Cja Segment Performance Comparator

Segment Performance Comparator (Customer Journey Analytics)

Compare 2–5 audience segments across a set of key metrics in a side-by-side matrix. The output tells the user not just what each segment looks like in isolation, but which segment wins or loses on each metric — and which differences are large enough to act on.

This skill answers the question "which audience should we focus on?" with data. Segment comparisons drive product decisions, personalization strategy, and budget allocation — so clarity and actionability matter more than exhaustive data.

CJA MCP Tools Used

• findSegments — search for segments by name or keyword
• describeSegment — understand the logic of candidate segments before using them
• findMetrics — resolve base metric IDs
• findCalculatedMetrics — include custom KPIs in the comparison
• listComponentUsage — identify the most-used metrics as default comparison set
• runReport (with segmentIds or adhocSegments) — pull metric values per segment

Phase 0 — Setup

1. Call findDataViews to list available data views.
2. If the user hasn't specified a data view, present the list and ask which to use.
3. Call setDefaultSessionDataViewId with the chosen ID.
4. Ask the user which segments to compare if not already specified. Confirm the metrics to compare them on.

Phase 1 — Identify Segments to Compare

1.1 From user description

If the user named specific segments, resolve them:

findSegments(search: "<segment name>")

For each match, call describeSegment to verify it is the correct one:

describeSegment(segmentId: "<id>")

Show the segment definition summary to the user if there is ambiguity:

"I found two segments matching 'mobile users': Mobile Visitors (All Devices) and Mobile App Users. Which do you want to compare?"

1.2 From plain-English descriptions

If the user says "compare mobile vs desktop users" but there are no matching segments, offer to create ad hoc segments inline for the comparison:

"I don't see pre-built segments for mobile and desktop. I can create temporary ad hoc segments for this comparison using device type. Should I proceed with ad hoc segments, or would you like to create permanent segments first?"

Ad hoc segments are constructed using adhocSegments in runReport — no save required for the comparison itself.

1.3 Segment count limit

Maximum 5 segments for a single comparison. More than 5 creates a matrix that is too wide to read meaningfully. If the user requests more, say:

"I'll limit to the 5 most relevant segments for readability. Would you like me to prioritize by usage count or stick with your list order?"

Phase 2 — Identify Metrics to Compare

2.1 From user specification

Resolve named metrics via findMetrics and findCalculatedMetrics.

2.2 Default metric discovery

If the user did not specify metrics, pull the top metrics by usage. The listComponentUsage tool does not support a limit parameter — it returns all components ranked by usage count; take the top 6–8 from the result:

listComponentUsage(componentType: "metric")
listComponentUsage(componentType: "calculatedMetric")

Prefer calculated metrics over raw base metrics when they measure the same thing — calculated metrics reflect intentional KPI definitions.

2.3 Metric selection for a comparison

Good comparison metrics should be meaningful across all segments. For example, "Revenue" is meaningful for both mobile and desktop users; "App Installs" is only meaningful for mobile. Remove metrics that would be trivially zero for one segment.

If unsure, ask: "Should I use your standard KPI set, or focus on specific metrics like conversion rate, revenue, and engagement?"

Phase 3 — Run the Comparison

For each segment, run a runReport with that segment applied and all comparison metrics included. Note that runReport takes metricIds as a comma-separated string, startDate/endDate (not dateRange), and a dimensionIds (required even for summary-only reports — use a low-cardinality dimension like variables/daterangeday or variables/web.webPageDetails.name). The summary totals for all metrics are in summaryData.filteredTotals:

runReport(
  dimensionIds: "variables/web.webPageDetails.name",
  metricIds: "metrics/visits,metrics/revenue_1,metrics/orders_1_1",
  startDate: "<period start>T00:00:00",
  endDate: "<period end>T23:59:59",
  page: 0,
  limit: 1,
  segmentIds: "<segment id>"
)

For ad hoc segments, use the full CJA segment definition object:

runReport(
  dimensionIds: "variables/web.webPageDetails.name",
  metricIds: "metrics/visits,metrics/orders_1_1",
  startDate: "<period start>T00:00:00",
  endDate: "<period end>T23:59:59",
  page: 0,
  limit: 1,
  adhocSegments: [{
    "func": "segment",
    "version": [1, 0, 0],
    "container": {
      "func": "container",
      "context": "visitors",
      "pred": {
        "func": "streq",
        "val": { "func": "attr", "name": "variables/device_type" },
        "str": "Mobile Phone"
      }
    }
  }]
)

Read metric totals from summaryData.filteredTotals[i] where i is the 0-based index of the metric in the metricIds string.

Run one report per segment. Collect all results into a matrix:

• Rows = metrics
• Columns = segments

Phase 4 — Build the Comparison Matrix

For each cell (metric × segment):

• value[metric][segment] = raw metric value from runReport

For each metric row:

• winner = segment with the highest value (or lowest, for "lower is better" metrics)
• loser = segment with the lowest value (or highest, for inverse metrics)
• range = (max − min) / max × 100 — the spread across segments as a percentage
• significant = true if range > 10% (a meaningful difference worth acting on)

Phase 5 — Generate HTML Comparison Report

Generate the report inline and write to /tmp/cja_segment_performance_comparator_report_<YYYY-MM-DD_HHMMSS>.html.