The situation is more complicated with visuals. Since we work with brands, and they have their own strict design, we cannot deviate from it. It is not yet possible to teach the neural network to generate images in the client's style, but it helps a lot in projects where the client has run out of photo banks or did not have one initially. AI is able to create images that are more lively and emotional than pictures on a photo stock, and all we have to do is correctly fit the product into them.
Analytics
we constantly receive various types of research: by industry, by social networks, by consumer demand, etc. Most often, global research is very voluminous, and it takes a lot of time to delve into it. In addition, human abilities are not unlimited - it is physically impossible to remember the dynamics of all indicators in all studies. But remembering where morocco cell phone number list they are stored is another matter. Therefore, when we start developing a strategy, we openhttps://pdf.aiand its knowledge base on the computer. In a matter of seconds, the neural network makes a brief summary and is able to answer any question about the file. aianswers in English, so in each request you have to write "answer in Russian". But it seems easier than rereading a mountain of data yourself.
Study of target audience
There are many possible actions here, but in general, each of them significantly speeds up the work process. If the client or we have a clear understanding of the target audience segmentation and there is no need to reinvent the wheel, then we simply feed the data into the neural network, add knowledge about the product on top, and as a result, we can ask to describe at what stage of the sales funnel the target audience may be and what communication tasks the brand should solve. After that, we can generate a content plan directly in the table and break it down into categories.