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TechVantage CRM Sales Analysis — SQL Case Study

A SQL-only analysis of a ~8,800-row CRM sales pipeline for a fictional B2B hardware company, TechVantage Solutions. Built as a business analytics training exercise: 20 queries answering deal performance, agent productivity, revenue trends, and product success questions, using only SELECT, WHERE, GROUP BY, HAVING, CASE, aggregates, and non-correlated subqueries — no joins, CTEs, or window functions.

Dataset: Maven Analytics — CRM Sales Opportunities (4 tables: sales_pipeline, accounts, products, sales_teams)

Repo contents

Path Description
sql/queries.sql All 20 queries, schema/table creation, and data load script
docs/business_insights_report.docx Written summary of 5 key business insights, in plain English
docs/crm_query_outputs.docx Exported results/screenshots for each query

Key metrics

Metric Value
Total opportunities 8,800
Won deals 4,238 (48.2%)
Lost deals 2,473 (28.1%)
Active deals 2,089 (23.7%)
Total revenue (Won) $10,005,534
Average deal value (Won) $2,360.91
Avg days to close ~52 days
Top agent by wins Darcel Schlecht — 349 wins
Top product by revenue GTXPro — $3,510,578
Largest client sector Retail — 17 accounts

Five key findings

  1. One agent dominates the team — Darcel Schlecht leads all 30 agents with 349 Won deals and $1.15M in revenue, more than double the next-closest agent.
  2. GTXPro is the revenue engine — it drives ~35% of total Won revenue, far ahead of the second-place product.
  3. A 48% win rate, but a 28% loss rate — nearly 1 in 3 closed deals is lost, representing an estimated $580K in recoverable revenue if 10% of losses convert.
  4. ~52-day average close time — useful as a benchmark for flagging stalled deals; a data quality anomaly was also found (all closures grouped under one year).
  5. Retail, Medical, and Technology lead client sectors — the only three sectors with more than 10 accounts each, alongside a data quality note ('technolgy' typo in the sector field).

Full detail and business recommendations are in docs/business_insights_report.docx.

Tools used

MySQL 9.7 · Standard SQL (SELECT, GROUP BY, HAVING, CASE, subqueries, date/string functions)


For educational use only. Dataset source: Maven Analytics Data Playground.

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SQL case study analyzing an 8,800-row B2B CRM sales pipeline — deal performance, agent productivity, revenue trends, and product success, using SELECT, GROUP BY, CASE, and subqueries.

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