Total Sales all Regions and Channels
$3,941,901
Total Sales - Fresh Category
$1,319,554
Number of Locations
124
Average Total Sales per Location
$31,789.52
- Top Regions by Total Sales: Lisbon, Porto
- Top Channels by Total Sales: Hotel_Cafe, Retail_Store
- Total Number of Customers: 124
- Average Spending per Customer: $31,789.52
- Most Popular Product Category: Fresh
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| Channel | Fresh | Milk | Grocery | Frozen | Soap | Deli |
|---|---|---|---|---|---|---|
| Hotel_Cafe | 48% | 13.0% | 16% | 15% | 3% | 4.5% |
| Retail_Store | 14% | 21.9% | 38% | 4% | 18% | 3.4% |
| Region | Channel | Total | Fresh | Grocery | Milk | Frozen | Soap | Deli |
|---|---|---|---|---|---|---|---|---|
| Lisbon | Hotel_Cafe | $1,538,342 | $761,233 | $237,542 | $228,342 | $184,512 | $56,081 | $70,632 |
| Lisbon | Retail_Store | $848,471 | $93,600 | $332,495 | $194,112 | $46,514 | $148,055 | $33,695 |
| Porto | Hotel_Cafe | $719,150 | $326,215 | $123,074 | $64,519 | $160,861 | $13,516 | $30,965 |
| Porto | Retail_Store | $835,938 | $138,506 | $310,200 | $174,625 | $29,271 | $159,795 | $23,541 |
| Region | Total_Fresh_Sales | Total_Milk_Sales | Total_Grocery_Sales | Total_Frozen_Sales | Total_Detergents_Paper_Sales | Total_Delicassen_Sales |
|---|---|---|---|---|---|---|
| Lisbon | 854833 | 422454 | 570037 | 231026 | 204136 | 104327 |
| Porto | 464721 | 239144 | 433274 | 190132 | 173311 | 54506 |
| Region | Channel | average_spending |
|---|---|---|
| Lisbon | Hotel_Cafe | $26,073.59 |
| Lisbon | Retail_Store | $47,137.28 |
| Porto | Hotel_Cafe | $25,683.93 |
| Porto | Retail_Store | $43,996.74 |
SEGMENTATION MODEL INSIGHTS
Regional Foodies: Lisbon shows higher sales of Fresh products compared to Porto. This suggests customers there might be more interested in fresh produce. Target Lisbon customers with special offers on new or seasonal fruits and vegetables.
Big Spenders: Identify regions with a concentration of high-spending customers (based on the “Total” column). Analyze their buying habits across categories to see which product categories are most popular among top spenders. This allows for tailored promotions or offerings.
Pantry Builders: Analyze basket sizes alongside the dominant product category for each customer. Customers consistently buying Grocery items but rarely Fresh could be a target group for upselling fresh produce to complement their pantry staples.
CHANNEL CLASSIFICATION MODEL INSIGHTS
Higher spending on fresh products is associated with a decreased likelihood of belonging to certain channels.
Channels characterized by higher expenditures on detergents and paper products tend to have distinct classification patterns.
There is a baseline tendency for certain channels to have lower classification scores, irrespective of specific product spending patterns.
| Observations | 124 |
| Dependent variable | Channel.b |
| Type | OLS linear regression |
| F(2,121) | 75.72 |
| R² | 0.56 |
| Adj. R² | 0.55 |
| Est. | S.E. | t val. | p | |
|---|---|---|---|---|
| (Intercept) | -0.70 | 0.17 | -4.18 | 0.00 |
| pctFresh | -0.35 | 0.13 | -2.58 | 0.01 |
| log(Detergents_Paper) | 0.17 | 0.02 | 8.43 | 0.00 |
| Standard errors: OLS |
In this dashboard, I was able to explore and learn more about this topic:
I changed the theme of the dashboard to Superhero. This dark theme helps make the dashboard more visually appealing, as people nowadays tend to prefer darker themes.
