Brand & Margin Analysis

It is important to note that the data considered begins with the date on the heading panel of the dashboard, under Earliest Transaction Date.  This means that your trends and filtered data will start with the transactions on this date.

You will see a link to this document in the top of the dashboard, under the heading Dashboard Help. 

KPIs

At the top of the dashboard, a selection of KPIs appear in two rows. The top row represents the "Review Date" metrics, and the bottom row represents the "Comp Date" metrics; these date periods are controlled with the filters to the right of the dashboard. Here you can compare the KPIs for two time periods to gauge performance, as well as to measure initiatives you may be testing. You can watch the metrics to be sure your expected performance is on track for the period, and make adjustments as needed.  As you initiate operational changes and set goals to measure success, you can use this section of the dashboard to know how the results compare with your goals and with previous results.  You are able to filter the KPIs to activity related to a variety of characteristics, including to specific channels to further narrow the focus.

Your margins on this dashboard are based on product sales and cost; they do not contemplate labor and other factors that might be included on a financial margin report. You will want to look at volumes of transactions and customers when analyzing margins - consider that a margin might be exceptional, yet the volume of activity (or customers) is light, this might spur an effort to promote the product and then monitor the success. You also might see a margin that seems on the light side, yet the volume of transactions is high - this might spur some price elasticity testing, perhaps a slight increase that might gain a small percentage yet large dollars.

Graphic Displays

The next graphics illustrate the top 15 manufacturers, based on sales dollars (as of the Review Date filter). You will see both the margin dollars and percentages for the top 15. Here you can focus your analysis on a specific product group, for example, or maybe a specific sales channel. You will be able to see where the outliers perform, and understand where products are similar in profitability. Once you filter to the desired characteristics, you can further focus on these graphics by toggling (left-click) the specific names in the legend to turn them on & off - turning specific names off will bring the others into sharper focus.

Use this section of the dashboard to find the manufacturers that warrant further scrutiny. Maybe you are considering whether to purchase from a new manufacturer, or remove an underperforming one. Maybe you have multiple manufacturers for a specific product type or types. Maybe you want to see how certain products perform before or after promotions. You can use the filters on the right side of the dashboard to narrow the focus to those products and quickly see how your margins compare. Use that information to determine the appropriate course of action. You could find that your customers appreciate multiple different manufacturers for specific product types, yet some of those are markedly better performing than others - this can inform your buying team in their efforts to choose which to purchase at higher levels. 

Two more graphics follow, illustrating sales, cost, and margin information in dollars to compare the dates you selected  in the filters. The second graphic illustrates margins as well as growth for sales, transactions and customers (growth from the Comp Date to the Review Date in your filters). Again, this represents the top 15 manufacturers based on the set of filters you choose. As with the above graphics, you are able to toggle the names in the legend to turn specific metrics on & off and look at very focused information. Maybe you want to see how sales performed for in-store sales, comparing last month to the same month in the previous year, then look at how those sales translated to your margins - are there areas where margins can be improved? where price elasticity can be tested? where buying power can be more effective? Maybe you want to analyze a specifc product type across the various manufacturers and focus on only the most profitable ones - are there overlaps where you can trim your buying options and free some valuable shelf space for other products? opportunities to clear underperforming manufacturers within the product type? volumes that might dictate more (or less) marketing or merchandising?

The next set of graphics show your margins, both in percentages and dollars. Pay attention to both metrics, as the volume in each grouping is as important as the margin percentage. For example, you may see a 90% margin for a particular grouping and notice that the volume was a single item sold one time at a deep discount. In this section you are able to switch the dimension to look at grouping of various category levels, manufacturers and stores. You will see in the KPIs in this section a comparison of the overall margin as compared with the date range you select in Comp Date. Below the KPIs are graphics that show the groupings you select with a right click ==> Switch Dimensions to see your options.

You may want to look at specific manufacturers to analyze how they perform against each other. Perhaps your buying team is considering a change in volume for certain products from these manufacturers. Maybe your promotions boosted interest in certain manufacturers or products and you want to understand the impact of different promotions. You can quickly see both product types and manufacturer details in the next data table. You can right click on the row description to switch dimensions from a menu of options.

Here you will see margin data for comparison, as well as the growth for your sales, transactions and customers between the Review and Comp dates in your filters.

Any of the data tables can be exported to work with the data outside the dashboard. Do this by clicking on the 3 dots at the top right corner of the widget, choose Download and export an image or file.  The recommended file type for a spreadsheet is CSV.