Key influencers visual in Power BI - Real Business Scenario

Scenario Mode

👤 Your Role: You are a sales analyst at a retail company.

📋 Request: Your manager wants to understand what factors influence whether a customer spends more than $500 in a single purchase.

📊 Data: You have a dataset with customer purchase records including Customer ID, Age, Gender, Product Category, Purchase Amount, and Store Location.

🎯 Deliverable: Create a Key influencers visual in Power BI that shows which factors most affect high purchase amounts (above $500).

Sample Data

Customer ID	Age	Gender	Product Category	Purchase Amount	Store Location
C001	25	Female	Electronics	650	Downtown
C002	40	Male	Clothing	120	Suburb
C003	33	Female	Home	540	Downtown
C004	29	Male	Electronics	300	Suburb
C005	50	Female	Clothing	700	Downtown
C006	45	Male	Home	200	Suburb
C007	38	Female	Electronics	800	Downtown
C008	22	Male	Clothing	150	Suburb
C009	31	Female	Home	480	Downtown
C010	27	Male	Electronics	520	Suburb

1

Step 1: Add a new calculated column to classify purchases as 'High' if Purchase Amount is greater than 500, otherwise 'Low'.

High Purchase = IF('Table'[Purchase Amount] > 500, "High", "Low")

Expected Result

A new column 'High Purchase' with values 'High' or 'Low' for each row.

2

Step 2: Open Power BI Desktop and load the dataset including the new 'High Purchase' column.

Load data from source with the calculated column included.

Expected Result

Dataset loaded with all columns including 'High Purchase'.

3

Step 3: Insert a Key influencers visual from the Visualizations pane.

Select 'Key influencers' visual icon.

Expected Result

Blank Key influencers visual appears on the report canvas.

4

Step 4: Set the 'Analyze' field to the 'High Purchase' column to analyze what influences high spending.

Drag 'High Purchase' to the Analyze field well.

Expected Result

Visual is ready to analyze factors influencing 'High Purchase'.

5

Step 5: Add 'Age', 'Gender', 'Product Category', and 'Store Location' to the 'Explain by' field well.

Drag 'Age', 'Gender', 'Product Category', 'Store Location' to Explain by.

Expected Result

Visual shows key influencers for high purchase amounts based on these fields.

6

Step 6: Review the Key influencers visual to identify which factors most increase the chance of a high purchase.

Observe the ranked influencers and their impact scores.

Expected Result

Visual displays top influencers such as Product Category = Electronics and Age group.

Final Result

Key Influencers Visual
----------------------
Target: High Purchase (High/Low)

Top Influencers:
1. Product Category = Electronics (Increases chance by 60%)
2. Age between 30-40 (Increases chance by 45%)
3. Store Location = Downtown (Increases chance by 40%)
4. Gender = Female (Increases chance by 30%)

✓Customers buying Electronics are more likely to spend over $500.

✓Customers aged 30 to 40 tend to have higher purchase amounts.

✓Purchases made at Downtown stores have higher spending.

✓Female customers show a higher chance of high purchase amounts.

Bonus Challenge

Create a slicer for 'Store Location' and observe how key influencers change when filtering by each location.

Show Hint

Add a slicer visual with 'Store Location' and interact with the Key influencers visual to see dynamic changes.