Data, data, data … if something is not lacking in the retail industry, it is data: each ticket issued contains important pieces of information that, analyzed, could become the basis for boosting sales: At what time are certain products sold the most? What items are usually bought together? What are the most successful offers at a certain branch? Where should products be placed so that they are more accessible?

More sales to the same customer

At the same time, big data is also the way for companies to achieve a deeper understanding of their customers: what they buy and when, how they pay, what they publish on their social networks that may be related to the brand, what mechanism of shipping they prefer.

Predictive analytics tools let us know when a customer’s next purchase will be and which items they will prefer. In this context, future operations with that consumer as well as cross selling strategies (sale of complementary products to those purchased) and up selling (an upgrade of the product that makes it more expensive) are facilitated.

And if you combine all of the above with, for example, the power of Intelligent Forecasting – the artificial intelligence solution that allows you to forecast business events – it is possible to generate demand projections, optimize inventories and ensure that the customer always gets the product they want.

Real time marketing

Predictive analytics applied to these huge volumes of data, on the other hand, makes it possible to set up which products to promote, the duration and frequency of the offers or the type of audience to reach with each specific message. Massive marketing campaigns or mass advertising are becoming part of the story: today each person can receive an attractive and relevant message from their company, since it is possible to identify in a customized way habits, history and lifestyle of each individual who enters the store or who browses in an e-commerce.

Segmentation becomes granular and can be done at multiple levels: by age groups, by geographical areas, by habits – for example, targeting customers who purchase only a certain brand of shoes with a special promotion – or by personal interests, to cite just a few references.

One channel, all channels

One of the great happenings left by the pandemic was the exponential growth in sales through e-commerce. This represented an additional challenge for traditional retailers in terms of attracting, retaining and generating a good experiencia in customers.

In the virtual field, the amount of data is so abundant – what customers observ on a website, how long did they stop at each product, what elements caught their attention, what products they kept in the cart, from which device did the queries and an etcetera impossible to enumerate. Big data is no longer an option, but a compass that indicates the next steps.

Towards total gratification

Loyalty programs are another great point of application of big data in retail, since by definition they provide feedback on themselves: they are a source of information to get to know the customer and also a way to reward their behaviors with personalized benefits.

And just as it is committed to satisfied customers, big data is the key to identifying those who are not: it is possible to analyze the reasons for abandoned carts and generate preventive or reactive actions to avoid casualties.

Data is already captured: in each ticket, in each claim, in each interaction with the service centers, in each browse through the company’s sites… The consumer leaves numerous traces. The difference will be between the companies that accumulate this data without rhyme or reason and those that manage to capture the value it contains to continuously improve the customer experience and, of course, the profitability of the business itself.