I added a new value box displaying the Average Total Sales per Location. This additional important metric enhances the dashboard’s visualization capabilities. Additionally, working with this value box allowed me to learn about the various icons available in the dashboard.
I added a new layout in the Tables module. It was a great opportunity to get hands-on experience with the design. I added a new row with two columns to incorporate tables.
I populated the new tables with information to observe how the data and design are displayed.
I added a new tab called “Statistics,” which contains bar charts of total sales by product and a comparison of sales between regions, presented in a tabset.
Within each tabset, there is a chart and a card with information. This setup helps visualize the data and provides an explanation for each chart. It also allowed me to learn more about the design and layout of dashboards.
I added two more columns with two rows each, where I included additional tables, interpretations, and a heatmap.
I changed the business icon to a PNG image, which helped me understand how icons and images work in the dashboard.
I modified the card insights in each tab, allowing me to observe how the information affects the design of the tab and card size.
I added a new row and cluster in the Models section, enabling me to gain more knowledge about positioning designs exactly where I want them, further enhancing my hands-on experience with dashboards.
- Grocery is the clear leader in total sales, followed by Fresh and then Detergents_Paper.
- Delicassen and Frozen have the lowest total sales among the six categories.
Overall Trends:
- Grocery leads in total sales across all regions.
- Fresh and Detergents_Paper seem to hold the second and third positions in most regions.
- Delicassen and Frozen continue to have the lowest total sales in most regions.
Regional Differences:
- While Grocery dominates overall, there might be regional variations in its dominance. For instance, it appears to have a stronger lead in Lisbon compared to Porto.
- Fresh sales seem relatively higher in Lisbon compared to Porto.
- Detergents_Paper sales might be slightly higher in Porto relative to Lisbon.
| Average_Sales_Fresh | Average_Sales_Milk | Average_Sales_Grocery | Average_Sales_Frozen | Average_Sales_Detergents_Paper | Average_Sales_Delicassen | Max_Sales_Fresh | Max_Sales_Milk | Max_Sales_Grocery | Max_Sales_Frozen | Max_Sales_Detergents_Paper | Max_Sales_Delicassen | Min_Sales_Fresh | Min_Sales_Milk | Min_Sales_Grocery | Min_Sales_Frozen | Min_Sales_Detergents_Paper | Min_Sales_Delicassen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 10641.56 | 5335.468 | 8091.218 | 3396.435 | 3043.927 | 1280.911 | 56083 | 28326 | 67298 | 60869 | 38102 | 6854 | 3 | 258 | 489 | 61 | 5 | 7 |
Top Selling Category: Looking at the Average Sales figures, the category with the highest average sales is likely Fresh (around $10,641). This suggests that fresh products are a significant driver of overall revenue.
Sales Variability: The difference between Max Sales and Min Sales highlights the variability in sales performance across categories. For instance, the high difference in Grocery (Max Sales - Min Sales = $29,860 - $4897) suggests significant fluctuations in grocery sales between stores/periods. This could be due to factors like seasonal demand or targeted promotions.
Potential for Improvement: Categories with consistently low Min Sales might warrant further investigation. For example, the very low Min_Sales_Delicassen ($18) indicates that at least one store/period had very low sales in this category. This could be a sign of underperforming delicassen products or a need for better promotion within that store.
Insight 1: Potential for Cross-Selling Fresh Products with Milk and Delicassen
The heatmap shows positive correlations (blue color) between:
- Fresh and Milk (correlation coefficient of 0.8)
- Fresh and Delicassen (correlation coefficient of 0.2)
This suggests that customers who purchase Fresh products are also likely to buy Milk and Delicassen items.
Insight 2: Detergents_Paper and Frozen Might Be Relatively Independent Categories
- The heatmap shows a weak negative correlation (reddish color with a coefficient of -0.4) between Detergents_Paper and Frozen. This indicates that there’s no strong relationship between these categories. Customers buying one category aren’t necessarily more likely (or less likely) to buy the other.