Who are your customers?

Analyzing Data in Tableau

Sara Billen

Curriculum Manager, Data Camp

Investigating "Who"

Person riding though town on a Divvy bike

Analyzing Data in Tableau

Divvy dataset: trips table

  • Trips taken between Jan - June, 2019
  • trip id: ID attached to each trip
  • bikeid: ID attached to each bike
  • tripduration: time of trip in seconds
  • starttime: day and time trip started (CST)
  • endtime:day and time trip ended (CST)
  • from station id: station ID of trip start
  • from_station_name: station name of start
  • to station id: station ID of trip end

Icon of a map showing a path from one point to another

  • to station name: station name of end
  • usertype: customer or subscriber
  • birthyear: birth year of rider
  • gender: gender of rider
Analyzing Data in Tableau

Divvy dataset: trips table

Icon of a map showing a path from one point to another

$$

  • usertype: subscriber or customer
  • birthyear: birth year of rider
  • gender: gender of rider
Analyzing Data in Tableau

User types

Subscribers

  • Commuters
  • Share personal information
  • gender and birthyear

Customers

  • Tourists
  • Don't share personal information
  • null values

$$

Note: Subscribers can cancel their subscription and become customers. In that case, the Gender and Birthyear information will be kept.

Analyzing Data in Tableau

Missing values

  • Known reason behind the missing information
  • Retitle those labels
  • Increase the available insights from the data

Puzzle with one missing piece

Analyzing Data in Tableau

Example

$$

Usertype Gender Birthyear
Subscriber Female 1993
Subscriber Male 1964
Customer Null Null
Customer Female 1987

$$

Usertype Gender Birthyear
Subscriber Female 1993
Subscriber Male 1964
Customer Day Pass Riders Day Pass Riders
Customer Female 1987
Analyzing Data in Tableau

Let's practice!

Analyzing Data in Tableau

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