SAS identifies four major trends in a world increasingly competitive and marked by the omnicanalidad.

Companies of all sectors are facing technological challenges in an increasingly competitive world. Among them, the companies retail, which must adapt to a scenario that is characterized by the omnicanalidad.

To analyze how you can respond to the preferences of consumers and improve the shopping experience, SAS identifies four popular trends that have to do with analytics.

“The volume and the cluster of climate are the #oldschool”, begins SAS, especially in a time marked by the rise of eCommerce. “in order To understand the preferences of the customers, it is critical that companies know what products people buy in each channel (online and store), and which of them have a chance at a local market”, says this company, you are encouraged to use grouping techniques.

While, “the analysis of attributes of fashion”. That is, the analysis of colors, sizes and other characteristics that you describe how is the merchandise. Here “the correlation analysis can be used to understand what elements of the goods are correlated, which can help to reduce the number of features to a manageable size”, instead of working with all of them. Another application of the analytical have to do with the discovery statistical of the most important properties from the point of view of the customer. From there the decision making to order would be simplified.

third, “the statistical planning is a great ally”, according to SAS, since that “the use of a forecast statistical allows retails predict the future demand”. You could calculate the relevance of events and promotions and optimize inventory for greater profitability.

finally, SAS is speaking of stay “away from the failure” to match both with the assortment as the inventory. And it also points to the use of “imputation techniques, process of replacing missing data by values. In retail, this methodology substitutes for the lack of sales due to lack of inventory, so that every time a business sells creates what is known as a lack of stock”. And continues: “to enable the analytics to determine what is the demand true-to-size for a particular product to a location level, will ensure that the customer find the correct merchandise”. This would avoid the discounts.