Sales Analysis

Introduction

This application contains sales data for a mid-sized retail company, that can be optimized for sales managers and individual reps. It is based on the sales database, and includes a high-level dashboard, product, region, and customer focused analyses, and of course a full set of transaction level detail.

The sales organization needs more than data – they need real insight. The current application enables organizations to more effectively drive productivity, grow revenue, and reduce risk.

Use case

The Retail Store Performance dashboard ties corporate strategy to store level execution at all levels of the store operations hierarchy. Performance metrics as CY Gross Sales, Profit and Margin can be analyzed and put in the perspective against target or previous year results.

On the landing page it is important to recognize all high-level information that this report can offer. In the next pages the information will be displayed in a more detailed and drill down manner.

All strategic KPIs are listed at a glance – Top 10 of the best-selling categories, top categories by Margin and sales versus target comparison.

Analyzing the sales, we come to the most centric part of the insights and this is the customer data and behavior.

Analyzing the average sales amount per customer over time gives you a better idea of how well your sales strategies and marketing campaigns are performing. The Client Acquisition rate from the other side shows how tactic are connecting with consumers and the success rate of the sales team in converting leads into actual customers.

The bar chart shows the correlation between the number of customers and the amount spent- analyzing this data gives us the opportunity to spot outliers due to seasoning.

The perfect solution when you need to summarize and analyze large amount of data is the pivot chart. To obtain the desired report we aggregate the information as per business requirements.

All these important KPIs- Sales in Volume and Value, Profit. Margin, Customer Ratio, Visitors. Discount and average daily sales can be aggregated at the year, location and month level. We can drill- down the same information also to the customer level and by this we perform a very detailed customer analysis.

Using the combo chart properties, we can visualize metric, using different scale- numbers and percentage. We can analyze how our sales figures are evolving over time against the target. By doing this we can improve our target setting for the future periods and simultaneously compare the sales progression.

On the graph we see the margin in %, which gives us a clear picture of what is left after all expenses are paid. This KPI is used to show the effectiveness of converting the sales into income. We can have this visualization on the year level and then by clicking the drill down dimension, to go on the month level.

And last but not least we can put an extended object on the sheet- again a pivot table, showing the most important financial KPIs but at a very detailed level- document, item, code, category, customer, etc. The order and the hierarchy can be customized according to the specific needs.

Results

With QlikView, sales managers and reps can take full advantage of their data to better understand sales performance and pinpoint opportunities to improve revenue and profitability. Qlik Sense, and Associative Analysis enables the analysis of consumer behavior and provides understanding of how profit and margin analysis evolve through the time. In addition, we tailor the analysis with the additional information upon business needs and requirments.