Click on the thumbnail image to see a larger image and use the arrows at the bottom to scroll through samples of these reports.
Year-over-Year Sales and Margin Comparison – Graph
Easily understand the relationship between sales and gross margin, year-over-year changes, trends and anomalies. A single click will cycle through product or customer classes.
Basic Sales Growth Analysis
Easily identify unusually good or bad individual customer performance. Compares year to date over prior year to date, this month over same month last year and percent of total prior year. Filter view by salesperson, territory, customer class or any other dimension.
Product Sales Metrics
Highlight key sales operating metrics that provide insight into the drivers of sales and gross margin. From average document amount and average sales price, through on-time shipment percent and average days order to ship date provide operational insight. Easily explore atypical results by customer segment product segment or individual customer.
Customer Product Detail
Immediately highlight changes in growth rates by customer segment. One-click drill-down to actual customers, or filter by product class, territory, or location.
Daily Customer Activity
This view provides daily feedback, by day of week across many key customer key metrics and can be used as a control report to immediately identify issues before they become problems. From unusually high returns, to poor shipping performance to atypical discounting or product mix, this view provides detailed and a wide range of operating metrics on a daily
Customer Acquisition Analysis
This view identifies new customer acquisition, commonalities and related information. The view does a 12-month rollback, identities all new customers, the month they were acquired from the current date and their life-to-date sales. In the columns, we can identify types of products new customer are buying, their territory, or salesperson that is selling to them. Many other dimensions can be used to identify commonalities.
Salesperson Customer Acquisition Analysis
This view identifies performing and non performing salespeople based on new customer acquisition. Based on the last 12 months, sales people are listed in descending order by their contribution to new business. This example shows Rita Ruth as the star performer generating 10.1% of all new business. Our overall top salesperson, Nancy (see in-cell orange bar) is doing well as fifth best in acquiring new business. We can also see that several salespeople like Tricia are living off their legacy bases as their % of all customers is greater than their percent of sales from new customers. With 3 clicks you can change view to analyze gross margin instead of sales, rolling 3 months instead of 12 months, or any other filter.
Customer Retention Analysis
Do you know how much business comes from new customer acquisition or customers you acquired 5 or more years ago? This view provides insight into customer retention by year by acquisition. The example indicates that we are not doing as well acquiring Institutional clients (44% vs. 48% for Consumer and Restaurant). Clients acquired Year 2 and 3 (between 13 and 48 months ago) account for slightly more than half of all sales for the current year. We can also see year of acquisition has no impact on gross margin %. You can drill down to the customer in the rows.
Customer Rising Stars
This view goes beyond identifying your top customers and calls your attention to customers that have the fastest rate of growth as a function of total company sales. The view shows top 20 by sorted by growth rate. In this case we are comparing the most recent 3 months to the preceding 9 months. The in-cell bar chart identifies with largest percentage of total company sales. Filter by salesperson, item, class, or any other dimension. Change Market Segment from All to Consumer.
Customer Falling Stars
This view calls your attention to customers that have you may be losing. The view shows the bottom 20 companies that are decreasing their percent of your total business by comparing the most recent 3 months to the preceding 9 months. The in-cell bar chart identifies with largest percentage of total company sales. This example shows that Georges International Grocery has dropped from average monthly sales of $114,955 to $41,902 per month. They currently account for 1.2% of total sales which is a drop from 2.1% a .9% drop. Filter by salesperson, item, class, or any other dimension. Change Market Segment from All to Consumer.
Top 10 Customers
Beyond just showing top 10 customers, this view also indicated that the top 10 make up 29% of total business. This view compares the current top 10 to their prior year-to-date performance. Roger Supper store is up 154% of the prior year, University of Killington is down at 62% of the prior year.
Top 10 Inventory
Beyond just showing top 10 products, this view also indicated that the top 10 products make up 54.8% of total business. This view compares the current top 10 to their prior year to date performance. Mushroom and Garlic Sauce is essentially unchanged at 10.3% of total business, but the Marinara Sauce is down to 69% of prior % of total sales at 3.9%.
Customers at Risk of Loss
This view provides away to identify customers at risk based on lack of activity. This view shows the number of months (or weeks) since the last time a customer has been invoiced. Some companies can use this view to identify single sale customers (see month 3 – Chianti). Since their inception to date equals the month 3 amount, this was a first time customer. They made one purchase and we haven’t heard from them since. For more information hover over Chianti, and see if there are any products on open order, any open receivables, customer phone number, and salesperson.
Customer Life Cycle
How do customers behave after they first become customers? Do buying patterns change over time? Are there commonalities due to industry, salesperson, or territory? This view tracks customer lifecycle by tracking sales based on how many weeks out from the date of the customer acquisition, normalizing customers that were acquired 1 year ago or 5 years ago. This sample chart shows that the first month of customer life is followed by a major decrease in sales in the second month, taking two more months to regain the month-one run rate. This may indicate that we are overselling the initial stocking order. Drill down on legend to see detail by market. Swap Product Line and Market on the graph.
Customer 360 Details
Go to one screen and get a full view of your customer relationship. Over 90 metrics are available. Basic measures include sales, receivables, cash receipts, open sales orders, and shipping metrics such as average days order to ship and late shipping measures. With the in-grid calculator, add you own key performance indicators. Click once and add in related time periods such as prior YTD, current month, and more.
Customer AR Aging – Graph
The graphical aging profile is a speed-of-thought method to see aging anomalies. The profile should always be consistent, and usually looks like the graph below. This profile provides incentive to clean up and eliminate the long tail bump caused by unresolved receivables. Easily add salesperson to the graph, and click through the profiles by salesperson to identify atypical profiles at a more granular level.
Receivables at Risk
This view can increase the collection of invoices in dispute. Invoices that are paid on time, but partially paid are at risk as well as invoices that are overdue. This view identifies both partially paid invoices and invoices past due 90 days.
Sales Order Aging – Graph
This graph is a starting point to understanding sales order back log as well as orders scheduled to ship. This view is showing backorders by warehouse location. After drilling down you can view on a day-by-day basis and product detail scheduled to ship, or backordered. Then filter by location, manufacturer, customer, salesperson, or any other dimension.
Shipping Performance – Graph
Visibility into shipping performance trends is critical for customer satisfaction and retention. This graph vividly presents the on-time shipping percentage over time (the black line). To add context both number of documents and line items shipped are indicated by the bars. Filter view by warehouse site, product type, or other dimensions.