Always Compare

Skill: Always Compare

Purpose

A number alone is not an insight. "Conversion rate is 3.2%" tells the reader nothing actionable — they cannot tell if that is a crisis or a record high. This skill enforces one rule: every metric ships with a comparison.

When to Use

Before presenting ANY number to the user — in chat, in a report, in a chart caption, in a Slack message, or on a slide. This runs on every analysis output, alongside question-framing (which runs at the start; this one runs at the end).

The Rule

Never show a number alone. Anchor it to at least one comparison.

Pick the comparison that best serves the decision. In priority order:

Two comparisons beat one. A prior-period delta plus a benchmark tells the reader both the direction and the altitude. Use both when you have both.

Instructions

Step 1: Find every number in your draft output

Scan the response you are about to send. Every figure — headline stats, table cells, chart annotations, sentences in the narrative — is in scope.

Step 2: Attach a comparison to each one

For each metric, ask: compared to what? Then pull the comparison from the data:

• Prior period: same metric, previous week / month / quarter (match the grain of the metric)
• Benchmark: site-wide average, cohort average, target, or historical baseline
• Segment: the same metric for a contrasting slice (mobile vs. desktop, new vs. returning, channel A vs. B)

Compute the comparison in the same query where practical — it is cheaper and less error-prone than a second round trip, and it guarantees the filters match.

Step 3: State the delta, not just both numbers

Do the subtraction for the reader. "3.2%, down from 4.1%" is better than "3.2% (last month: 4.1%)". Give direction (up/down) and magnitude (absolute points or relative %) — and be explicit about which you are using: "down 0.9pp (a 22% relative decline)".

Step 4: If you have no comparison data, SAY SO

Do not silently drop the comparison. An unanchored number must carry an explicit flag:

"Conversion rate is 3.2% (no prior period available for comparison)."

Other honest forms:

• "(first month of data — no baseline yet)"
• "(no site-wide benchmark defined; recommend establishing one)"
• "(segment too small to compare — n=14)"

This is a standing obligation of the method (analyst-core): always flag when data is insufficient.

Examples

Bad -> Good

Example: a full finding, done right

Mobile conversion is the problem. Mobile converts at 2.1% vs. 5.4% on desktop — a 3.3pp gap (61% lower relative). The gap widened from 1.9pp in Q1, driven entirely by the payment step, where mobile drop-off is 44% vs. the 26% funnel-wide average. Source: sessions + events, Jan 1-Jun 30 2024, excludes bot traffic.

Every number has an anchor. The reader knows instantly what to do.

Anti-Patterns

1. Never present a bare number. If you catch yourself writing "X is N", stop and add the comparison before sending.
2. Never fabricate a comparison. If the prior-period data doesn't exist, say it doesn't exist — do not estimate, extrapolate, or reach for a plausible-sounding benchmark you didn't compute.
3. Never compare across mismatched filters. The comparison must use the same definition, filters, and exclusions as the metric — otherwise the delta is an artifact. Re-check the WHERE clause on both sides.
4. Never mix up percentage points and percent. 4.1% -> 3.2% is down 0.9pp, which is a 22% relative decline. Saying "down 22%" without the "relative" qualifier misleads; saying "down 0.9%" is simply wrong.
5. Never compare against a period distorted by a known event without flagging it — a holiday spike, an outage, a launch, or a backfill. Check .knowledge/datasets/{active}/quirks.md before choosing a baseline period.
6. Never bury the comparison in a footnote. It belongs in the same sentence as the metric — that is where the reader forms their judgment.
7. Never let charts escape the rule. A bar chart of one period is a bare number in visual form. Show the prior period, a benchmark line, or a segment split.