pipeline reporting across leadership and sales teams

Challenges & Learnings

  • Aligning snapshot-based reporting with dynamic close-date filtering

  • Managing complexity of time intelligence across multiple date contexts

  • Ensuring consistency across all reporting views and stakeholders

This project demonstrates my ability to design scalable, reliable reporting frameworks that enable confident, data-driven decision-making.

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Executive KPI dashboard highlighting win rate, conversion rate, total bookings, and key loss drivers across reporting periods.

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Regional performance trends with aligned current vs prior period comparisons using snapshot and close-date logic

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Breakdown of closed-lost revenue by reason category to identify key drivers impacting pipeline performance.

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