How Data Visualization is Transforming the Retail Sector
The world retail has been changing very rapidly with online shopping being the biggest catalyst across the globe, third word countries being its latest point of focus. In both online and offline modes, retailers which are embracing a data-first strategy towards understanding their customers, matching them to products and parting them from their cash are reaping dividends.
Data visualization and analytics is now being applied at every stage of the retail process, right from working out what the popular products will be by predicting trends, forecasting where the demand will be for those products, optimizing pricing for a competitive edge, identifying the customers likely to be interested in them and working out the best way to approach them, taking their money and finally working out what to sell them next. Let’s have a look how data visualization and analytics are going to virtually transform this cash-heavy world of retail very soon.
Assistance in Observing New Trends
Nowadays, retailers have a wide range of tools available to them in order to work out what will be this season’s ‘must have’ items, whether that be children’s toys or designer dresses. Trend forecasting algorithms comb social media posts and web browsing habits to work out what’s causing a buzz, and ad-buying data is analyzed to see what marketing departments will be pushing. Brands and marketers engage in ‘sentiment analysis’, using sophisticated machine learning-based algorithms to determine the context when a product is discussed, and this data can be used to accurately predict what the top selling products in a category are likely to be.
Foreseeing Shifts in Demand Patterns
After gaining useful insights about what products people will be buying with the help of data visualization and analytics tools, the retailers will work on understanding where the demand will be. This involves gathering demographic data and economic indicators to build a picture of spending habits across the targeted market. For example, in Indian retail markets, the demand for precious ornaments and ethnic apparels increases exponentially as the festive season arrives. So retailers increase the amount of jewellery and apparel recommendations which appear in their customers’ feeds as the festive season arrives during the late autumns every year.
Smart Price Determination
Well known retailers across the globe spend millions on enhancing their real time merchandising systems that track a huge number of transactions every day. With the help of advanced algorithms, demand, inventory levels and competitor activities are tracked so that appropriate action might be taken based on insights in a matter of minutes. Data visualization and analytics also plays a part in helping to determine when prices should be dropped, which is known as ‘mark down optimization’. Prior to the age of analytics most retailers would just reduce prices at the end of a buying season for a particular product line, when demand has almost gone. However analytics has shown that a more gradual reduction in price, from the moment demand starts to sag, generally leads to increased revenues.
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