Writing texts for posts, optimizing them, creating illustrations and covers is a labor-intensive process consisting of several stages. All materials must correspond not only to the promotion strategy, but also to current trends, requests and interests of the audience. Until recently, a lot of time, effort and money were spent on preparing posts and videos, but today, thanks to the use of neural networks, the process of creating content for social networks has been significantly accelerated and simplified.
Step 1 – preparing a content plan and texts via a neural network
Everything starts with a thorough analysis of the audience and its preferences, wishes. It is necessary to find out what interests it, what format of posts it prefers. At this stage, it is necessary to determine their focus – they can be selling, engaging, reputational, entertaining. In a word, this is a large and voluminous work, and it is this, as practice has shown, that can and should be entrusted to artificial intelligence. For example, the capabilities of the Chat GPT neural network allow you to make publication plans for pages in social networks for any period, even a year in advance. All that is required is to correctly formulate the task and set it before the digital assistant.
Chat GPT generates text for publications quite stably, but does it many times faster than a person. Thus, the neural network independently analyzes and studies:
- Audience behavior and reaction.
- Main trends.
- Key queries and hashtags.
How does this work?
Let’s say you need to create a content plan to promote a service – packaging of goods for a marketplace. Requests for Chat GPT are formulated and set sequentially:
- Step 2 — “Create a list of content ideas about product packaging for marketplaces. Include formats: text posts, stories, videos, checklists, and review posts”
- Step 3 — “Create a monthly content plan to promote the service of packaging goods for marketplaces, taking into account the stages of the sales funnel: attracting attention — generating interest in purchasing the service, creating emotional involvement”
The result is a ready and detailed content plan, which may need to be finalized. However, the basis will already be there in any case.
As for the texts for publications themselves, their preparation can also be safely entrusted to the neural network, as well as their optimization. Selection of LSI and keywords, collection of the semantic core, creation of texts from scratch, already adapted for SEO, analysis of competitors’ content – the same Chat GPT with the +WEB function copes with these tasks at a good level and quite quickly.
Step 2 – generating visual content via a neural network
Illustrations and animated images are used as a tool to capture attention. They provide an emotional response, engage the user, and encourage them to make decisions. The more diverse the visual content, the better. Previously, designers and even artists, creators, and editors worked on it. Now, literally everything related to the visual component of the content can be entrusted to the Midjourney neural network. All you need is to write prompts and commands correctly. In order to get the desired result, the commands are simply added to the already used prompts. They can be used to manage the size of images, correct their artistic style, and generally achieve the most accurate result.
Parameters when sending tasks to Midjourney must be placed at the end of the message. If you specify them in the middle or at the beginning, the original Midjourney will return an error. The exception is working with MJ via @yes_ai_bot in the Telegram messenger, where incorrect parameter setting is automatically corrected.
There are many parameters, all of which perform specific functions and tasks. For example, the –AR command determines the aspect ratio of the image. For example, if you need to prepare a horizontal rectangle image for social media content, the request specifies –ar 3:2, and if you need a cover for Stories, –ar 16:9 will do.
Example of YouTube cover
Another assistant is the neural network Flux.1
It generates professional content for social networks in literally 10-20 seconds, and the process itself is surprisingly simple. Flux’s special feature is the unrivaled quality of the text it can write on an image.
Flux.1 can be used to solve many problems. For example, the neural network will create not only a spectacular cover for a post on a social network, but also an interesting, eye-catching and memorable preview for YouTube videos. The algorithm for working with Flux looks like this:
- Come up with a plot for a scene – the already mentioned Chat GPT can help with this. Just ask it, for example, to write a plot for a video on the topic “How I rode a bike 200 kilometers”
- Clarify details – describe in detail the characters in the illustration and their actions
And if you combine Photoshop skills and neural network functions, you can create very attractive content, here is an example
You can go beyond static illustrations and diversify your content with animated images. They can be created using the Kling Ai neural network. It can animate any images based on a text description or frame (start and end). Kling almost always correctly understands the meaning of prompts, making fewer mistakes as a result. You can also create a video using just a prompt. There is a special instruction for this.