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Auction analysis from Kaggle

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Auction analysis for usedcars dataset from Kaggle

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Auction analysis from Kaggle

  1. 1. Auction Analysis SARANG ANANDA RAO
  2. 2. Executive Summary Bad Buys tend to increase with Vehicle Age and Warranty Cost Bad Buys are much higher with low Current Retail Average Price and Current Auction Clean Price($4000-6000) SUVs, Compact and Sports Vehicles are more likely to be Bad Buys Bad Buys increase with higher Vehicle Odometer Readings
  3. 3. Problem Solving Approach Current State Kicked vehicles are vehicles which are bought in auction that have mechanical problems that prevent it to be sold to customers The client has 14% bad buys of vehicles from auctions The client wants to minimize the bad buys so that the losses from the auction can be minimized Complication • Identify the traits of kicked vehicles so that losses can be minimized in the future Desired Future State • Traits of kicked vehicles are identified • The client is able to maximize good buys from the auctions
  4. 4. Bad Buys increase with increase in Vehicle Age and Warranty Cost 0.00 0.10 0.20 0.30 0.40 0.50 1 2 3 4 5 6 7 8 9 Ratio of bad buys Vehicle Age(in years) Ratio of buys by Vehicle Age 0 5 10 15 20 0 0.5 1 1.5 2 1 2 3 4 5 6 7 8 9 Good Buys(in thousands) Bad Buys(in thousands) Vehicle Age(in years) Buys by Vehicle Age Bad Buy Good Buy 0 1 2 3 4 5 6 7 0 0.2 0.4 0.6 0.8 1 401-500 501-600 601-700 701-800 801-900 901-1000 1001-1100 1101-1200 1201-1300 1301-1400 1401-1500 1501-1600 1601-1700 1701-1800 1801-1900 1901-2000 2001-2100 2101-2200 Good Buys(in thousands) Bad Buys(in thousands) Warranty Cost(in $) Buys by Warranty Cost Bad Buys Good Buys 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Ratio of Bad Buys to Good Buys Warranty Cost(in $) Ratio of Buys by Warranty Cost
  5. 5. Bad Buys increase with lower Current Retail Price and Current Auction Clean Price 0 5 10 15 20 0 0.5 1 1.5 2 2.5 Good Buy(in thousands) Bad Buy(in thosands) Current Retail Average Price(in $) Buys by Current Retail Average Price Bad Buy Good Buy 0.00 0.05 0.10 0.15 0.20 0.25 4000-6000 6000-8000 8000-1000 10000-1200012000-1400014000-16000 Ratio of bad buys to good buys Current Retail Average Price(in $) Ratio of buys by Current Retail Average Price 0 2 4 6 8 10 12 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Good Buy(in thousands) Bad Buy(in thousands) Current Auction Clean Price( in $) Buys by Current Auction Clean Price Bad Buy Good Buy 0.00 0.05 0.10 0.15 0.20 0.25 Ratio of bad buys to good buys Current Auction Clean Price(in $) Ratio of buys by Current Auction Clean Price
  6. 6. SUVs have higher chances of Bad Buys while Bad Buys increase with higher Odometer readings 0.00 0.05 0.10 0.15 0.20 0.25 COMPACT CROSSOVER LARGE LARGE SUV LARGE TRUCK MEDIUM MEDIUM SUV SMALL SUV SMALL TRUCK SPECIALTY SPORTS VAN Ratio of bad buys to good buys Average Vehicle Size Buys by Vehicle Size 0 5 10 15 20 25 0 0.5 1 1.5 2 2.5 3 3.5 50000-60000 60000-70000 70000-80000 80000-9000090000-100000 Good Buy(in thousands) Bad Buy(in thousands) Vehicle Odometer Readings(in miles) Buys by Vehicle Odometer Readings Bad Buy Good Buy 0.00 0.05 0.10 0.15 0.20 0.25 50000-60000 60000-70000 70000-80000 80000-90000 90000-100000 Ratio of Bad Buys to Good Buys Vehicle Odometer Readings(in miles) Buys by ratio of bad buys to good buys
  7. 7. Certain Makers and Models are more likely to be Bad Buys Ford FocusNissan Maxima Oldsmobile Bravada Chevrolet Colorado Cooper Mini Pontiac Grand Mazda Protege Hyundai XG 300 Lincoln Aviator Mercury Mountaineer Models that are likely to be Bad Buys Makers that are likely to be Bad Buys

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