Deep learning makes advertising activities up to 50% more efficient
Technology assists companies in data analysis and decision making; having a clear business strategy is essential to adopt it
Learn and act as human beings without the need for specific instructions or rules: this is the essence of deep learning.
The technology, which is part of machine learning, in which computers and devices perform their functions without seeming programmed, is able to analyze deeply, through neural networks, a large volume of data, identifying patterns of consumption.
According to a study by RTB House, a consultancy specializing in personalized retargeting, the precision brought by technology can make advertising activities up to 50% more efficient than with the typical mechanical learning approach.
This is because, with deep data analysis, companies can identify the consumer profile – where they live, when and why they buy, what they are looking for – and create more accurate and customized advertising campaigns. “Much more demanding, the consumer wants to receive personalized and targeted offers.
So the use of deep learning can be crucial to maintain competitiveness, “says consultant Cezar Taurion, partner and head of digital transformation at Kick Ventures.
In practice, the tool trains a computational model to decipher a natural language. Powered by data, this model is able to relate terms and words and thus infer meaning.
In this way, it assists in making decisions and analyzes information intelligently. Deep learning software also groups data and applies more complex calculations. “These algorithms not only absorb the information but refine everything they have learned from it,” explains consultant Taurion.
But it is not just the retailer that has benefited. Companies in other industries – such as entertainment, services and transportation – can also take advantage. “We live in the data age and organizations that can use them efficiently will stand out competitively,” explains Reinaldo Roveri, market intelligence and business strategy consultant.
In the financial sector, technology can be used to better understand the profile of customers, improving service features and increasing offers. “A bank, for example, can use it to give personalized customer investment tips,” explains Taurion.
In addition, you can use it to detect alert points as they occur, which will help detect fraud as well as prevent theft of funds and personal information.
But to embrace it and enjoy its benefits, according to Roveri, it is important to have a clear business strategy. “Some companies are conducting prototypes in many areas, but many of them do not even have a strategy or are just following a market trend,” he points out.