Technology as a competitive advantage
In an ultra-competitive sector like retail, millions of variables influence the evolution of your business on a daily basis. Your competitor’s promotions and the climate are just some of the factors that can alter the behaviour of your sales. It’s impossible for a human team to measure and evaluate such a large number of factors without the help of advanced technological tools. Reactev was built using an AI engine based on cutting-edge technologies like machine learning and deep learning. Thanks to this technology, this tool is able to process millions of past and present events of different types, detecting correlations and patterns, and, therefore, predicting future situations with great precision. Every piece of data and every decision made serves as self-learning for our AI engine, making predictions more accurate and your decisions more successful every day.
The prices of the competition, priority data
Your sales forecasts, even when based on past behaviour, can be altered by competitive aggressiveness. Reactev, unlike other solutions, has a “market leader” approach, making the competition’s prices and availability very important data that will allow you to accurately determine your competitive positioning.
Seasonality and climate in your decision model
The analysis of millions of past situations can help us find correlations and patterns. For example, in DIY, there is a marked increase in sales of paint and enamel with the arrival of spring. Likewise, weather conditions have a strong impact on your business. For example, if a storm is expected in the near future, it might not be a good idea to launch a promotion in the physical stores that will be affected. Reactev is capable of processing past events to detect seasonality as well as climatological data with which it can predict future sales behaviour.
Your sales history, the target to beat
Each of the sales made in your stores is processed, normalised, and analysed to build a model for estimating the demand with which to predict future behaviour. Understanding how our pricing strategies worked in the past and how they translated into results will help us to define and achieve increasingly ambitious goals.