Custom Reports

The built-in reports (daily check, bleeders, winners, fatigue) cover 90% of ad management. But when you need to dig deeper — audience demographics, device performance, placement analysis — you need custom reports.

Basic Structure

Every custom report has three components:

Level — Campaign, adset, or ad
Fields — Metrics to include (spend, CTR, CPC, etc.)
Breakdowns — How to slice the data (age, gender, device, etc.)

Command Syntax

./scripts/meta-ads.sh custom \
  --level [campaign|adset|ad] \
  --fields "field1,field2,field3" \
  --breakdowns "breakdown1,breakdown2" \
  --preset [date_range]

The Level Parameter

Controls which object type you’re analyzing.

Campaign
Adset
Ad

Use when: You want account-level or campaign-level performance.

./scripts/meta-ads.sh custom \
  --level campaign \
  --fields "campaign_name,spend,impressions,ctr,cpc" \
  --preset last_30d

Example Output:

Campaign Name               | Spend    | Impressions | CTR   | CPC
----------------------------+----------+-------------+-------+------
Spring Launch 2026          | $4,234   | 892,441     | 2.1%  | $1.24
Retargeting — Site Visitors | $1,856   | 234,892     | 3.4%  | $0.89
Prospecting — Lookalikes    | $2,991   | 678,234     | 1.8%  | $1.45

Use when: You want audience-level performance (each adset targets a specific audience).

./scripts/meta-ads.sh custom \
  --level adset \
  --fields "adset_name,spend,frequency,ctr,conversions" \
  --preset last_7d

Example Output:

Adset Name                  | Spend    | Frequency | CTR   | Conversions
----------------------------+----------+-----------+-------+-------------
Women 25-45, Fitness        | $892     | 2.3       | 2.8%  | 42
LAL 1% — Purchasers         | $1,234   | 1.9       | 3.1%  | 58
Retarget — Cart Abandoners  | $456     | 3.2       | 4.2%  | 28

Use when: You want creative-level performance (which specific ad is driving results).

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,cpc,conversions,cost_per_conversion" \
  --preset last_7d

Example Output:

Ad Name                     | Spend    | CTR   | CPC   | Conv | CPA
----------------------------+----------+-------+-------+------+------
Before/After Grid           | $423     | 3.2%  | $0.87 | 28   | $15.11
Customer Testimonial        | $298     | 2.7%  | $1.02 | 19   | $15.68
Product Demo Video          | $287     | 0.6%  | $2.18 | 12   | $23.92

Available Fields

Specify which metrics to include in your report.

Performance Metrics

Field	Description
`spend`	Total amount spent
`impressions`	Number of times ad was shown
`clicks`	Number of clicks
`ctr`	Click-through rate (clicks/impressions)
`cpc`	Cost per click
`cpm`	Cost per 1,000 impressions
`frequency`	Average times each person saw the ad
`reach`	Number of unique people who saw the ad

Conversion Metrics

Field	Description
`conversions`	Total conversions (based on optimization goal)
`cost_per_conversion`	Spend / conversions
`conversion_rate`	Conversions / clicks
`purchases`	Purchase events (if tracking)
`purchase_value`	Total purchase value
`roas`	Return on ad spend (purchase_value / spend)

Engagement Metrics

Field	Description
`post_engagement`	Reactions, comments, shares
`video_views`	3-second video views
`video_avg_watch_time`	Average watch time
`link_clicks`	Clicks to destination URL

Identity Fields

Field	Description
`campaign_name`	Campaign name
`adset_name`	Ad set name
`ad_name`	Ad name
`campaign_id`	Campaign ID
`adset_id`	Ad set ID
`ad_id`	Ad ID

Not all fields are available at all levels. For example, ad_name only works with --level ad.

Breakdowns

Slice your data by demographic, placement, or device.

Demographic Breakdowns

Age
Gender
Age + Gender

Performance by age range.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,conversions" \
  --breakdowns "age" \
  --preset last_7d

Example Output:

Ad Name              | Age   | Spend  | CTR   | Conversions
---------------------+-------+--------+-------+-------------
Before/After Grid    | 18-24 | $45    | 1.8%  | 2
Before/After Grid    | 25-34 | $189   | 3.4%  | 14
Before/After Grid    | 35-44 | $142   | 3.1%  | 10
Before/After Grid    | 45-54 | $47    | 2.2%  | 2

Insights:

25-34 is the highest performing age range (3.4% CTR, 14 conversions)
Consider shifting budget to 25-44 age range

Performance by gender.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,conversions" \
  --breakdowns "gender" \
  --preset last_7d

Example Output:

