How To Analyse Retail Sales Data

The Retail Analysis sample content pack contains a dashboard, report, and dataset that analyzes retail sales data of items sold across multiple stores and districts. The metrics compare this year's performance to last year's for sales, units, gross margin, and variance, as well as new-store analysis.

How to analyse retail sales data. Set up a sales analysis report template that you can use to track sales data. The frequency for reporting and the level of detail in your data are two of the most important components to consider when developing a sales analysis, says Mark Gandy, small business financial consultant and founder of Free Agent CFO™ and G3CFO. This paves way for decision-makers to employ predictive analytics to derive the best value of all the data gathered and ensure better sales outcomes in the near future. Predictive analytics is a proactive approach, whereby retailers can use data from the past to predict expected sales growth, due to change in consumer behaviours and/or market. Sales analytics is the practice of generating insights from sales data, trends, and metrics to set targets and forecast future sales performance. The best practice for sales analytics is to closely tie all activities to determine revenue outcomes and set objectives for your sales team. Sales and marketing analytics are essential to unlocking commercially relevant insights, increasing revenue and profitability, and improving brand perception. With the help of the right analytics.

To perform sales trend analysis, you need a place to input and analyze your sales data. You could use Microsoft Excel or a software platform that is specifically designed for data insights. Many managers use Microsoft Excel for sales trend analysis to unlock insight and set up alerts. Another way to analyze sales data is to review your sales by each sales representative you have. You must do more than just rank them by gross sales, however. Find out which reps have the highest product return rates, sell the most high-margin products, generate the highest gross profits, have the largest number of new customers each month, and. POS Data Analytic is a Free and Easy way to improve your Retail business. This guide helps you define the important POS Data and How to analyze it to make your Business better day-by-day. Create a report in excel for sales data analysis using Advanced Pivot Table technique: The pivot table can be used to perform several other tasks as well. Some of these include: Categorize daily data on a monthly or yearly basis You can group data from the daily dataset based on a month or a year using a pivot table. Moreover, you can also.

Data analysts, data-quality managers, and business-solution architects can help identify the data needed for business-specific outcomes and make sure the data are clean, accurate, and standardized. The team should also include finance and sales staff, who will collaborate to vet the data every month. Let’s take a closer look at the advantages that retail data analysis can provide for SMB retailers. 1. Actually Get to Know Your Customers. Dish the Fish is a fish stall in Singapore that uses Vend’s cloud-based POS and retail management platform to track sales and inventory.. Prior to using the platform, Jeffrey Tan, the stall’s owner, used to order a lot of ikan kuning (a type of fish. 5 Ways to Analyze Retail Point of Sale / Scanned Sales Data Published on November 10, 2016 November 10, 2016 • 31 Likes • 1 Comments data.world. Feedback

Featured Resource. Vend’s Excel inventory and sales template helps you stay on top of your inventory and sales by putting vital retail data at your fingertips.. We compiled some of the most important metrics that you should track in your retail business, and put them into easy-to-use spreadsheets that automatically calculate metrics such as GMROI, conversion rate, stock turn, margins, and more. Why sales teams should measure this: It lets you approach product sales data from various angles like the demographics, product popularity, and the like. Multi-product firms can use the results from this analysis to take constructive actions, like discontinuing unprofitable products. Retail analytics focuses on providing insights related to sales, inventory, customers, and other important aspects crucial for merchants’ decision-making process. The discipline encompasses several granular fields to create a broad picture of a retail business’ health, and sales alongside overall areas for improvement and reinforcement. 1. Daily Sales Reports Top 11 Daily Sales Report Templates And Examples. A daily sales report is a management tool used by businesses, sales reps, and managers in order to extract the most relevant daily sales data such as the number of closed deals, client conversations, opportunities created, and many other sales-related KPIs.

What are the key data sets that BI tools should be used to analyze and report on in the retail industry? There are several common data sets critical to the retail industry that BI tools should be used to report on and analyze. These include: Sales data. Point of sale data; Gross margins and revenue; Turns; Gross margin return on inventory. Most companies have massive databases of historical sales data, but few firms invest the money and staff time to mine the intelligence hidden in those databases. It seems that everyone has sales data, but almost no one does a good job of analyzing that data. The purpose of this article is to present some basic ideas on sales analysis that might serve as a starting point for any novice who. Sample Sales Data, Order Info, Sales, Customer, Shipping, etc., Used for Segmentation, Customer Analytics, Clustering and More. Inspired for retail analytics. This was originally used for Pentaho DI Kettle, But I found the set could be useful for Sales Simulation training. 6. Examine Same-Store Sales Data Closely . This is the most important metric in retail sales analysis. Same-store sales data reveal how a store, or several stores, fare on a period-to-period basis.

According to retail software buyer data from Software Advice, 56 percent of single-store retailers don’t have a POS system in place capable of harnessing customer data. That means that over half of retailers aren’t equipped to make data-based decisions on customer experience and store strategies, a capability likely to boost sales.