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p_04 · Real Estate

Real Estate Brokerage Analytics

Profitability and client segmentation model that identified 30% of total revenue tied to NPAs, plus property performance and sales trends across verticals.

  • SQL
  • Power BI
  • DAX

01 / Problem

Leadership needed to see where brokerage revenue really came from and how much of it was at risk in non-performing assets.

02 / Data

  • Transaction-level brokerage records: sale count, area, property value, brokerage booked, received and pending, third party payouts, lead source and team.

03 / Approach

  • SQL to shape the transaction data, a Power BI model with DAX measures on top.
  • A brokerage waterfall from booked to net-to-company and RM revenue.
  • Pages for brokerage, team, accrued brokerage, sales, projects, received brokerage, lead origin, expiry dates and deleted transactions.

  1. stage_1

    SQL

    Transaction data

  2. stage_2

    Power BI model

    DAX measures

  3. stage_3

    Report

    9 navigable pages

04 / Live dashboard

preview · power bi

Open in Power BI(opens in a new tab)
Real estate analytics Power BI report with brokerage KPIs, team and lead source charts and a project table
Open full dashboard(opens in a new tab)

05 / Business impact

  • Identified 30% of total revenue tied to NPAs.
  • Property performance and sales trend analytics across multiple verticals.

06 / Tools

  • SQL
  • Power BI
  • DAX
Next projectStock Brokerage Analytics