Aa Segment Performance Comparator

Segment Performance Comparator (Adobe Analytics)

Compare the performance of two or more audience segments across key metrics side by side to understand how different visitor groups behave. Uses direct segment-vs-segment comparison to determine a winner, loser, and spread for each metric, with a separate context panel showing segment sizing.

AA Call Budget: AA's runReport accepts a single segmentId per call. For N segments × M metrics the comparison requires N×M calls, plus 1 baseline call for the segment-size context panel. For 3 segments × 5 metrics = 16 calls. Limit to 4 segments and 6 metrics for practical performance. Always confirm the segment/metric list with the user before starting.

AA MCP Tools Used

• findReportSuites — select report suite
• setSessionDefaults — set session context (reportSuiteId + globalCompanyId)
• findSegments — discover and select comparison segments
• findMetrics — resolve metric IDs
• runReport — one call per segment per metric, plus one unsegmented call for sizing context

Phase 0 — Setup

1. Confirm report suite with findReportSuites / setSessionDefaults.

findReportSuites(globalCompanyId: "<gcid>", page: 0, limit: 10)
setSessionDefaults(globalCompanyId: "<gcid>", reportSuiteId: "<rsid>")

Phase 1 — Select Segments

Ask the user which segments to compare. If not specified, prompt:

"Which visitor audiences would you like to compare? For example: Mobile vs. Desktop, New vs. Returning, Paid Search vs. Organic, or specific named segments from your library."

Search for and confirm each segment:

findSegments(page: 0, limit: 50)
# Filter locally by name. Built-in IDs: "Paid_Search", "Purchasers", "Return_Visits"

Note: findSegments does not accept a searchTerm parameter. Retrieve all segments and filter by name locally. Built-in template segments have short IDs like "Paid_Search" that can be passed directly as segmentIds in runReport.

If the user requests a segment that doesn't exist by name, offer to build it first using the aa-segment-builder skill, or suggest the closest existing segment from search results.

Limit: 4 segments maximum per comparison. Advise this limit upfront.

Phase 2 — Select Metrics

Ask the user which metrics to compare. Suggest a balanced mix:

• Volume: metrics/visits
• Engagement: metrics/pageviews, metrics/bouncerate, metrics/pagespervisit
• Conversion: metrics/orders, conversion rate calculated metric
• Revenue: metrics/revenue

Call findMetrics to resolve each metric ID:

findMetrics(expansions: "componentType,categories", page: 0, limit: 200)
# Filter locally by name. Key IDs: metrics/visits, metrics/revenue, metrics/orders, metrics/bouncerate

Limit: 6 metrics maximum. Confirm the final list with the user:

"I'll compare these 3 segments across 5 metrics. This requires 16 report calls (3 segments × 5 metrics + 1 sizing call). OK to proceed?"

Phase 3 — Select Date Range

Ask for or confirm the analysis period:

• Last 7 days (good for quick comparison)
• Last 30 days (recommended default)
• Last 90 days (for seasonal smoothing)
• Custom range

Phase 4 — Run Comparison Reports

4.1 Segment sizing (context only)

Run a single unsegmented call for metrics/visits to get the total population size, then one call per segment for metrics/visits to compute each segment's share of total. These sizing values populate the context panel — they are not used in the comparison matrix.

runReport(
  dimensionId: "variables/page",
  metricIds: "metrics/visits",
  startDate: "<start>",
  endDate: "<end>",
  limit: 1
)
# allVisitorVisits = summaryData.totals[0]

runReport(
  dimensionId: "variables/page",
  metricIds: "metrics/visits",
  segmentIds: "<segmentId>",
  startDate: "<start>",
  endDate: "<end>",
  limit: 1
)
# segmentVisits = summaryData.totals[0]; shareOfTotal = segmentVisits / allVisitorVisits × 100

Reuse these results if metrics/visits is already a comparison metric.

4.2 Per segment per metric

For each segment × metric combination:

runReport(
  dimensionId: "variables/page",
  metricIds: "<metricId>",          # note: "metricIds" not "metricId"
  segmentIds: "<segmentId>",        # note: "segmentIds" not "segmentId"
  startDate: "<start>",
  endDate: "<end>",
  limit: 1
)
# Total = summaryData.totals[0]

Read totals from summaryData.totals[0] (not rows[]). dimensionId is required — use any dimension with limit: 1 for aggregate totals. Segment IDs are the raw id field from findSegments.

Track progress: "Fetching Segment 2 of 3, metric 3 of 5..."

Phase 5 — Build the Comparison Matrix

The matrix compares segments directly to each other — no baseline column.

For each metric row, compute:

For metrics where lower is better (bounce rate, cost per acquisition), invert the winner/loser logic — the segment with the lowest value wins. Mark these metrics clearly in the report.