01 · Scan · Performance Scan

Start with the account’s big picture.

Review your KPIs across recent periods to see where performance is improving or slipping. Choose the movement that needs your attention.

Open it in Timeline with the same KPI, scope, and selected period ready to review.

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Performance ScanSample data · Illustration
Scope: All accountKPI: CPAReporting Range: May 8 – May 21Comparison Range: Apr 24 – May 7
CPA · Prior 14 days
$80
CPA · Selected 14 days
$100

+25% CPA

Spend rose from $8,000 to $10,000 while conversions stayed at 100.

Open full analysis in Timeline

02 · Diagnose · Timeline

See what was happening around the shift.

Compare periods and place performance alongside account changes, Auction Context, and your notes.

Review who changed what and when, then narrow the view to the campaigns or dates you want to understand.

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TimelineSample data · Illustration
Scope: All accountKPI: CPAReporting Range: May 8 – May 21Comparison Range: Apr 24 – May 7
Spend
$10,000
Conversions
100
CPA
$100
$80$100$120May 8 · Keyword expansionApr 24May 8May 21

Review Contribution, account changes, Auction Context, and notes around the same period. Timing alone does not establish cause.

03 · Campaign contribution

Know where to focus first.

See how much each campaign contributed to the change in your account’s performance.

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Illustrative example

Why campaign size matters

Account ROAS

4.00× → 3.52×

Larger campaign

$20,000 spend in each period

Campaign ROAS
4.0× → 3.6×
ROAS change
−10%
Share of account decline
80%

Smaller campaign

$1,000 spend in each period

Campaign ROAS
4.0× → 2.0×
ROAS change
−50%
Share of account decline
20%
04 · Ask TimelinePreview

AI gave you a recommendation. See whether the numbers support it.

Ask a question or paste a recommendation. Match the scope, metrics, and dates to review the relevant charts, tables, and account context.

Try a sample recommendation

From your AI tool

A sample recommendation, pasted in

Review Summer Sale before adding budget. CPA has risen over the last 14 days.

Matched to a usable view

Scope
Summer Sale
Metrics
CPA · Spend · Conversions
Dates
Aug 30–Sep 12 vs Aug 16–29, 2026

Preview with a preset example. Checking your own recommendation is coming soon.

TimelineSummer Sale
Demo account · Sample data
Campaign: Summer SaleCPA · Spend · Conversions14 days vs previous 14

Supports the recommendation

The numbers support a review.

CPA rose 71%. The sample data supports checking efficiency before adding budget. Review the surrounding changes to understand why.

Actual product capture. Preset interpretation of sample data.

05 · Save · Saved Views

Pick up where you left off.

Save the KPI, dates, scope, filters, selected changes, and notes behind a finding. Reopen that view without rebuilding the analysis.

Use fixed dates to keep a specific period, or a rolling range to revisit an ongoing question.

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Saved ViewsSample data · Illustration
Scope: All accountKPI: CPAReporting Range: May 8 – May 21Comparison Range: Apr 24 – May 7
Saved View

CPA review · May 8–21

All account · CPA · Campaign breakdown · Prior period comparison

Choose Save View and give the analysis a name. Return through Saved Views to reopen its filters and date settings.

This illustration uses fixed dates. A view saved with a rolling range advances with the available data.

06 · Track · Trackers

See what happened after the change.

Choose the change, scope, and outcome KPI. Trackers compare performance before and after as new data arrives.

See whether results improved, worsened, or stayed similar—whether the change came from you, a platform, a script, or an AI agent.

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TrackersSample data · Illustration

Query review · Change on May 22

Scope: All account · CPA · Before: May 8 – May 21 · After: May 22 – Jun 4 · Two complete 14-day periods

Before change
$100
After change
$90

−10% CPA

Spend $10,000 → $9,000 · Conversions 100 → 100

Observed outcome after the change. Review other changes, demand, and conversion lag before attributing the result.

See the workflow in action.

Explore Adnertia with sample data, or join the waitlist for early access.