Hello my name is Christopher.
In this video presentation, the subject is Retail Analysis.
The source material content originates from Microsoft Power BI blog article - by Michele Hart
The Retail Analysis industry sample dashboard and underlying report analyse
retail sales data illustrates items sold across multiple stores and districts.
The metrics compare this year’s performance to last year’s in these areas:
sales, units, gross margin, and variance, as well as new store analysis.
This is real data from obviEnce (www.obvience.com) that has been anonymised.
I’ll start by showing you the dashboard and open the report
1.On the dashboard, I’ll select the "Total Stores" tile:
This takes me to the "Store Sales Overview" page in the report.
As you can see I have 104 total stores, 10 of them new.
I have two chains, Fashions Direct and Lindseys.
Fashions Direct stores are larger on average.
2.In the pie chart, I’ll select Fashions Direct.
Notice the result in the bubble chart:
Fashions Direct -01 district has the highest Average Sales per Square Foot.
Fashions Direct -02 has the lowest Variance in Sales compared to last year.
Fashions Direct-03 and Fashions Direct -04 are the worst performers overall.
3. I’ll select individual bubbles or other charts to see cross highlighting, revealing the impact of my selections.
4. I’ll select Power BI in the top navigation bar to return to the dashboard.
5. On the dashboard, I’ll select the tile that has "This Year’s Sales."
This is equivalent to typing "This year sales" in the question box.
Now I’ll review a tile created with Power BI Q&A
Let me get more specific.
1.I’ll add “this year sales by district” onto the question.
Observing the result: I see it automatically put the answer in a bar chart and suggests other phrases:
2.Now I’ll change the question to “this year sales by zip and chain”.
Notice how it answers the question as I type with the appropriate charts.
3. Playing around by asking more questions I would see what kind of results I’ll get but for now I’ll move forward.
4. When I’m ready, to return to the dashboard I select Power BI in the upper-left corner.
Now let's explore in a more detailed way, looking at the districts' performances.
1.On the dashboard, I’ll select the tile comparing this year's sales to last year’s.
Notice the large variability on Variance percentage to last year, with January,
April, and July being particularly bad months.
Let’s see if I can narrow down where the issues might be.
2.I’ll select the bubble chart, and choose 020-Mens.
Observe the men's category wasn't as severely affected in April as the business overall, but January and July were still problem months.
3.Now, I’ll select the 010-Womens’ bubble. Notice the women's category performed much
worse than business overall, cross all months, and much worse in almost every month compared to the previous year.
4.I’ll select the bubble again to clear the filter. Next, I’ll try out the Slicer Let’s look at how specific districts are doing.
1.I’ll select Allan Guinot in the slicer on the top left.
Note that Allan’s district outperformed Last Year in March and June.
2.Now, while Allan is still selected, I’ll select the Women’s bubble.
Note that for the Women’s category, his district never met last year’s volume.
3. If I explore the other district managers and categories – I’ll gain other insights but I move on.
4. I’ll return to the dashboard.
I’ll ask the question ‘what is my data telling me about sales growth this year?
The last area I want to explore is the growth for new stores opened this year.
1.I’ll select the 'Stores Opened This Year’ tile.
As evident from the tile – more Fashions Direct stores than Lindseys stores opened this year.
2.I can see the Sales Per Sq Ft by Name chart: There is quite a bit of difference in Average Sales per square foot across the new stores.
3.I click on the Fashions Direct legend item in the top right chart.
Notice, even for the same chain, the best store (Winchester Fashions
Direct) significantly outperforms the worst store (Cincinnati 2 Fashions Direct) $21.22 vs $12.86 respectively.
4.I’ll click Winchester Fashions Direct in the slicer and observe the line chart.
The first sales numbers were reported in February and is a leading store in terms of volume for almost every month.
5. I’ll click on Cincinnati 2 Fashions Direct in the slicer and I see in the line chart
that the store was opened in June and it seems to be the worst performing store.
6. As before, I can explore by clicking on other bars, lines and bubbles throughout the charts and
see what other insights I can discover but I’ll leave you to discover this for yourselves.
Thank you for viewing this video, hopefully the presentation intrigued you enough to want to read Michele Hart, article in full.
This video presentation can only at the very best give you an overview so why not explore the data for yourself.
Have a fabulous day.