data-portfolio

Bike Sales Dashboard — Buyer Segmentation & Conversion Insights

Excel dashboard to identify who buys bikes and which factors drive conversion (age, commute distance, region, home ownership, etc.).

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Project Overview

• Title: Bike Sales — Buyer Persona & Conversion Drivers
• Business problem: Who are the most likely buyers (buyer personas), which factors most influence purchase (age, commute distance, region, home ownership, marital/education), and how can these insights improve targeting and campaign ROI?
• Dataset: Bike Sales Dashboard Project.xlsx → main sheet bike_buyers, 1,026 rows × 14 columns (key fields: Gender, Income, Children, Education, Occupation, Home Owner, Cars, Commute Distance, Region, Age, Age Bracket, Purchased Bike).
• Tools used: Microsoft Excel (PivotTables, Slicers, Pivot Charts, Dashboard sheet).

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Analysis Results

• Key finding 1 — Who converts most?

  • Age Bracket: Middle Age highest conversion 54.7% (vs Adolescent 36.6%, Old 31.3%).
  • Commute Distance: 2–5 Miles 58.6%, 0–1 Miles 54.8% → short–medium commutes are most likely to buy.
  • Region: Pacific 58.9% highest; Europe 49.4%; North America 43.3%.
  • Marital Status: Single 54.3% > Married 43.0%.
  • Cars: 0 car 60.2%, 1 car 57.4% → fewer cars, higher purchase likelihood.

• Key finding 2 — Buyer profile & behavior

  • Gender: nearly balanced (Female 48.5%, Male 48.0%) → gender is not a primary driver.
  • Home Owner: Non-homeowner slightly higher (49.5%) vs Homeowner 47.6%.
  • Income & Age: median Income is similar for Yes/No ($60,000), but mean is higher among buyers (~$57.5k vs $55.0k). Buyers skew younger (median 41 vs 44).

Quick KPIs

• Total records: 1,026
• Overall conversion (Purchased Bike = Yes): 48.25%
• Top segments: Middle Age, 2–5 Miles commute, Pacific, Single, 0–1 cars

Business impact:

• Targeting → focus on Middle Age with 0–5 mile commutes in Pacific/Europe; tailor creatives & channels to Single segments.
• Positioning → emphasize commute-friendly features (lightweight, practical, efficient).
• Promotions → entry bundles for buyers with no/one car; commute gear bundling.

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Dashboard & Files

• Workbook (Excel): Bike Sales Dashboard Project.xlsx

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Technical Highlights

• Data size: 1,026 × 14; key fields: Gender, Income, Children, Education, Occupation, Home Owner, Cars, Commute Distance, Region, Age, Age Bracket, Purchased Bike.
• Conversion math: conv_rate = count(Yes) / total per segment; validated with Yes+No totals.

• Descriptive splits:

  • Age Bracket → Middle Age 54.7%, Adolescent 36.6%, Old 31.3%
  • Commute → 2–5 58.6%, 0–1 54.8%, 1–2 47.2%, 5–10 39.1%, 10+ 29.2%
  • Region → Pacific 58.9%, Europe 49.4%, North America 43.3%
  • Home Owner → No 49.5%, Yes 47.6%
  • Gender → Female 48.5%, Male 48.0%

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Skills Demonstrated

Excel PivotTables & Slicers, KPI design, categorical segmentation, conversion analysis, dashboard storytelling, stakeholder-ready insight framing.

**Credit : Alex The Analyst**