AI Prompts for Making Sense of Amazon Analytics and Sales Insights

AI Prompts for Making Sense of Amazon Analytics and Sales Insights

You don’t grow an Amazon business by guessing. The best brands win because they understand their data — what’s selling, what’s not, what’s wasting ad spend, and where margins silently vanish.

But let’s be honest: digging through Seller Central reports, Amazon Business Reports, and advertising dashboards is exhausting. And messy. Especially when all you want is a straight answer like:

“Why are my profits down this month?”

That’s where AI can help. With tools like ChatGPT and platforms like DataDoe.com, you can analyze large amounts of data through plain-English prompts — turning messy numbers into clear, actionable insights.

Let’s walk through the most powerful prompts you can use to pull intelligence from your data — even if you hate spreadsheets.

Step 1: Get a Quick Overview of Your Business

Start with high-level performance prompts that summarize your sales, traffic, and profit trends.

Prompt 1
Based on this data from the last 30 days (revenue, units sold, ad spend, sessions, conversion rate), give me a simple health report for my Amazon store. Highlight what's improving, what's declining, and why.

Prompt 2
Here’s my Amazon settlement data for the last 3 months. Create a monthly profit & loss summary including sales, fees, ads, refunds, and estimated profit margins.

Prompt 3
Analyze this month vs last month. What changed the most and what might explain the difference?

Pro Tip
Use a tool like DataDoe to sync your data live, so you can ask these questions in real time without downloading 5 reports.

Step 2: Find Hidden Patterns in Sales Performance

Sometimes it’s not the numbers themselves, but what they don’t say outright. Use these prompts to spot silent killers and emerging trends.

Prompt 4
Which ASINs are trending down in sessions or conversions over the last 60 days? Flag anything that might be caused by a listing issue or competitor move.

Prompt 5
Compare my top 10 ASINs. Which ones have the highest refund rate, and how has that changed over time?

Prompt 6
Look at this sales velocity data. Which SKUs are underperforming vs expected, based on their past 90-day trend?

Extra Tip
Don’t just ask “what’s low” — ask “what’s falling.” Sudden drops often signal suppressed listings, hijacking, or keyword ranking issues.

Step 3: Analyze Your Advertising Efficiency

Amazon ads often turn into a black hole. Use AI to figure out what’s working — and what’s burning cash.

Prompt 7
Based on this PPC report, which campaigns are spending the most without generating profit? Include wasted spend and possible action steps.

Prompt 8
Show me which keywords have a high click-through rate but low conversion. What might that tell me about my listing or targeting?

Prompt 9
Analyze these three ad groups. Which has the highest TACoS and what can I do to improve ROAS without killing sales volume?

Pro Insight
If you’re using Amazon's Sponsored Products + Attribution + DSP — use a single prompt like:
“Build a multi-channel ad performance report with top spending campaigns, top converters, and suggested cuts.”

You can also plug in performance data from tools like Perpetua, Quartile, or Amazon Ads Console into ChatGPT — or let DataDoe auto-sync and handle the heavy lifting.

Step 4: Understand Customer Behavior & Product Feedback

Data isn’t just numbers — your reviews, returns, and buyer messages also contain hidden insights.

Prompt 10
Analyze the last 100 reviews across all ASINs. What themes show up in 5-star vs 1-star feedback? Where should I focus improvements?

Prompt 11
Group these customer support messages by topic. Which issues are most common, and how can I fix them at the source?

Prompt 12
Here’s my return reason report. What patterns stand out, and how could I reduce refund rates based on this?

Smart Add-On
You can use Zapier or Make.com to send reviews or returns data to Google Sheets daily — then analyze them with prompts like these.

Step 5: Forecast Performance & Plan Smarter

Use AI to look ahead — not just behind.

Prompt 13
Predict my next 30-day revenue based on the past 90 days. Flag any risk factors that could cause underperformance.

Prompt 14
Create a basic sales forecast per SKU for Q4 based on last year’s data, current trends, and upcoming promotions.

Prompt 15
Help me model 3 profit scenarios: conservative, expected, and aggressive. Include ad spend, refund rate, and COGS assumptions.

Pro Framework
Ask for a “What If” simulation:
“If I double ad spend on these 3 products, what might happen to TACoS, revenue, and profit?”

Bonus: Build a Chat-First BI Workflow

You can turn ChatGPT or DataDoe into your own personal data analyst.

Prompt 16
You’re my eCommerce analyst. I’ll paste in sales and ad data, and you’ll give me a performance summary, top action items, and anything that looks broken.

Prompt 17
Here’s my full P&L report for July. Write a monthly report summary I can send to my business partner.

Final Word

Sellers who understand their data — and act on it — don’t just survive Amazon. They scale it. AI tools let you finally use all the data you’ve been collecting to make faster, better decisions without hiring a full analytics team.

If you want to connect your Amazon reports automatically and use AI chat to pull insights, check out DataDoe — built for sellers who think strategically.

Want even more plug-and-play prompt templates?
Explore the full Analytics & Insights Prompts for Amazon Sellers and start decoding your numbers today.