Skip to content
AI for ads

Prompts for Ads Analysis: 25 Questions to Ask Claude or ChatGPT

Ready-to-use prompts for analysing Meta Ads, Google Ads and Shopify data with AI, plus the context to give first and the format that makes answers easy to check.

Updated 5 min readBy Tera Ads editorial teamFacts checked

On this page
  1. The context block
  2. Prompts for spend and efficiency
  3. Prompts for creative
  4. Prompts for audiences and structure
  5. Prompts for Google Ads
  6. Prompts that bring in returns
  7. Getting answers you can check
  8. From analysis to action
  9. Common mistakes
  10. Frequently asked questions

Good prompts for ads analysis share three parts: context about your business, the data and period to use, and a specific question with the format you want back. Tell the assistant your break-even ROAS, return rate and attribution setting first, ask one question at a time, and request a table plus the rows behind each conclusion. The prompts below work in Claude or ChatGPT, with uploaded exports or a live connector.

Key takeaways

  • Start every analysis with a context block: margins, break-even ROAS, return rate, currency and attribution setting.
  • Name the metric, threshold and period in every question.
  • Ask for tables and the evidence behind each conclusion, so answers can be checked.
  • Separate "what happened" questions from "what should I do" questions.
  • Reuse the same prompts weekly so results are comparable.

The context block

Paste this at the start of a conversation and fill in your numbers. It stops the assistant judging your campaigns against generic benchmarks.

We're a D2C brand selling [product] in [country] through Shopify. Average order value is $[x]. Contribution margin after product, shipping and fees is [y]%, so break-even ROAS on kept orders is [z]x. About [a]% of orders are returned or refunded. Meta attribution setting is 7-day click, 1-day view. All money is in USD. When you answer, state the date range and the setting you used.

If you don't know your break-even ROAS, the break-even ROAS guide shows the one-line formula.

The three parts of a good analysis prompt
The three parts of a good analysis prompt

Prompts for spend and efficiency

  1. "Which campaigns spent the most in the last 30 days? Show spend, purchases, cost per purchase and ROAS in a table, sorted by spend."
  2. "Which ad sets have a cost per purchase more than 50% above our average over 14 days, with at least $250 spent?"
  3. "Show weekly spend and ROAS for the last eight weeks. Did efficiency fall as spend rose?"
  4. "Which campaigns are below break-even ROAS on platform numbers? Which are close enough that returns would push them below?"
  5. "Compare blended results: total spend across Meta and Google against total Shopify revenue (MER), by week." See MER vs ROAS.

Prompts for creative

  1. "For each active ad, show spend, CTR, frequency and cost per purchase over 14 days. Which ads show falling CTR with rising frequency?"
  2. "Group our ads by their opening hook. Which hook type has the best cost per purchase with at least $500 spend?"
  3. "Which ads get high CTR but low conversion rate? List them with landing page."
  4. "What do our three best ads by cost per purchase have in common: format, length, offer, opening line?"
  5. "Which ads have run for more than 45 days? Show their weekly CTR trend."

Prompts for audiences and structure

  1. "Which ad sets target overlapping audiences? Show their CPMs side by side."
  2. "How much spend goes to retargeting versus prospecting, and how does cost per new customer compare?"
  3. "Which ad sets haven't exited the learning phase, and how many conversions did each get last week?"
  4. "Compare results by age and gender breakdown. Where does cost per purchase differ by more than 40%?"
  5. "Which placements spend the most with the worst cost per purchase?"

Prompts for Google Ads

  1. "List search terms with more than $50 spent and no conversions in 30 days, grouped by theme, as negative keyword candidates."
  2. "Split search spend into brand and non-brand. Show ROAS for each."
  3. "Which Shopping products got clicks but no sales in 60 days?"
  4. "Which campaigns are limited by budget, and which by target ROAS?"
  5. "Compare conversion value with Shopify revenue from Google-tagged orders for the same month."

Prompts that bring in returns

These need Shopify orders with UTM campaign, plus their refunds and returns. They matter because platform ROAS counts returned and refunded orders as sales. In cash-on-delivery markets such as India, add delivery outcomes from your shipping platform, since refused parcels (RTO) are returns too; True ROAS after RTO and COD explains the calculation.

  1. "Join orders to refunds and returns by order number. Calculate the return rate by UTM campaign for orders past our return window."
  2. "Calculate real ROAS on kept orders for each campaign. Which campaigns change rank compared with platform ROAS?"
  3. "Which products have the highest return rate, and what reasons do customers give?"
  4. "Which regions or postcodes have a return rate above 35% with at least 30 orders?"
  5. "Estimate how much monthly profit we lose to returns, using $[x] shipping each way."
Prompt categories, from spend to returns
Prompt categories, from spend to returns

Getting answers you can check

What to request in every analysis answer.
Ask forWhy
A table, not paragraphsEasy to scan and compare with the platform
Date range and settings usedCatches the most common mismatch
The rows behind each conclusionLets you verify in a minute
Totals that reconcileRevenue by campaign should add up to the total
"Say if the data can't answer this"Reduces confident guesses

From analysis to action

Keep diagnosis and recommendations apart. First ask what happened and check it. Then ask: "Based only on the tables above, suggest up to three changes, the evidence for each, and how we'd know in two weeks whether it worked." Asking for the success measure up front turns a suggestion into a small test, and it stops the assistant recommending changes it can't justify from the data. Using ChatGPT for ad analysis covers preparing the data these prompts need.

Common mistakes

Skipping the context block. Without margins and return rate, the assistant judges by generic benchmarks.

Asking several questions at once. Answers get shallow; ask one, then follow up.

Mixing periods. Compare the same dates across Meta, Google and Shopify.

Asking for recommendations first. Diagnose, check, then decide.

Changing prompts every week. Reusing the same prompts makes week-on-week comparisons fair.

Tera Ads works out your store's profit after returns from your Shopify sales and shows every Meta Ads and Google Ads campaign in one table with the ROAS each platform reports, which gives you checked numbers to paste into any prompt. It is free for one business.

Frequently asked questions

What is the best prompt for analysing Facebook ads?

There's no single one. Start with a context block covering margins, break-even ROAS and return rate, then ask a specific question with a metric, threshold and period.

Do these prompts work with Claude and ChatGPT?

Yes. They work with uploaded spreadsheet exports in either assistant, or with a live connector to your ad account where your plan supports one.

How do I stop AI giving generic marketing advice?

Give it your own numbers and targets, and ask it to base every conclusion only on the data provided, saying when the data can't answer.

Should I share customer data in prompts?

No. Ad analysis rarely needs personal data. Remove names, phones and addresses from order exports before uploading.

How often should I run these prompts?

Weekly for spend, creative and search terms; monthly for returns, audiences and blended results.

See what your ads really earn.

Connect your store and ad accounts. Free for one business, no card needed.

Create free account