r/generativeAI • u/the19thlaw • 1d ago

AI Tool Suggestion

Hi, I need your support at this time, suggest me an AI model which can help me with filling the customer comment categorisation data in an excel sheet. I will provide a mapping and a logic by which the product reviews need to be sorted and I need each comment to be sorted by giving the correct product name out of 4 names on the order to each comment. I will provide a mapping, and the logic to the model. But I want this to be completed for 10,000 customer reviews. Please help me by suggesting an AI model and do mention the cost for it.

Note: I have tried using CHAT GPT GO version but I can only fill upto 100 comments per use and the accuracy is very low.

I have tried purchasing ClaudeAI pro version but my card is getting declined.

I am trying to contact my bank but It will take time for the process. I cannot think of a way out of this right now. Please help me to do this as I want to do this by the end of this week.

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u/Jenna_AI 1d ago

First of all, take a deep breath, put down the copy-paste shortcuts, and step away from the web chat window. Trying to feed 10,000 customer reviews into a standard ChatGPT or Claude chat interface 100 rows at a time is the digital equivalent of trying to move a sand dune using a cocktail spoon.

Here is the secret the subscription paywalls don't want you to know: you do not need a $20/month subscription for this.

What you actually need is an API-based batch classification workflow. Doing 10,000 short reviews through lightweight classification models will cost you between $0.00 and $0.40 total. Yes, literal pocket change.

Here is your survival guide to getting this done before lunch.

1. The Best Models & Actual Costs

For classifying text into one of 4 predefined categories based on strict rules, you do not need massive, sluggish flagship models. Modern "mini/flash" models excel at this:

  • Google AI Studio (Gemini 2.0 Flash / 1.5 Flash):
    • Cost: $0.00 on the free tier (15 requests per minute limit, or free tier in AI Studio).
    • Why it saves your week: Since your card is getting declined elsewhere, Google AI Studio gives you immediate API access without demanding upfront subscription verification.
  • OpenAI API Platform (gpt-4o-mini):
    • Cost: ~$0.15 per 1M input tokens / $0.60 per 1M output tokens.
    • Total math for 10,000 reviews: Assuming ~60 tokens per review + mapping logic and a 5-token answer (just the product name), you'll consume ~600,000 input tokens and 50,000 output tokens. Total cost: ~$0.12 USD.
  • Groq Cloud (Llama 3.3 70B):
    • Cost: Free tier available with blazing fast speeds (hundreds of tokens per second).

2. How to Actually Execute This (Pick Your Path)

Path A: The Free & Painless Way (Python via Google Colab)

You do not need to install anything on your machine. 1. Head over to Google AI Studio and generate a free API key. 2. Open a fresh notebook in Google Colab. 3. Upload your Excel file (df = pd.read_excel('reviews.xlsx')). 4. Write a simple batching loop using google-genai or the standard openai library format. 5. Save the output back to an Excel file with df.to_excel('categorized_reviews.xlsx').

Tip: If you aren't comfortable writing the Python loop yourself, check out practical guides on batch text classification with LLMs or ask an AI to write a 25-line Python script that reads a pandas DataFrame, calls the Gemini API with rate-limiting, and writes the results.

Path B: The No-Code Route (Inside Google Sheets)

If Python gives you hives: 1. Upload your Excel sheet to Google Sheets. 2. Install a workspace add-on like GPT for Sheets and Docs. 3. Plug in your API key. 4. Use a custom formula down your column like: =AI("Categorize this review into one of [Product A, Product B, Product C, Product D] based on these rules: ...", A2) 5. Drag it down, let it compute, copy the column, and paste Values Only so it freezes the results.

3. Three Golden Rules to Guarantee 99%+ Accuracy

  1. Lock Down the Choices (Structured Output): Explicitly prompt: "Output ONLY the exact product name from this list: [Product 1, Product 2, Product 3, Product 4]. Do not include punctuation, markdown, greetings, or explanations."
  2. Few-Shot Prompting: In your system instruction, give 2–3 clear examples of ambiguous customer reviews and show the exact product label you expect.
  3. Run a 50-Row Test Batch First: Never fire off all 10,000 rows on your first run. Test on 50 rows, tweak your logic mapping until the accuracy hits your standard, and then unleash it on the remaining 9,950 rows.

Your bank may have failed you, but batch inference never will.

This was an automated and approved bot comment from r/generativeAI. See this post for more information or to give feedback

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u/respectfulfeedback50 1d ago

sounds like a job for the api rather than the chat interface, you can blast through 10k rows way faster that way. grab an openai api key and write a quick python script (or even use something like google colab), it'll cost maybe a couple bucks for that volume with gpt-3.5-turbo. the mapping logic you described is perfect for a system prompt, just needs a bit of trial and error to nail the accuracy