We know, the quantity of what you sell varies depending on price, demand, competition, consumer behaviour, accumulation and assortment: but how do you identify the correct price to apply to a specific product at a specific time?

The answer is Artificial Intelligence: the implementation of vertical models, based on Machine Learning algorithms, enables the retail sector to adjust prices in real time. With proper Dynamic Pricing retailers can make more informed decisions, maximise the profit margin and optimise market competitiveness.

Today, Marketing for Mass Retail and Retail must utilise new and more effective tools: promotional campaigns must be calibrated down to the last detail (product, price, content, timings and specific target groups). Through the use of customer data, Data Science enables sectors such as  Food Retail to comprehensively personalise offers and promotions. Loyalty programmes based on predictive models improve the customer experience, increasing brand loyalty and sales. All of this is done, with full controller by the retailer, by combining human cognition of personnel involved in Marketing and Sales processes with the leading technologies.

In the Retail sector, Data Science analyses data on user behaviour to optimise physical and virtual sales layouts. A predictive approach enables the synthesis of multiple variables at the individual level into a single indicator of propensity to buy, making it possible to offer the most on-target product for the user’s tastes at the most opportune moment. The advantage? Refinement of the purchasing experience and customer journey. 

Demand Planning is an activity that cannot be based solely on the experience of the person managing the process, their intuition and sales forecasts. Today, in Retail it is essential to transition to smart demand forecasting, for planning that eliminates wastage and optimises production and profits. Here too, Artificial Intelligence supports companies with an application to predict demand and anticipate issues in a constantly changing world. A true virtual assistant to facilitate the daily work of Demand Planners.

How can we prevent customers from stopping purchasing products or services? Artificial Intelligence makes it possible to identify users with churn risk, those that may stop purchasing a product or using a service, subscription or utility. All of this is done by leveraging customer details, customer-satisfaction data and information on interactions. The picture is completed with tools to optimise contact, which enable calibration of effort/commercial tools, calculation of churn risk and value of customers that can be saved, adopting an uplift-modelling logic.