As the sales industry is increasingly moving into the virtual world of the web, with the number of e-commerce stores increasing by the day and online shopping becoming the norm, entrepreneurs are discovering the importance of analytics to optimize the proposed service, customer support, and also to capitalize on market trends to increase profits.
But what do we mean by retail data analytics? Is this something that owners of small shops can also exploit? And how? In this article, Cerdá offers you the support you need to understand everything you need on sales data analysis.
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What is sales data analysis?
The goal of the analysis of sales data is to improve strategies regarding prices, the production and supply chain, customer support, and many other aspects. After all, it is only with the data in hand that we can understand how to improve a certain aspect and find out if our attempts at improvement have achieved the desired effect.
In order to support you in achieving these objectives, however, retail data analytics is based on a large amount of data; it is for this reason that experts refer to this database with the term "big data".
Analyzing sales data means first of all collecting it. Once we have our “big data” at our disposal we can process them to support us in the goals we mentioned above.
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1. Data collection
When setting up your data collection you must not only focus on how you will collect your data, but also on what data you will collect.
The most effective data collections are those that make use of specific software: the best management software, today, also has functions that allow you to create reports on sales. You can make a difference, though, by knowing what to look for.
To collect data effectively, the best strategy is to identify performance indicators: particular categories of data that are indicators of the store's performance. Instead of just counting how many units you have sold, ask the software about the relationship between store turnout and units sold, between store turnout and actual purchases, how turnout has increased in relation to a particular promotion, and so on…
Data analytics software
As we've mentioned, using a data analytics software tool is the best way of collecting your data and creating automated reports. Managing huge amounts of data without a software is difficult, but creating reports and elaborating that data without data analytics software is impossibile!
In this section, we are going to explore some of the best data analytics software you can start using today.
Manta is a software tool that uses different algorithms to elaborate your data according to your queries. With this tool, you can rely on the software’s outcome, but you can also go deeper and see the actual data and find out how that outcome was provided and why.
Mantra works well both when you need a quick and overall overview over the data and when you need to dig deep and find specific statistics or parameters.
2. TNG Data
TNG Data is a data analytics software tool primarily focused on price monitoring. WIth this tool you can set up your prices based on the tendencies, availability, and popularity of the items. You can also upload your price according to the seasons or the change in the tendencies as the program provides real-time price data.
Cluvio is a powerful data analytics software that is also user-friendly. It also creates beautiful and interactive dashboard reports so that you can easily and efficiently share your reports with your collaborators, employers, or employees.
If you work in a team, this is probably the best option because this software is born with the aim of not only providing data and data reports, but also to help the members of a team sharing those data and reports.
2. Use the Data
Once you have your "big data" base available, it's time to use them to improve the performance of your store. How can you use sales data analysis?
When setting prices for your products, you make an important decision for your business. It is a decision that always depends on the relationship between the demand and availability of a product, but which also takes into account trends, seasons and other factors.
Data analysis provides you with this type of information so that you can calculate and optimize the price of your products accordingly.
The analysis of sales data is also important to develop your marketing strategies and also the entire management of your store. The analysis tools provide you with quantifiable data about market trends and other complementary information. Knowing that Minnie and Mickey Mouse products are one thing, having sales data in hand that shows that the sales of these characters' products are always 20% higher than those of any other brand is the data that makes you aim. on Minnie and Mickey Mouse products with absolute confidence.
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Data analysis can also be used to improve the customer's shopping experience. Some performance indicators, for example, are indices of customer trends, needs, needs or problems. By analyzing the data you can then highlight the gaps in the current market by filling them.
The cross-selling strategy consists in suggesting to the customer a product based on those he has already purchased. It is a strategy that is used in physical stores, but which becomes even more important in e-commerce. Whenever a user views a product or places it in their shopping cart, your e-commerce site can - and should - display at least three complementary products to what the customer is buying. This same strategy can also be used to suggest a product similar to the one the user is looking at, but which costs more.
To implement effective cross-selling, your algorithms - if we are talking about e-commerce - must be able to count on a large availability of data.
Cross-selling is one of the most important uses that can be made of data analytics.
Manage the supply
Last but not least, data analysis is also needed to optimize the management of your supply. An in-depth analysis of sales data, for example, also allows you to make accurate forecasts and, based on these forecasts, place orders for goods well in advance and when prices are lowest. It is with strategies like these that you can significantly increase your profits and they are all based on the analysis of sales data.
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When you run a selling business, you need to be able to foresee the future sometimes. Cerdá, for example, often foresees future tendencies for you.
Such predictions, however, aren’t due to a supernatural power. They are the result of a deep analysis of the market and, therefore, data. While you can always count on Cerdá, you also want to customize those predictions for your own sector, area, and competitors. Data analytics are the base for your predictions: you can draw your own conclusions, or you can thrust your software tools to do so.
Predictions can help you understand what item you should buy for the next season, what kind of changes you should make in your customer support or store management, and so on…
Cerdá supports you with your retail data analysis
Nowadays, opening your own online store or physical store has become increasingly easier. On the other hand, this also means that competition is increasingly fierce. To make sure you stand out from the crowd, you need to hone your strategies. Cerdá knows how to provide you with a professional look at the business world and provide you with the tools to implement increasingly effective strategies to increase the sales of your store. Find out what else Cerdá can do for you and the services it offers you!