Meta Ads Usage Examples
This section collects practical recipes for configuring reports and extracting data through the Meta Ads connector.
Recipe 1: Daily Spend and Performance Report
Goal: get a daily summary across all campaigns for the last 7 days with key metrics.
Request parameters:
level:campaigndate_preset:last_7dfields:campaign_name, spend, impressions, clicks, ctr, cpc, cpm, reach, frequency
Result:
| campaign_name | spend | impressions | clicks | ctr | cpc | reach |
|---|---|---|---|---|---|---|
| Summer Sale 2026 | 1 250.00 | 45 000 | 1 200 | 2.67% | 1.04 | 32 000 |
| Brand Awareness | 800.00 | 120 000 | 800 | 0.67% | 1.00 | 95 000 |
| Retargeting Cart | 450.00 | 12 000 | 600 | 5.00% | 0.75 | 8 500 |
Analysis: the Retargeting Cart campaign shows the best CTR (5%) but the smallest reach. Brand Awareness has the largest reach with a low CTR, which matches the campaign's objective.
What could be improved: add a daily breakdown to analyze trends, add a filter to exclude paused campaigns.
Recipe 2: Conversion Analysis by Ad Set
Goal: evaluate ad set performance by conversions and ROAS over the last 30 days.
Request parameters:
level:adsetdate_preset:last_30dfields:adset_name, campaign_name, spend, purchases, purchase_value, purchase_roas, cost_per_resultfiltering:spend > 10(exclude ad sets with minimal spend)action_attribution_windows:7d_click, 1d_view
Result:
| adset_name | spend | purchases | purchase_value | purchase_roas | cost_per_result |
|---|---|---|---|---|---|
| Lookalike 3% | 5 000.00 | 120 | 18 000.00 | 3.60 | 41.67 |
| Interests - Sport | 3 200.00 | 45 | 6 750.00 | 2.11 | 71.11 |
| Retargeting 30d | 1 800.00 | 65 | 9 750.00 | 5.42 | 27.69 |
Analysis: Retargeting shows the best ROAS (5.42), but a smaller sales volume. Lookalike delivers more sales in absolute terms with a ROAS of 3.6.
What could be improved: add a breakdown by platform (publisher_platform) to compare Facebook vs Instagram performance.
Recipe 3: Detailed Ad Report with Creatives
Goal: get a list of ads with creatives and metrics for a manual audit.
Request parameters:
level:addate_preset:last_30dfields:ad_name, adset_name, campaign_name, thumbnail_url, body, link, media_type, spend, impressions, clicks, ctr, video_playsfiltering:media_type = video(video ads only)
Result:
| ad_name | thumbnail_url | media_type | spend | impressions | clicks | ctr | video_plays |
|---|---|---|---|---|---|---|---|
| Product Demo 30s | https://... | video | 750.00 | 22 000 | 550 | 2.50% | 18 000 |
| Customer Story | https://... | video | 620.00 | 18 000 | 380 | 2.11% | 14 500 |
| UGC Review | https://... | video | 340.00 | 10 000 | 290 | 2.90% | 8 200 |
Analysis: UGC Review shows the best CTR among the videos, but a smaller reach. Product Demo has more views, but a slightly worse CTR.
What could be improved: add an age + gender breakdown to understand which audience responds best to each creative.
Recipe 4: Cross-Campaign Platform Comparison
Goal: compare placement performance on Facebook and Instagram.
Request parameters:
level:campaigndate_preset:last_30dfields:campaign_name, spend, impressions, clicks, ctr, cpc, results, cost_per_resultbreakdowns:publisher_platform
Result:
| campaign_name | publisher_platform | spend | impressions | ctr | cpc |
|---|---|---|---|---|---|
| Summer Sale | 800.00 | 30 000 | 2.10% | 1.27 | |
| Summer Sale | 450.00 | 15 000 | 3.50% | 0.86 | |
| Brand | 500.00 | 80 000 | 0.50% | 1.25 | |
| Brand | 300.00 | 40 000 | 0.80% | 0.94 |
Analysis: Instagram shows a better CTR and lower CPC compared to Facebook within the same campaigns. It may be worth reallocating budget toward Instagram.
General Recommendations
- Start at the aggregated level (campaign), then drill down to adset and ad
- Filter out inactive entities:
impressions > 0orspend > 0 - Compare periods of equal length: week-over-week, month-over-month
- Account for conversion delay: data for the last 1-2 days may be incomplete
- Use breakdowns sparingly: each additional breakdown increases the volume of data