Sales Channel Review

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 (similar to the Sales Metrics Review 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, importantly to specific channels to further narrow the focus.

When you need to analyze your activity based on how your customers are shopping, say In Store or Buy Online Pickup In Store (BOPIS), you are able to filter to that data. Use the filters to the right of the dashboard to narrow Store Name to the store(s) you want to see, plus your online "location" i.e. xyz.com. Then use the Fulfillment Store Id for Online Orders filter to select the location id of the store(s) you are analyzing. For example, if you want to analyze Store #1 ABC: on the Store Name filter choose ABC and xyz.com; on the Location Id for Online Orders choose 1. This will reflect the In-Store sales for that location plus the online orders that the store fulfilled.

The KPIs are relatively straightforward, and will respond to the Review Date and Comp Date filters, as well as any of the other more specific filters. This dashboard is largely focused on the channels your customers are using to shop. You may have initiated a BOPIS option or maybe a promotion to entice new customers, or perhaps a special offer for same day delivery - you want to be able to track their usage, as well as how they may be impacting other channels, like in-store shopping.  How much are in-store sales impacted when that same store starts, or increases its BOPIS sales? How is Same Day Delivery evolving as a service, and how is it impacting other channels? Start digging in to the data here.

Graphic Displays

Below the KPI panels, you will see a graphic of the major sales metrics - based on the filters you have applied to the dashboard you will see at a glance which of the metrics are driving your sales performance. Maybe you see a dramatic increase in BOPIS/Curbside sales - is that driven by a similar increase in transactions? customers? items? are these metrics in line with your normal overall performance? Next you might want to look at the in-store metrics to see how they were impacted. You will want to pay attention to trends for these metrics, and understand how to compensate where sales are negatively affected, and how to capitalize where sales are positively affected. Perhaps your locations are going gangbusters on Curbside pickup or a newly launched Same Day Delivery service - how is this impacting in-store sales when your customers no longer walk past the impulse items when they are inside the store? Is the average transaction value increasing as a result of a minimum purchase for same day delivery? Maybe you want to consider a minimum purchase for this service if you do not have one already. Be sure to look at each metric as part of a larger picture - no single one will tell the whole story.

Next you will see a high level comparison by sales channel - at a quick glance you can see if certain sales channels are materially different from your Comp period. Maybe you find that transaction volumes have fluctuated more than normal, what's behind that? Is the fluctuation specific to a single shopping channel, or do you see a trend where different shopping channels are shifting in opposite directions? Start digging into the data here.

Next to the graphic there is a table of metrics that correspond to the KPI panel - you will see it organized by shopping channel to understand which are improving and which might be deteriorating. Be sure to pay attention to the collection of metrics, a single indicator may not tell the whole story. If you hover to the right of the field names, you will see an arrow that allows an ascending/descending sort. You can export the data in these tables, to work with it outside of 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.

Next you will see a stacked column chart where you can see how overall sales compare from month to month, as well as the individual sales channels that make up each months performance. Maybe your overall sales are staying relatively stable, yet a certain sales channel seems to be increasing over a series of months. You will want to be sure that you allocated appropriate resources to compensate for the shift. To the right of this graphic you will see how the individual growth metrics impact each sales channel - this graphic will help guide an understanding of how the channels interact and impact each other. Remember of course that your lower volume sales channels could have percentage changes that are not a one-to-one  comparison with your higher volume sales channels.

The next graphics will show you the trend of average monthly purchases for customers (this will exclude your guest shoppers) by sales channel. These graphics represent the actual purchases made in each month, on average for each customer, You will want to understand any operational changes that might have affected the dips and spikes in each channel - if your same day delivery service shows an increase in monthly sales while at the same time your in-store sales dropped a bit, you will want to dig deeper into the reasons and respond with labor allocations and shopping enticements as needed.

You will see two different graphics representing the same data. Each will give you a different perspective of the trends, and may draw your attention to different opportunities.

The next two graphics provide analysis by shopping channel cohort. The cohorts are based on a 12 month lookback period where customers have shopped in certain numbers of channels. As customers shop in more channels, they move into the higher cohort for all 12 months of the analysis. For example, in the 12 month lookback period, a customer shopping In-Store and by Same Day Delivery will be in the "2" cohort. When that same customer adds BOPIS to their experience, they move into the "3" cohort for the entire 12 month analysis. The monthly average spend is calculated on the basis of all customers in the cohort, whether they shopped in the month or not.

This 12 month spending analysis will help you understand the value of your customers as they increase the ways they shop with you. Here you can understand average spending trends that are smoothed over a 12 month timeframe. Your customers might shop in some months, and skip other months. The prior graphics on this dashboard will reflect this ebbs & flows of the actual purchase activity. In these cohort graphics you'll see customer spending averaged over time, and grouped by cohort. Say there are 5 customers in the "2" cohort, not all of them will shop every month - the average spending each month is calculated by taking the total spending that month & dividing (in this example) by 5, thus smoothing the spending over time. Remember also, that the cohorts are based on customers who have shopped in the past 12 months.

It is reasonable to assume that customers shopping in more channels are likely to average higher spending levels - as with any assumption, you'll want to know if this is the case - and how a variety of filters will give you the information you need to make better decisions. Do your customers purchase certain product types in a variety of channels? You will want to know how the varrious cohort activity differs - is a 3 channel customer 2% higher in spending than a 2 channel customer, or maybe 5% higher? As your customers get hooked on the various channels you make available, they are often more likely to stay with you. How will you maintain your higher spending customers? How will you get other customers to add one more channel to their experiece and become even more valuable?

Exporting the Data Table

The data table at the bottom of the dashboard is a granular listing of what is represented in the dashboard.  You are able to right click on the product type name to drill into deeper detail of the data. This table will react to filters set as you are viewing the dashboard.  There may be times when you want to look at this data, filtered or not, in a spreadsheet or image.  This functionality allows you to shape and model your data for reporting, and importantly to inform your business decisions.

You are also able to interact with the table by removing the product type name to see only the sales channels, and then adding it back to the table. If you right click in the column header area you will bring up the menus to do this:

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.