Cohort analysis patterns in Tableau - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the Tableau calculation to assign each customer to their cohort month based on their first purchase date.

Tableau

DATETRUNC('month', [1])

Drag options to blanks, or click blank then click option'

A[First Purchase Date]

B[Order Date]

C[Transaction Date]

D[Signup Date]

Attempts:

3 left

💡 Hint

Common Mistakes

Using the transaction date instead of the first purchase date.

Using a date field unrelated to customer acquisition.

The cohort month is based on the customer's first purchase date, so we use First Purchase Date in the DATETRUNC function.

2fill in blank

medium

Complete the Tableau calculation to find the number of months since the cohort month for each transaction.

Tableau

DATEDIFF('month', [1], [Order Date])

Drag options to blanks, or click blank then click option'

A[Cohort Month]

B[First Purchase Date]

C[Signup Date]

D[Transaction Date]

Attempts:

3 left

💡 Hint

Common Mistakes

Using the first purchase date directly instead of the cohort month.

Using the wrong date field for comparison.

We calculate months since cohort by comparing the Cohort Month to the current order date.

3fill in blank

hard

Fix the error in this cohort retention calculation to count distinct customers who made a purchase in the current month since their cohort.

Tableau

COUNTD(IF [1] = 0 THEN [Customer ID] END)

Drag options to blanks, or click blank then click option'

A[Order Date]

B[Cohort Month]

C[Months Since Cohort]

D[First Purchase Date]

Attempts:

3 left

💡 Hint

Common Mistakes

Comparing the cohort month or order date directly to zero.

Using the wrong field that does not represent months since cohort.

The condition should check if Months Since Cohort equals zero to identify customers in their first month.

4fill in blank

hard

Fill both blanks to calculate the retention rate as the ratio of customers active in the current month to those in the cohort month.

Tableau

SUM(IF [1] >= 0 THEN 1 ELSE 0 END) / SUM(IF [2] = 0 THEN 1 ELSE 0 END)

Drag options to blanks, or click blank then click option'

A[Months Since Cohort]

B[Order Date]

D[Cohort Month]

Attempts:

3 left

💡 Hint

Common Mistakes

Using different fields for numerator and denominator.

Mixing date fields instead of months since cohort.

Retention rate compares customers active from cohort month (months since cohort = 0) to those active in current or later months (months since cohort >= 0).

5fill in blank

hard

Fill all three blanks to create a cohort retention table calculation that resets at each cohort month and calculates retention percentage.

Tableau

IF FIRST() = 0 THEN WINDOW_SUM(SUM([[1]])) / WINDOW_SUM(SUM([[2]])) ELSE PREVIOUS_VALUE(1) END * [3]

Drag options to blanks, or click blank then click option'

AActive Customers

BCohort Customers

C100

DMonths Since Cohort

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong fields for numerator or denominator.

Forgetting to multiply by 100 for percentage.

This calculation divides active customers by cohort customers, resets at each cohort, and multiplies by 100 to get a percentage.

Practice

1. What is the main purpose of cohort analysis in Tableau?

easy

A. To create pie charts for sales distribution

B. To filter data by geographic location only

C. To group users by their start time and track their behavior over time

D. To calculate total revenue without time context

Solution

1. Step 1: Understand cohort analysis concept

   Cohort analysis groups users based on when they started using a product or service.

2. Step 2: Identify its purpose in Tableau

   It tracks user behavior or retention over time, not just static metrics like revenue or location.

3. Final Answer:

   To group users by their start time and track their behavior over time -> Option C

4. Quick Check:

   Cohort analysis = group by start time and track behavior [OK]

Hint: Remember: Cohorts track groups by start time over periods [OK]

Common Mistakes:

• Confusing cohort analysis with simple filtering
• Thinking cohort analysis is only about total sales
• Ignoring the time dimension in cohort grouping

2. Which of the following calculated fields correctly defines a cohort start month in Tableau?

easy

A. DATEDIFF('day', [User Signup Date], TODAY())

B. DATEPART('year', [User Signup Date]) + 1

C. SUM([User Signup Date])

D. DATETRUNC('month', [User Signup Date])

Solution

1. Step 1: Understand cohort start date calculation

   Cohort start is usually the first day of the period, here month, so DATETRUNC('month', date) is correct.

