Dashboard creation for marketing KPIs in Digital Marketing - Mini Project: Build & Apply

Dashboard creation for marketing KPIs

📖 Scenario: You are a marketing analyst tasked with creating a simple dashboard to track key marketing performance indicators (KPIs) for your team. The dashboard will help visualize important metrics like website visits, conversion rates, and social media engagement.

🎯 Goal: Build a basic dashboard structure that organizes marketing KPIs clearly and allows easy updates of the data.

📋 What You'll Learn

Create a data structure to hold marketing KPIs with exact values

Add a configuration variable for a target goal for one KPI

Use a loop or comprehension to prepare KPI display data

Complete the dashboard layout with final labels and structure

💡 Why This Matters

🌍 Real World

Marketing teams use dashboards to monitor campaign performance and make data-driven decisions quickly.

💼 Career

Skills in organizing and presenting marketing KPIs are essential for roles like marketing analyst, digital marketer, and data specialist.

1

Set up the marketing KPIs data

Create a dictionary called marketing_kpis with these exact entries: 'Website Visits': 12000, 'Conversion Rate': 3.5, 'Social Media Engagement': 4500

Digital Marketing

# Create the marketing_kpis dictionary with the exact KPI values
# Your code here

Hint

Use a dictionary with keys as KPI names and values as their numbers.

2

Add a target goal for Conversion Rate

Create a variable called conversion_target and set it to 4.0 to represent the target conversion rate percentage.

Digital Marketing

marketing_kpis = {
    'Website Visits': 12000,
    'Conversion Rate': 3.5,
    'Social Media Engagement': 4500
}
# Create the conversion_target variable with value 4.0
# Your code here

Hint

This variable will help compare actual conversion rate to the target.

3

Prepare KPI display data with status

Create a new dictionary called kpi_status using a dictionary comprehension. For each KPI in marketing_kpis, set the value to 'On Track' if the KPI is not 'Conversion Rate' or if its value is greater than or equal to conversion_target. Otherwise, set it to 'Needs Improvement'.

Digital Marketing

marketing_kpis = {
    'Website Visits': 12000,
    'Conversion Rate': 3.5,
    'Social Media Engagement': 4500
}
conversion_target = 4.0
# Create kpi_status dictionary with status based on conversion_target
# Your code here

Hint

Use a dictionary comprehension with a condition checking the KPI name and value.

4

Complete the dashboard layout structure

Create a list called dashboard_layout that contains strings combining each KPI name, its value from marketing_kpis, and its status from kpi_status in this exact format: "KPI: [KPI Name], Value: [Value], Status: [Status]" for all KPIs.

Digital Marketing

marketing_kpis = {
    'Website Visits': 12000,
    'Conversion Rate': 3.5,
    'Social Media Engagement': 4500
}
conversion_target = 4.0
kpi_status = {kpi: ('On Track' if (kpi != 'Conversion Rate' or value >= conversion_target) else 'Needs Improvement') for kpi, value in marketing_kpis.items()}
# Create dashboard_layout list with formatted KPI strings
# Your code here

Hint

Use a list comprehension with f-strings to format each KPI's display line.

Practice

1. What is the main purpose of a marketing KPI dashboard?

easy

A. To create complex formulas for data analysis only

B. To store raw marketing data without visualization

C. To display key marketing numbers clearly in one place

D. To replace all marketing reports with text summaries

Solution

1. Step 1: Understand the role of a dashboard

   A dashboard is designed to show important information clearly and quickly.

2. Step 2: Identify the main function in marketing context

   Marketing KPI dashboards focus on showing key numbers in one place for easy review.

3. Final Answer:

   To display key marketing numbers clearly in one place -> Option C

4. Quick Check:

   Dashboard = Clear key numbers [OK]

Hint: Dashboards summarize key info visually [OK]

Common Mistakes:

• Confusing dashboards with raw data storage
• Thinking dashboards only store data without visuals
• Assuming dashboards replace all reports with text

2. Which of the following is the correct way to add a filter for 'Date' in a marketing dashboard tool?

easy

A. Create a text box with date values

B. Write a SQL query to delete dates from the data

C. Use a pie chart to show dates

D. Add a slicer visual and connect it to the Date field

Solution

1. Step 1: Identify how filters work in dashboards

   Filters let users select data subsets, often using slicers connected to fields.

2. Step 2: Choose the correct method for date filtering

   Adding a slicer visual connected to the Date field allows interactive filtering by date.

3. Final Answer:

   Add a slicer visual and connect it to the Date field -> Option D

4. Quick Check:

   Filter by slicer on Date [OK]

Hint: Use slicers for interactive filters [OK]

Common Mistakes:

• Deleting data instead of filtering
• Using pie charts to filter data
• Using text boxes instead of filter controls

3. Given a dashboard showing total website visits by channel, if the data is: Organic=5000, Paid=3000, Referral=2000, what will the pie chart show for Paid visits percentage?

medium

A. 30%

B. 25%

C. 50%

D. 20%

Solution

1. Step 1: Calculate total visits

   Total = 5000 (Organic) + 3000 (Paid) + 2000 (Referral) = 10000 visits.

2. Step 2: Calculate Paid visits percentage

   Paid % = (3000 / 10000) * 100 = 30%.

3. Final Answer:

   30% -> Option A

4. Quick Check:

   Paid visits = 30% of total [OK]

Hint: Divide part by total, multiply by 100 [OK]

Common Mistakes:

• Adding percentages instead of calculating
• Using wrong total for percentage
• Confusing counts with percentages

4. You created a dashboard but the filter for 'Campaign' does not change the charts. What is the most likely cause?

medium

A. The data source is offline

B. The filter is not connected to the data model

C. The dashboard has too many visuals

D. The charts are using the wrong color scheme

Solution

1. Step 1: Understand filter connections

   Filters must be linked to the data model fields used in visuals to affect them.

2. Step 2: Identify why filter has no effect

   If the filter is not connected properly, selecting values won't update charts.

3. Final Answer:

   The filter is not connected to the data model -> Option B

4. Quick Check:

   Filter connection missing = no effect [OK]

Hint: Check filter connections to data fields [OK]

Common Mistakes:

• Blaming colors for filter issues
• Assuming too many visuals cause filter failure
• Ignoring filter-data model link

5. You want to create a dashboard showing monthly revenue and conversion rate by marketing channel with a filter for last 6 months. Which combination is best?

hard

A. Use a line chart for monthly revenue, a card for conversion rate, and a date slicer for last 6 months

B. Use a pie chart for monthly revenue, a table for conversion rate, and no filter

C. Use a bar chart for total revenue only, a text box for conversion rate, and a filter for all time

D. Use a scatter plot for revenue and conversion, and a slicer for last year

Solution

1. Step 1: Choose visuals matching data types

   Line charts show trends over time well; cards highlight single KPIs like conversion rate.

2. Step 2: Select appropriate filter for time range

   A date slicer filtered to last 6 months allows focused analysis on recent data.

3. Final Answer:

   Use a line chart for monthly revenue, a card for conversion rate, and a date slicer for last 6 months -> Option A

4. Quick Check:

   Visuals + filter match data needs [OK]

Hint: Match chart type to data and add time slicer [OK]

Common Mistakes:

• Using pie charts for time series data
• Not adding time filters
• Choosing visuals that don't highlight KPIs clearly