SOCIAL MEDIA

Which Is Best for Content Creators?


AI chatbots like ChatGPT have become ubiquitous and vital to how many knowledge workers, content creators, and business owners operate.

But as powerful as ChatGPT is, it’s not the only player in the game — and sometimes, exploring alternatives can reveal new ways to streamline your workflow.

That’s where this guide comes in.

Instead of just rating chatbots based on generic criteria like accuracy, speed, and creativity, I wanted to see how they perform in a real-world content workflow.

So, I paid for the subscriptions (courtesy of Buffer’s AI Tools stipend that will help me recoup those costs) and fed them data from my own social media, and gave a structured challenge to each one designed to evaluate how well they take existing inputs and turn them into meaningful insights.

Let’s dive into the details and determine which chatbot delivers the best results.

The experiment: How I tested the chatbots

There’s no shortage of AI chatbot comparisons online, but many focus on isolated prompts rather than real-world use cases — especially those relevant to you, our audience of creators, and small business owners.

To truly test how useful these tools are for creators, I needed a challenge that mirrored how we actually use AI in a content workflow.

So, instead of throwing random questions at each chatbot, I set up a structured experiment:

  1. I uploaded a CSV file with 60 days of my LinkedIn posts and their performance data—real engagement metrics from my latest posts.
  2. I gave each chatbot a series of interconnected prompts to see how well it could analyze, generate, and refine content.
  3. I kept everything within one continuous conversation, testing their ability to retain and apply context.

What I was testing for

This test was designed to evaluate each chatbot across five key areas:

  • Data analysis: Can it break down LinkedIn performance metrics and extract useful insights?
  • Creativity & content generation: Can it generate fresh, non-generic (super important) content ideas based on real engagement data?
  • Format adaptation: Can it transform a high-performing idea into multiple content formats (LinkedIn post, Twitter thread, short-form video script)?
  • Strategic insights: Does it offer clear, actionable advice to improve content performance?
  • Workflow optimization: Can it help streamline content planning, repurposing, and tracking?

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It’s important that I clarify here: I’m no machine learning engineer, simply someone who has played around with enough chatbots, and has a decent context of different social media needs. So if you’re looking for a very technical analysis, you won’t find it here.

The chatbots

I selected five leading AI chatbots for this experiment, each with different strengths, pricing, and features:

  • ChatGPT
  • Claude
  • Google Gemini (formerly Bard)
  • Perplexity AI
  • DeepSeek

Now, let’s get into the challenge and see how they performed.

The challenge

Each chatbot was given the same structured test — a continuous conversation where they had to analyze LinkedIn performance data, generate new content ideas, adapt content across formats, offer strategic insights, and create a workflow for ongoing content success.

After uploading the CSV file containing my posts and data, I asked each bot these questions:

  • Here’s my LinkedIn performance data. What types of posts performed best and why?
  • Based on what worked, suggest five new LinkedIn content ideas.
  • Take the best-performing idea and turn it into a LinkedIn post, a Twitter thread, and a short-form video script.
  • How can I improve my LinkedIn engagement rate based on this dataset?
  • Create a content workflow that helps me repurpose high-performing content and track engagement.

Here are the results.

ChatGPT

Best at retaining context

Rating: 3.5/5

Pricing: Free with limited access; $20 per month for GPT-4

ChatGPT is OpenAI’s flagship chatbot and arguably the most well-known AI tool on this list. With its ability to generate structured responses, adapt content across formats, and provide strategic recommendations, it’s a strong contender for creators looking to streamline their workflow.

ChatGPT started strong analyzing the average performance of each post type, showing that analysis, and then giving a strong, nuanced list of takeaways and recommendations. It didn’t state anything too unique (videos performed best, carousel posts had the most impressions), but the insights were good to have.

However, the request for engagement rate improvement ideas showed off ChatGPT’s data analysis capabilities even better. It broke down the engagement rate data by post type, day, and even hour.

Then, more impressively, it gave a list of actionable tips, including the best time to post on LinkedIn according to my data — something none of the other tools did. Other suggestions it made were to prioritize video and text posts and improve my early engagement strategy by responding to the comments in the first 30 minutes of posting.

ChatGPT also really shined in delivering hyper-relevant ideas. When asked for unique content ideas, the bot gave me a list that played off my existing high-performing topics and formats. For example, it recommended I share a behind-the-scenes of my LinkedIn video process, an idea I’ll definitely be using.

When asked to turn one of the ideas into different formats, it pulled from its memory of our previous chats, plus the context it had about my preferred voice and tone, to deliver well-structured and relevant results.

The final request for a workflow initially seemed promising, with a clean, structured visual chart mapping out how to repurpose content.

But while that was nice to look at, it wasn’t until I asked for a more practical version — something i could turn into a Notion page or Google Doc, that it became actually useful. This is something I repeatedly struggle with when using ChatGPT to kickstart a visual reference for what my templates or dashboards might look like — getting anything immediately actionable can be difficult. And that’s where the next tool on our list excels.

I’ll conclude with a caveat here: I’ve had a ChatGPT account for a while now — at least a full year — so the bot had a lot of context to pull from as it can retain context from previous chats. So, that definitely influenced its performance and responses. However, I’d call that a point in its favor as it means that it will give you better responses with frequent use.

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Final verdict: ChatGPT is a strong option for content creators who need structured insights, detailed engagement strategies, and adaptable content formats. However, its responses often require additional refinement to become truly actionable. Frequent use improves its recommendations, making it a solid choice for the long term.

Claude AI

Best for generating workflow mockups

Rating: 3.5/5

Pricing: Free with limited use; $20 per month

Developed by Anthropic, Claude AI is designed to be a conversational, long-form assistant with a focus on thoughtful and structured responses. Unlike some of the other chatbots in this experiment, Claude approaches tasks with a more methodical and organized style, making it a compelling option for those who prioritize clarity in their workflows. But how well does that translate to practical scenarios?

Well, instead of going through the prompts chronologically, I want to focus on Claude’s visualization capabilities and state, for the record, that they are the best of the bunch.

From the first prompt, Claude translated the data into something super easy to look at, along with the recommendations that were par for the course for every chatbot tool. Having the data presented in a bar chart immediately gave me a clear understanding of my next steps.

It continued this trend throughout the conversation without being prompted.

My favorite thing about Claude, by far, is its ability to code and create a visual mockup of a workflow or database within the chat in a little preview window on the right. This has made it ten times easier to create Notion pages that do exactly what I need, with minimal time spent figuring out where to place which element.



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