Ad Name              | Gender | Spend  | CTR   | Conversions
---------------------+--------+--------+-------+-------------
Before/After Grid    | Male   | $156   | 2.1%  | 8
Before/After Grid    | Female | $267   | 3.6%  | 20

Combine multiple breakdowns for granular analysis.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,conversions" \
  --breakdowns "age,gender" \
  --preset last_7d

Example Output:

Ad Name              | Age   | Gender | Spend  | CTR   | Conv
---------------------+-------+--------+--------+-------+------
Before/After Grid    | 25-34 | Female | $142   | 4.1%  | 11
Before/After Grid    | 25-34 | Male   | $47    | 2.2%  | 3
Before/After Grid    | 35-44 | Female | $89    | 3.4%  | 7
Before/After Grid    | 35-44 | Male   | $53    | 2.6%  | 3

Insights:

Women 25-34 are the highest performers (4.1% CTR)
Consider creating dedicated ad sets for this segment

Placement Breakdowns

Platform
Device

Facebook vs Instagram performance.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,cpc" \
  --breakdowns "platform_position" \
  --preset last_7d

Example Output:

Ad Name              | Platform        | Spend  | CTR   | CPC
---------------------+-----------------+--------+-------+------
Before/After Grid    | FB Feed         | $234   | 2.8%  | $1.12
Before/After Grid    | FB Stories      | $67    | 1.9%  | $1.45
Before/After Grid    | IG Feed         | $189   | 3.4%  | $0.89
Before/After Grid    | IG Stories      | $112   | 3.1%  | $0.95

Insights:

Instagram placements outperform Facebook (3.4% vs 2.8% CTR)
Instagram has lower CPC ( $0.89 vs$ 1.12)
Consider shifting budget to IG placements

Mobile vs desktop performance.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,conversions" \
  --breakdowns "device_platform" \
  --preset last_7d

Example Output:

Ad Name              | Device  | Spend  | CTR   | Conversions
---------------------+---------+--------+-------+-------------
Before/After Grid    | Mobile  | $378   | 3.2%  | 24
Before/After Grid    | Desktop | $45    | 2.1%  | 4

Time Breakdowns

# Daily performance
./scripts/meta-ads.sh custom \
  --level campaign \
  --fields "campaign_name,spend,ctr" \
  --time-increment 1 \
  --preset last_7d

Example Output:

Campaign Name         | Date       | Spend  | CTR
----------------------+------------+--------+------
Spring Launch 2026    | 2026-02-26 | $423   | 2.8%
Spring Launch 2026    | 2026-02-27 | $456   | 2.6%
Spring Launch 2026    | 2026-02-28 | $489   | 2.3%
Spring Launch 2026    | 2026-03-01 | $512   | 2.0%  ⬇️ Declining

Use --time-increment 1 for daily breakdowns. This is how the fatigue check works under the hood.

Real-World Examples

Example 1: Find Best Performing Demographics

Goal: Identify which age/gender combo drives the most conversions.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,conversions,cost_per_conversion" \
  --breakdowns "age,gender" \
  --preset last_30d

How to use the output:

Sort by cost_per_conversion (lowest = best)
Identify winning segments (e.g., Women 25-34)
Create dedicated ad sets targeting those segments
Exclude poor performers from broad targeting

Example 2: Instagram vs Facebook Performance

Goal: Decide where to allocate budget.

./scripts/meta-ads.sh custom \
  --level campaign \
  --fields "campaign_name,spend,ctr,cpc,roas" \
  --breakdowns "platform_position" \
  --preset last_30d

How to use the output:

Compare CTR, CPC, and ROAS across platforms
If Instagram outperforms, shift budget there
Or create platform-specific creatives optimized for each

Example 3: Track Creative Fatigue Over Time

Goal: See day-by-day CTR decline for a specific ad.

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,frequency,cpc" \
  --time-increment 1 \
  --preset last_14d

How to use the output:

Plot CTR over time
Identify when decline started
Correlate with frequency — does fatigue start at frequency > 3?
Use this to predict when future creatives will fatigue

Example 4: Audience Comparison

Goal: Which audience (adset) is most efficient?

./scripts/meta-ads.sh custom \
  --level adset \
  --fields "adset_name,spend,conversions,cost_per_conversion,frequency" \
  --preset last_7d

How to use the output:

Sort by cost_per_conversion
Check frequency — audiences with frequency > 3 are saturated
Scale winners (low CPA, frequency < 2.5)
Pause or refresh fatigued audiences (high frequency, rising CPA)

Advanced: Combining Reports

Chain multiple custom reports to build a full analysis.

Workflow: Optimize an Underperforming Campaign

Campaign-level overview

./scripts/meta-ads.sh custom \
  --level campaign \
  --fields "campaign_name,spend,ctr,cpc,roas" \
  --preset last_30d

Identify the underperforming campaign (low ROAS, high CPC).

