Your company wants to communicate regularly with customers. So you start a newsletter. In the beginning, this is often still a motivated process: Collect topics, write an intro, include three updates, add a call-to-action, done.
After two or three issues, the same thing usually happens: The newsletter becomes irregular, too long, too random or sounds different every time. Sometimes it is too promotional, sometimes too dry, sometimes just an unsorted list of internal information.
This is exactly where AI can help - but not by "just writing a newsletter". The real leverage only comes when you specify a clear structure and use AI specifically for topic selection, structure, tonality and variants.
Many teams already use AI for content selectively, but without a system.
Typical mistakes are:
The result: AI produces text, but no reliable communication structure.
So the real bottleneck is not the writing. The bottleneck is the structure.
You don't need a complex editorial system for a functioning monthly customer newsletter. You need a simple, repeatable framework.
I recommend this 5-block model:
Don't start with corporate phrases, but with a clear hook:
A newsletter needs a focus in terms of content. This could be
This is where you place smaller messages:
Every issue should know exactly what the next step is for the reader:
A short, consistent conclusion creates brand character and saves time in creation.
This turns "We need to send something to customers again" into a predictable communication process.
It gets exciting when you don't just use one tool, but compare the same newsletter process with several AI systems.
This is precisely how you can quickly recognize which tool works best in your company for which work step.
Before you open a tool, collect:
Only then do you go into AI.
Gemini is well suited to this workflow if you are already working in the Google ecosystem. Officially, you can use Gemini directly in Gemini Apps, upload files and develop content or include sources in Google Docs with "Ask Gemini" or writing functions. Depending on the function, this requires registration, a suitable plan or activated workspace functions.
A sensible use in the newsletter process is
Example prompt:
Create a monthly newsletter structure for
existing customers.
Goal: inform, strengthen trust, show relevance.
Target group: medium-sized companies.
Tone: professional, clear, approachable.
Build the following structure: introduction, main topic, three short
short updates, CTA, conclusion.
In addition, formulate three subject lines and two
variants for the introduction.
Typical strength of Gemini in the process:
If your team works with Google Docs anyway, the transition from input to draft text is often very direct.
ChatGPT is particularly strong for this use case if you want to systematize the workflow. According to OpenAI, ChatGPT allows you to create projects, bundle chats, upload files and store project-specific instructions. In addition, paying users can create their own GPTs for recurring tasks.
In practical terms, this means for your newsletter creation:
It becomes even more efficient if you define your own GPT for newsletter production, for example with
Typical strength of ChatGPT in the process:
Repeatability. If you want to turn an individual task into a standard process, this is a great advantage.
Claude is particularly suitable if you want to develop a calm, consistent text from several notes, documents or collections of input. Anthropic describes that Claude offers projects for organizing knowledge and chats; in addition, Claude can now create and edit files directly, while Artifacts are used for interactive or visual work states.
In the newsletter process you can use Claude for:
Typical strength of Claude in the process:
Raw material often turns into a very clean, readable overall text - especially if you place value on style, reading flow and linguistic consistency. This assessment is a practical classification of the workflow, not an official product promise. It is supported by the fact that Claude offers projects, learning resources and file-based workflows for professional use.
A sensible testing process looks like this:
Give Gemini, ChatGPT and Claude exactly the same information:
Evaluate each output according to:
Then you define roles instead of beliefs.
For example:
This way, you don't use AI arbitrarily, but process-related.
A consulting company would like to send out a customer newsletter once a month. This is how it works so far:
Beforehand:
Then an AI-supported workflow is introduced.
New:
Afterwards:
The key difference is not that AI "writes texts".
The difference is that an unclear writing process becomes a standardized content workflow.
To get started right away, implement these five steps:
Make it binding:
A single document is enough:
Don't decide based on gut feeling, but compare with the same material.
The best results are almost never achieved by chance. Record working prompt patterns.
Determine
Many companies underestimate newsletters because they see them purely as a marketing channel.
In reality, they are a strategic communication format:
If you don't structure this process, your newsletter will remain dependent on individuals, daily form and time pressure.
However, if you set it up properly with AI, the result is a scalable communication process that delivers better quality month after month with less effort.
This is precisely where the competitive advantage lies: not in the tool itself, but in its systematic use.
If you not only want to understand AI, but also use it in a structured way in your company, then:
👉 Find out more about our AI training:
https://bloo.school
👉 Find out about our Smart Market Fit offers:
https://bloola.com/smf - The Smart Market Fit course
https://bloola.com/smf-system - The Smart Market Fit system for companies
👉 Or find out more about our consulting and automation solutions:
https://bloola.com