Advanced PowerBI Sales Analytics Dashboard

Preview Video Below

Features

• Measure Selector for dynamic analysis
• Conditional Formatting for better data visualization
• Bookmarks for seamless navigation
• Complex DAX Measures to generate insightful visuals
• Reset Button to clear filters easily
• Tooltips for quick insights
• Profitability Analysis to identify high-profit areas

Key Insights & Recommendations

How can we apply these insights to other markets?

• Top Improved Salespersons: Ches Bonnell & Gunar

What factors contributed to their improvement?

Were they newly hired?

How can we sustain their performance and motivate them further?

• Top 5 Salespersons: Kelci Walkedn, Rafaelite Blaksland, Husein

Consider offering incentives to maintain motivation.

Leverage their expertise—train other sales team members.

• Top Selling Products: Organic Choco Syrup & Peanut Butter Cubes

Can we bundle these with lower-performing products to boost overall sales?

• Most Profitable Products: 99% Dark & Pur, Fruit & Nuts Bar

Can we introduce a new product line with similar ingredients?

Should we invest more in marketing these products to maximize sales?

99% Dark & Pur has the highest profit margin but ranks third in sales—how can we boost its sales further?

• Sales Decline: 25.3% Drop in Canada

Identify the root cause:

Were discounts discontinued?

Did a major retailer stop carrying our products?

• Sales Growth: Notable Increase in India & New Zealand

What strategies worked here that didn’t elsewhere?

Should we replicate these strategies in other regions?

Is marketing the key driver?

• Bars Among Top-Selling Products

What strategies made bars successful?

Can we apply these strategies to boost sales of Bites?

Should we focus more on our core product line (Bars)?

• India’s Market Success: 3 of the Top 5 Selling Products Are from India

What factors contribute to their strong performance?

Measures Created

• Total Sales
• Total Boxes
• Total Shipments
• Total Costs
• Total Profit
• Profit %
• LBS Counts
• LBS %
• MoM Change for
  • Boxes Change %
  • Costs Change %
  • Profit Change %
  • Sales Change %
  • Shipments Change %
• YoY Change for
  • Boxes Change %
  • Costs Change %
  • Profit Change %
  • Sales Change %
  • Shipments Change %

Explanation of DAX

Total Cost = SUM(shipments[Costs])

This sums up all the rows of costs column in shipment table

MoM Sales Change % = 
    var this_month= [Total Sales]
    var prev_month= [Total Sales (prev month)]
return
    DIVIDE(this_month-prev_month,prev_month)

# In this dax we are calculating Month on Month Change
# Here we are defining two variables and then using that variable to calculate the change

MoM Boxes Change % = 
    var this_month= [Total Boxes]
    var prev_month= CALCULATE([Total Boxes],PREVIOUSMONTH('calendar'[Date]))
return
    DIVIDE(this_month-prev_month,prev_month)

# This is similar to above but we are calculate the previous month total boxes

Latest Date= LASTDATE('calendar'[Start of Month])

# Get Last Date of the 

Total Sales Latest Month = 
    var ld =[Latest Date]
return
    CALCULATE([Total Sales],'calendar'[Start of Month]=ld)
# Here CALCULATE function filter the total sales to include the row whichs start of month matched the Latest Date

# Latest Date measure is calculated like this 
# Latest Date = LASTDATE('calendar'[Start of Month])

Latest MoM Sales Change % = 
    var ld  = [Latest Date]
    var this_month_sales =[Total Sales Latest Month]
    var previous_month_sales=CALCULATE([Total Sales],'calendar'[Start of Month]=EDATE(ld,-1))
return
    DIVIDE(this_month_sales-previous_month_sales,previous_month_sales)

# Here we have new learning EDATE which is used to calculate date

Profit Target Indicator = IF([Profit %]>[Profit Target],2,IF([Profit %]>0.9*[Profit Target],1,0))

# To create If conditional to check whether the sales people have achieved the target