The expert called the main mistake of brands in social networks

Brands are increasingly creating content for the sake of speed and reach, rather than for the sake of meaning, which is why the Internet is filled with "digital noise." Pavel Galin, a media entrepreneur, co-founder of Spot Film and Big Black Studio, told Izvestia on May 20.

According to him, the modern market has found itself in a situation where companies are forced to constantly publish new materials in order not to fall out of the information agenda. As a result, the content ceased to be an event and turned into an endless stream of similar publications.

"There is so much content that it has ceased to be an event. It has turned into digital dust," the expert noted.

Galin believes that brands are increasingly using so—called parasitic content - publications that are based on other people's trends, emotions and viral formats, but do not create their own ideas. According to him, the industry has begun to put the regularity of publications above quality and meaning.

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The expert paid special attention to the use of neural networks in marketing. In his opinion, artificial intelligence really helps to produce content quickly, but it is not able to automatically build an emotional connection with the audience.

"Neural networks are a separate story. The market met the ideal employee: fast, cheap, infinitely productive. But productivity and trust are not the same thing," Galin emphasized.

He added that the audience recognizes insincerity and gets tired of algorithmic content. In addition, according to Galina, brands are losing trust not because of the lack of memes, but because of the lack of a clear idea and their own voice. He stressed that it is important for companies to research the audience, work with positioning and use trends only as a tool, and not as the basis of all communication.

On the same day, Inna Filippova, Chief Operating Officer of the SOK smart office network, said that AI is increasingly being introduced into office work, from document processing to data analysis. However, even the most advanced algorithms are not able to completely replace employees. At the same time, it is able to automate a significant part of routine processes — data processing and structuring, preparation of standard documents, information retrieval, primary analysis of reports and large amounts of data.