⏳ Reclaim hours lost to weekly reporting

♥️ Product research just got 10x smarter

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Hey there!

Weekly reports are essential: they show your growth, your performance and also keep your team aligned.

But let’s be honest…

They’re also time-consuming, repetitive, and often shoved to Friday at 6pm.

The good news? With the right structure, you can use ChatGPT to automatically generate weekly business reports from plain data or a quick summary of your KPIs.

And the best part? They’ll be consistent, insightful, and ready to share. Every time.

Here’s how to set it up. 👇

Step 1: Decide What to Track Weekly

Why this matters: A useful report focuses on the most important numbers, not every detail.

Start by identifying your core metrics. Depending on your business, that could include:

• Revenue & net profit

• Ad spend & ROAS

• New customers or orders

• Conversion rate

• Top-performing products or SKUs

• Refunds, returns, or customer issues

• Inventory changes

• Email subscribers or social growth

Prompt Example:

“Act as a reporting assistant. Help me outline a weekly Amazon FBA business report. I want to track revenue, ad spend, units sold, TACoS, and top 3 products. Keep it concise and easy to scan.”

Step 2: Feed ChatGPT Your Weekly Data

Why this matters: ChatGPT doesn’t pull real-time data, but it can analyze and format the data you provide.

You can either paste:

• KPIs from a spreadsheet

• Bullet points of changes

• Team member inputs

• Notes from meetings

Prompt Example:

“Here is my data for this week:

Revenue: $8,420

Ad spend: $1,230

TACoS: 14.6%

Units sold: 982

Top products: 1) Silicone lunchbox, 2) Collapsible bottle, 3) Travel cutlery set

Write a short weekly report summary with key wins, areas to improve, and a closing note.”

✅ You’ll get a clean summary that’s ready to paste into Slack, email, or Notion.

Step 3: Add Context or Commentary Automatically

Why this matters: Data is only helpful when it’s interpreted. Use ChatGPT to analyze shifts and spot insights.

Prompt Example:

“Add one-sentence insights for each metric above. Highlight what went well or what might need attention. For example, if TACoS increased, suggest why and what to check.”

Output Example:

“TACoS rose to 14.6% — slightly above target. Consider reviewing ad bids on low-converting campaigns.”

Step 4: Format It for Your Platform of Choice

Why this matters: You’ll likely want to paste your report into email, Slack, Google Docs, Notion or a team dashboard.

You can ask ChatGPT to format it accordingly.

Prompt Example:

“Format this weekly report into a clean Notion entry with headers for: Metrics, Insights, Wins, Issues, and Next Steps.”

Or:

“Format as a professional email I can send to my team. Keep the tone friendly and data-driven.”

✅ Your report is now ready to publish or share in under 5 minutes.

Step 5: Build a Reusable Template Prompt

Why this matters: Once you’ve found the format that works, you can reuse it every week with just updated numbers.

Prompt Template Example:

“Each Friday, I want to generate a weekly business report. I will paste the numbers below. Please return a structured summary with sections:

• Overview

• Key Metrics

• Highlights

• Areas for Improvement

• Action Steps

Keep it under 300 words, and use a confident, helpful tone.”

✅ Bookmark this as your go-to reporting prompt. And reporting becomes effortless.

Final Thoughts

You don’t need to choose between clarity and time. With ChatGPT, you can:

👉 Skip repetitive reporting tasks

👉 Get consistent weekly insights

👉 Share your progress with confidence

👉 Spot problems before they cost you

Because great operators don’t just track data, they act on it. And now, you can do both, faster.

Now is your turn: What part of your weekly reporting slows you down the most — gathering the numbers, formatting the report, or interpreting the insights?

Reply and let me know. I can prepare a future newsletter on these topics.

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Key practices include breaking tasks down appropriately (parallel vs sequential), enforcing structured communication protocols, ensuring error handling, monitoring performance, and optimizing with caching and correct model choices.

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