2. Step 2: Evaluate each option

   Calculating days to today gives elapsed time, not the start month; adding 1 to the year part shifts cohorts incorrectly; summing dates is invalid.

3. Final Answer:

   DATETRUNC('month', [User Signup Date]) -> Option D

4. Quick Check:

   Start month = DATETRUNC('month', date) [OK]

Hint: Use DATETRUNC to get cohort period start date [OK]

Common Mistakes:

• Using DATEPART instead of DATETRUNC for cohort start
• Calculating date differences instead of truncating
• Applying aggregation functions on dates incorrectly

3. Given the cohort start month calculated as DATETRUNC('month', [Signup Date]) and the current month as DATETRUNC('month', TODAY()), what does this calculation return?
DATEDIFF('month', DATETRUNC('month', [Signup Date]), DATETRUNC('month', TODAY()))

medium

A. The number of days since the user signed up

B. The number of months since the user signed up

C. The user's signup date truncated to the day

D. The total count of users signed up this month

Solution

1. Step 1: Analyze the DATEDIFF function

   DATEDIFF('month', start, end) returns the number of whole months between two dates.

2. Step 2: Apply to given dates

   It calculates months between the user's signup month and the current month, showing how many months have passed.

3. Final Answer:

   The number of months since the user signed up -> Option B

4. Quick Check:

   DATEDIFF('month', signup, today) = months since signup [OK]

Hint: DATEDIFF with 'month' counts months between dates [OK]

Common Mistakes:

• Confusing months with days in DATEDIFF
• Thinking it returns a date instead of a number
• Assuming it counts users instead of time difference

4. You created a calculated field for cohort period as:
DATEDIFF('month', [Cohort Start], [Order Date])
but the results show negative values. What is the most likely cause?

medium

A. [Order Date] is earlier than [Cohort Start], causing negative differences

B. The DATEDIFF function does not support 'month' as an interval

C. The calculation should use DATEADD instead of DATEDIFF

D. [Cohort Start] is not a date field but a string

Solution

1. Step 1: Understand DATEDIFF behavior

   DATEDIFF returns negative values if the first date is after the second date.

2. Step 2: Check date order in calculation

   If [Order Date] is before [Cohort Start], the difference is negative, which explains the issue.

3. Final Answer:

   [Order Date] is earlier than [Cohort Start], causing negative differences -> Option A

4. Quick Check:

   Negative DATEDIFF means first date > second date [OK]

Hint: Check date order: earlier date first to avoid negatives [OK]

Common Mistakes:

• Assuming DATEDIFF can't use 'month' interval
• Confusing DATEDIFF with DATEADD function
• Not verifying data types of date fields

5. You want to create a heatmap in Tableau showing user retention by cohort month and months since signup. Which combination of fields and visualization best achieves this?

hard

A. Rows: Cohort Month (DATETRUNC), Columns: Months Since Signup (DATEDIFF), Color: Count of Users

B. Rows: User ID, Columns: Signup Date, Color: Total Sales

C. Rows: Order Date, Columns: Product Category, Color: Average Price

D. Rows: Months Since Signup, Columns: Total Revenue, Color: Cohort Month

Solution

1. Step 1: Identify correct cohort and period fields

   Cohort Month groups users by signup month; Months Since Signup tracks time elapsed.

2. Step 2: Choose visualization layout

   Heatmap uses rows and columns for cohort and period, color shows user counts for retention.

3. Final Answer:

   Rows: Cohort Month (DATETRUNC), Columns: Months Since Signup (DATEDIFF), Color: Count of Users -> Option A

4. Quick Check:

   Heatmap = cohort by period with user count color [OK]

Hint: Heatmap axes: cohort start and months since signup, color by users [OK]

Common Mistakes:

• Using unrelated fields like product category or revenue
• Placing total revenue on columns instead of cohort period
• Not using count of users for color intensity