Retail Sales Data Analysis

A quick analysis of retail sales data consists of comparing the released data to the consensus, then to the high/low range to see how far from consensus the data is. At the same time, you will be looking at the revised number for the prior month to see if has been revised in the same direction as the current month’s data.

Retail sales data analysis. Retail Sales YoY in South Africa averaged 3.83 percent from 2003 until 2020, reaching an all time high of 15.50 percent in September of 2006 and a record low of -49.90 percent in April of 2020. This page provides - South Africa Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news. Excluding automobiles, gasoline, building materials and food services, retail sales increased 0.3% last month. Data for September was revised lower to show the so-called core retail sales slipping. 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. Why sales teams should measure this: Sales data analysis and interpretation are based on your past sales data, but market research can fill in the gaps of such analyses. For sales directors, it serves as a gateway into the future. How to perform sales analysis: a 3-step process.

The growth of the retail industry and customer demand has increased the cost, time, and effort needed to handle multiple business processes in the industry. Learn how OpsDog’s workflow, or flow chart, templates can keep retail sales organizations efficient and able to handle processes such as inventory replenishment, purchasing, advertising creation, etc. 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. We used predictive data mining techniques to identify profit generating activity from a 14 system source data set. It covered 5 years, intraday data and 150 attributes. Our analysis identified the store attributes that actually drive performance, whether performance is defined as sales, profit or any other metric. For big retail players all over the world, data analytics is applied more these days at all stages of the retail process – taking track of popular products that are emerging, doing forecasts of sales and future demand via predictive simulation, optimizing placements of products and offers through heat-mapping of customers and many others.

The field of retail analysis goes beyond superficial data analysis, using techniques like data mining and data discovery to sanitize datasets to produce actionable BI insights that can be applied in the short-term. Moreover, companies use these analytics to create better snapshots of their target demographics. Total global retail sales is projected to reach $26.29 trillion in 2019 and $27.73 trillion by 2020. 4% – The CAGR of global retail sales from 2013-2018 ; The total value of ecommerce sales is projected to reach $3.45 trillion in 2019. 15.5% – The CAGR of ecommerce from 2013-2018. China is the largest ecommerce market in the world. They rely on gut feel or on high-level analysis of aggregated sales data to gauge how their offline and online channels interact with each other, and they assume that cross-channel dynamics are the same in every market—when, in fact, every single customer touchpoint affects the rest of the retail network in its own unique way, depending on a. Need for Retail Big Data Analytics. The supermarket chain TESCO has 600 million records of retail data growing at rapid pace of million records every week with 5 years of sales history and 350 stores. It would be practically impossible to analyze this amount of data at once, with the help of legacy systems.

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. Context. The Challenge - One challenge of modeling retail data is the need to make decisions based on limited history. Holidays and select major events come once a year, and so does the chance to see how strategic decisions impacted the bottom line. 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. The Retail Sales Index (RSI) measures the value and volume of retail sales in Great Britain on a monthly basis. Data are collected from 5,000 businesses in the retail industry, with all businesses employing over 100 people or with an annual turnover of more than £60 million receiving an online questionnaire every month.

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. Understanding how retail and ecommerce sales channels impact each other is critical for remaining competitive in today’s market. Hear how YETI Coolers used the visual analytics power of Tableau’s geo mapping to do cross channel sales analysis of their product line to drive business value. 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. 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.

Monthly Retail Trade Report. Statement Regarding COVID-19 Impact: The Census Bureau continues to monitor response and data quality and has determined that estimates in this release meet publication standards. For more information, see COVID-19 FAQs.. The July 2020 Monthly Retail Trade and Food Services report was released on September 16, 2020 at 8:30 a.m. for sales and 10:00 a.m. for.