More signups. A smaller share converted.

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Fictional worked example · Not a published customer artifact. You review the draft; nothing is published without your approval.

What we started withThe same facts, as an email

Fictional project email

Two-period signup review — more signups, lower conversion

Team,

The fictional extract has 1,000 eligible visits and 100 completed signups in Period A, versus 2,000 eligible visits and 160 signups in Period B. The definitions match across periods. The original headline, “Signups increased 60%,” is arithmetically correct: 60 more signups divided by the original 100. Eligible visits increased by 1,000, or 100%.

The signup rate fell from 100 / 1,000 = 10% to 160 / 2,000 = 8%. That is a decrease of 2 percentage points, or a 20% relative decline from A’s 10% rate. The larger visit count coincided with more total signups, while a smaller share converted. This does not establish why the rate changed, statistical significance, or better business performance.

Calendar dates, durations, timezone, export time and finality status are not supplied. Equal duration and data maturity are unverified. The exact eligibility rules, exclusions, missing values, duplicate handling and segment mix are not documented. These are visits and signup events, not established unique people, paid customers or revenue. No experiment, attribution model, spend or customer reconciliation is supplied.

Suggested investigation, not an approved intervention: confirm period coverage and measurement quality, then obtain comparable segment data. No cause, owner or deadline has been established. This fictional report was prepared September 20, 2026, not exported on that date. Keep the workbook as the calculation source; the report is a static reading view without live refresh.

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<header><div class="kicker"><span class="eyebrow">The denominator report</span><span class="eyebrow">Fictional data · Static snapshot</span></div><h1>More signups.<br>A smaller share converted.</h1><p class="intro">Both statements are true. The count grew, but the conversion rate fell in the supplied two-period dataset.</p></header>
<section class="paired" aria-label="Count and rate comparison">
<article class="panel volume"><p class="eyebrow">Signup volume · A → B</p><p class="delta">+60%<small>60 more completed signups</small></p><div class="row"><div class="bar-label"><span>Period A</span><strong>100 signups</strong></div><div class="track" aria-hidden="true"><div class="bar a-count"></div></div></div><div class="row"><div class="bar-label"><span>Period B</span><strong>160 signups</strong></div><div class="track" aria-hidden="true"><div class="bar b-count"></div></div></div><p class="scale">Bar scale: 0–200 completed signups</p></article>
<article class="panel rate"><p class="eyebrow">Signup conversion · A → B</p><p class="delta">10% → 8%<small>Down 2 percentage points</small></p><div class="row"><div class="bar-label"><span>Period A</span><strong>10%</strong></div><div class="track" aria-hidden="true"><div class="bar a-rate"></div></div></div><div class="row"><div class="bar-label"><span>Period B</span><strong>8%</strong></div><div class="track" aria-hidden="true"><div class="bar b-rate"></div></div></div><p class="scale">Bar scale: 0–10% of eligible visits</p></article>
</section>
<p class="finding">Eligible visits doubled, from <strong>1,000 to 2,000</strong>. More signups does not, by itself, mean better conversion.</p>
<section class="section"><div class="section-head"><span class="number">01 /</span><h2>Keep the denominator in view.</h2></div><div class="table-wrap"><p class="scale" id="data-note">Supplied aggregate counts; rates calculated from those counts.</p><table aria-describedby="data-note"><thead><tr><th>Period</th><th>Eligible<br>visits</th><th>Completed<br>signups</th><th>Signup<br>rate</th></tr></thead><tbody><tr><th>A</th><td>1,000</td><td>100</td><td>10%</td></tr><tr><th>B</th><td>2,000</td><td>160</td><td>8%</td></tr></tbody></table></div><div class="formulas"><div><h3>Count change</h3><p>(160 − 100) / 100 = <strong>+60%</strong><br>The change is relative to A’s 100 signups.</p></div><div><h3>Rate change</h3><p>100 / 1,000 = 10%; 160 / 2,000 = 8%.<br>8% − 10% = <strong>−2 percentage points</strong>.<br>(8% − 10%) / 10% = <strong>−20%</strong> relative change.</p></div></div></section>
<aside class="caution"><h2>The arithmetic is clear. The cause isn’t.</h2><p>The larger visit count coincided with more signups, while a smaller share converted. These totals alone do not establish why, statistical significance, or better business performance.</p></aside>
<section class="section"><div class="section-head"><span class="number">02 /</span><h2>What the extract doesn’t tell us.</h2></div><div class="limits"><div><h3>Period coverage</h3><p>Calendar dates, durations and timezone are not supplied. Equal duration is unverified; this is not an established time trend.</p></div><div><h3>Data maturity</h3><p>Export time and processing/finality status are not supplied. Neither period is confirmed final.</p></div><div><h3>Exclusions &amp; definitions</h3><p>The definitions match across A and B. Exact eligibility rules, exclusions, missing values and duplicate handling are not documented.</p></div><div><h3>Unit of measurement</h3><p>Visits and signup events—not established unique people, paid customers or revenue. Segment mix and causal evidence are absent.</p></div></div></section>
<section class="next"><p class="eyebrow">Suggested investigation · Not an approved intervention</p><h2>Check comparability. Then ask what changed.</h2><p>Confirm period coverage and measurement quality. Obtain comparable segment data to investigate the rate difference. No cause, owner or deadline has been established.</p></section>
<footer><p>Source: the guide’s fictional two-period signup dataset. Preparation date: September 20, 2026; data export date unknown.</p><p>Fictional worked example by share/artifacts. Figures and preparation date are invented for demonstration. Keep the workbook as the calculation source. No live data or automatic updates.</p></footer>
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