Bead Necklace charts for product performance and mix analysis

Benefits of Product Mix Analysis

This bead necklace chart provides detailed and actionable insights, to better understand the mix of each of the brands/retailers (price distribution) for a specific product hierarchy (SKU in this case), what are the top performing SKUs (with more sales), and if their sales are decreasing or increasing.

How to Read the Bead Necklace Chart

The x axis represents the price sold for each of the SKUs. The color represents the % change vs. the previous period. The bubble size represents the total POS sales for each SKU.







Ingredients: Product Mix Analysis 

(see list of preferred vendors)

  • Point of Sale data at the appropriate level of detail
  • Advanced data visualization software

Excel raw data

Raw data

Tableau Workbook

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Insights Examples: Product Mix Analysis

In the sheet “Analysis by Brand”:

  • Brand 3 has the better mix of products (most sales in higher price-point), while Brand 5 has the worst.
  • Brand 1 has been improving considerably in the $69 to $75 price point range.
  • Most of the sales of Brand 2 are between $54 and $59; it has some opportunities to expand the product line into different price points.

What other insights can you generate from this sheet, and the other ones? Leave comments below to share your additional insights.

Common Questions: Product Mix Analysis

  • Q: Why is the color midpoint not at zero, causing the SKUs with sales decreases, to still be blue?
    • A: The overall category is down; therefore most of the color midpoint needs to be adjusted. If the color midpoint is defined as zero, then most of the data points would be orange, therefore limiting the visual impact. This set-up allows the user to easily detect the SKUs that are performing better than their peers, not just the ones that have positive growth vs. the previous period.
  • Q: Why the name “Bead Necklace” chart?
    • A: We are not aware of this chart being named before, and it look like a “Bead Necklace.”

Want so share your own  visualization for this data? Use the comments section below.