Ad-level breakdown

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,conversions" \
  --preset last_7d

Find which specific ads are dragging performance down.

Demographic breakdown

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,cost_per_conversion" \
  --breakdowns "age,gender" \
  --preset last_7d

Identify if certain demographics are causing the high CPA.

Placement breakdown

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,cpc" \
  --breakdowns "platform_position" \
  --preset last_7d

Check if specific placements (e.g., Audience Network) are inefficient.

Take action

Based on findings:

Pause underperforming demographics
Exclude inefficient placements
Pause bleeders
Scale winners

Tips for Custom Reports

Keep field lists short

Requesting too many fields slows down the API and makes output hard to read.Good:

--fields "ad_name,spend,ctr,conversions"

Too much:

--fields "ad_name,spend,impressions,clicks,ctr,cpc,cpm,frequency,reach,conversions,cost_per_conversion,roas"

Request only the metrics you need for the specific analysis.

Use breakdowns strategically

Each breakdown multiplies the number of rows in the output. Combining 3+ breakdowns can create overwhelming data.Good for exploration:

--breakdowns "age,gender"

Too granular (hard to interpret):

--breakdowns "age,gender,platform_position,device_platform"

Match preset to analysis type

Analysis Type	Recommended Preset
Daily checks	`last_7d`
Fatigue detection	`last_14d` with `--time-increment 1`
Monthly reporting	`last_30d`
Audience testing	`last_7d` (enough signal without noise)

Export to CSV for deeper analysis

Pipe output to a CSV for analysis in Excel/Sheets:

./scripts/meta-ads.sh custom \
  --level ad \
  --fields "ad_name,spend,ctr,conversions" \
  --breakdowns "age,gender" \
  --format csv > performance.csv

Common Questions

What's the difference between custom reports and built-in reports?

Built-in reports (bleeders, winners, fatigue) are pre-configured for specific use cases and include analysis + recommendations.Custom reports are raw data queries — you get the metrics you ask for, but no interpretation.Use built-in reports for daily workflow. Use custom reports for deep dives and one-off analysis.

Can I filter results (e.g., only ads with spend > $100)?

Not directly in the command. Instead:

Run the full report
Export to CSV
Filter in Excel/Sheets/Python

Or use the raw social-cli command with filtering:

social marketing insights ad --fields "ad_name,spend" --filtering "[{'field':'spend','operator':'GREATER_THAN','value':100}]"

Why are some metrics missing in the output?

Possible reasons:

Metric not available at that level: E.g., ad_name only works with --level ad
Insufficient data: If the time range is too short, some metrics won’t populate
Conversion tracking not set up: Metrics like purchases require proper event tracking

Get Started

Core Concepts

Skills

Configuration

Reports

Actions

Advanced

Basic Structure

Command Syntax

The Level Parameter

Available Fields

Performance Metrics

Conversion Metrics

Engagement Metrics

Identity Fields

Breakdowns

Demographic Breakdowns

Placement Breakdowns

Time Breakdowns

Real-World Examples

Example 1: Find Best Performing Demographics

Example 2: Instagram vs Facebook Performance

Example 3: Track Creative Fatigue Over Time

Example 4: Audience Comparison

Advanced: Combining Reports

Workflow: Optimize an Underperforming Campaign

Tips for Custom Reports

Common Questions

Next Steps

Reports Overview

Fatigue Detection

​Basic Structure

​Command Syntax

​The Level Parameter

​Available Fields

​Performance Metrics

​Conversion Metrics

​Engagement Metrics

​Identity Fields

​Breakdowns

​Demographic Breakdowns

​Placement Breakdowns

​Time Breakdowns

​Real-World Examples

​Example 1: Find Best Performing Demographics

​Example 2: Instagram vs Facebook Performance

​Example 3: Track Creative Fatigue Over Time

​Example 4: Audience Comparison

​Advanced: Combining Reports

​Workflow: Optimize an Underperforming Campaign

​Tips for Custom Reports

​Common Questions

​Next Steps

Reports Overview

Fatigue Detection

Basic Structure

Command Syntax

The Level Parameter

Available Fields

Performance Metrics

Conversion Metrics

Engagement Metrics

Identity Fields

Breakdowns

Demographic Breakdowns

Placement Breakdowns

Time Breakdowns

Real-World Examples

Example 1: Find Best Performing Demographics

Example 2: Instagram vs Facebook Performance

Example 3: Track Creative Fatigue Over Time

Example 4: Audience Comparison

Advanced: Combining Reports

Workflow: Optimize an Underperforming Campaign

Tips for Custom Reports

Common Questions

Next Steps