Expert How to analyze the target audience and competitors through neural networks: step-by-step instructions

Today, many entrepreneurs and experts analyze the target audience in the same way: open a neural network and write “Do an analysis of the CA for a niche...” The answer is a beautiful text that looks convincing but has little to do with real customers.

The problem is that the neural network does not know your audience. It is based on average knowledge gained during training.

In this article, I will show you how to use neural networks to analyze the real data of your customers and competitors, rather than generating plausible guesses.

What is target audience analysis and competitor analysis?

Target audience analysis (CA) It is a study of people who are the most likely consumers of our product.

The analysis of the target audience helps:

• contentBecause knowing the pains, fears and desires of the client allows you to make publications that solve audience problems.
• Choose effective platforms for promotionBecause analysis shows where your audience is and what channels are really working.
• build offTo understand the values of the audience and formulate a proposal that will differ from the competition.
• Increase conversion and salesSpeaking to a customer in their language significantly increases conversions at all stages of the sales funnel.

Analysis of competitors Research of companies that offer similar products or services.

Competitor analysis is needed to:

• Develop a unique trading offer (USP) Find out how your competitors’ products and services differ from yours.
• Identify gaps in service or rangewhich need to be filled.
• Determine which advertising channels Competitors use them and how they value their products.
• Understand what content It gets the most response and why.

How can neural networks help?

The main advantage of neural networks is to quickly analyze thousands of comments, search for recurring topics, combine similar thoughts and find patterns. That is why AI should be used not to generate analysis from scratch, but to process real data. This approach will be discussed further.

But from experience, I can say that the neural network can be wrong in two cases:

• When there is too little comment;
• Analyze several different segments of the audience.

Therefore, for analysis, select larger sites and aimed at a specific segment of your target audience.

How to analyze the target audience using neural networks

In order for a neural network to make qualitative analysis, it needs real audience data. These can be comments from your Telegram channel or from competitor channels where your target audience is communicating.

Instructions on how to upload comments from the Telegram channel

It only works on your computer and Windows operating system.

1. Go to the competitor’s Telegram channel.
2. Click the channel name and go to the description.
3. Open the Discussion section and go to the chat room, which is where comments are stored under competitor posts.
4. Press 3 points from the top right.
5. Click on the “Export Chat History” button.
6. Remove all ticks, select the last 3-6 months, otherwise the export may take a long time, and save in Json format.

And now we go to any text neural network, upload our Json file to it and write the following prompt:

“You are a marketer with 10 years of experience. My niche [...] I have attached a file with the channel content and user comments.

Analyze the comments and give:

1. Top 10 Pain and Problems - quotes from the comments.
2. Top 5 Fears - What scares people the most?
3. Top 5 wishes - Where they want to go.
4. Objections before purchase.
5. The words and phrases they use themselves.

Important: If there are few comments (for example, less than 200-300), the conclusions may not be accurate enough. The more real messages the AI analyzes, the more objective the result will be.

From the received answer, we conclude what objections should be worked out, what content should be done in accordance with the desires, fears and pains of the audience, as well as what words and phrases to use in posts, stories and videos.

For example, we recently did a similar analysis for clients and received a frequent fear that many are afraid to fly to Egypt in the summer. Also often asked about family holidays to be comfortable with children. So, the content plan should add publications about the safety of holidays in the summer in Egypt, a selection of family hotels and answers to frequent questions of parents. Such content will not be based on guesses, but on real requests of the audience.

How to analyze competitors using neural networks

To analyze competitors, the process is almost the same. Only instead of going to chat discussions export the channel with publications.

We also go to any text neural network, upload a new Json file to it and write the following prompt:

“You are a marketer with 10 years of experience. My niche [...] Analyze competitor content (headings, structure, tonality).

1. How well do headlines capture attention?
2. Is the structure easy to read?
3. What tone of communication is used?
4. What triggers and messages are used?
5. What topics are repeated most often?
6. Are calls to action used and appropriate?

Highlight:

1. Strengths
2. Weaknesses / What can be improved
3. Specific recommendations on how to make this block better than a competitor

At the end of the analysis, give a general conclusion:

What are the top 3 insights and insights I can take from these competitors for my account? What should I do differently?

After receiving the analysis, select 3-5 main conclusionsWhat works well for them, what does not work at all, what is especially catchy and articulate 2-3 hypothesesHow to improve your account: what to implement, what to rebuild and where to strengthen the feed.

Do not copy your competitors, but adapt. Your task is to find patterns:

• What topics are repeated;
• which formats are gaining more discussion;
• What promises do everyone use?
• That's what nobody says.

The latter often becomes the basis of strong positioning.

How to analyze your own social networks

The same method is suitable for analyzing your own channel. Upload content and comments, ask AI to identify strengths and weaknesses, identify audience interests, and offer recommendations for content improvement.

As a result of this analysis, you will have not just a list of ideas, but the actual basis for creating content strategy, advertising campaigns and positioning.

Totally.

The network itself does not know your customers. But if you give her comments, posts, and audience feedback, she’ll find patterns in minutes that would manually take hours or even days.

Use neural networks not instead of marketing analysis, but as a tool that helps you work faster with data and make decisions based on facts, not assumptions. This is where their main value lies today.