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Prompt Details

Model
(claude-5-sonnet)
Token size
527
Example input
[DATA]: Last week's signup metrics for our SaaS: Free signups 287 vs 245 prior week (+17%). Paid conversions within 7 days: 8 vs 14 (-43%). Average time-to-paid: 3.2 days vs 2.1 days (+52%). Source mix: 60% organic search, 25% Twitter, 15% direct, similar to prior week. Note: we launched a free trial extension last Wednesday.
Example output
**Headline:** Free signups went up, paid conversions went down, and the gap is almost certainly the new trial extension giving people more time before deciding. **What the numbers show:** - Free signups: 287 vs. 245, +17% week-over-week. Real increase. - Paid conversions in the 7-day window: 8 vs. 14, -43%. Substantial drop. - Time-to-paid: 3.2 days vs. 2.1 days, +52%. People are taking longer before converting. - Channel mix is roughly stable, so the changes aren't explained by traffic source shifting. **Likely explanations:** 1. **Trial extension changed conversion timing, not conversion rate.** Most likely. The 7-day window now captures fewer conversions because the extended trial pushes some of them past the window. People are still converting; just later. Confirm: check 14-day or 21-day conversion in two weeks. If 14-day conversion is comparable to last week's 7-day conversion, this is the answer. 2. **Trial extension brought in lower-intent signups.** Possible. A more generous trial could attract people who are less serious about converting. Confirm: check the source mix more carefully (specifically whether the additional 42 signups came disproportionately from one channel) and check qualitative signals like activation rates. 3. **Genuine drop in paid intent, unrelated to the trial change.** Lowest priority but worth ruling out. Could be a competitor launch, a pricing change rumor, seasonality. Confirm: look at the absolute paid conversion number from two weeks ago and the pattern over the last 8 weeks. **What's not in the data:** - We don't see the conversion outcomes for users who signed up before the trial change. Their "7-day window" expired before the change, so the data shown is for a different cohort than prior weeks. - We don't see activation metrics (whether new signups did the key onboarding actions). If activation dropped alongside paid conversion, that's a stronger signal of lower intent. - We don't have a comparison to historical trial-extension experiments, if any exist. **What to do next:** 1. Wait two weeks before drawing a strong conclusion. Look at 14-day and 21-day conversion for last week's cohort. 2. Pull the source mix for the 42 marginal signups (new signups vs. prior week's count) to check whether they came from a different channel mix than the baseline. **Calibrated read:** Suggestive but needs more data. The most likely story (timing shift from the trial extension) is a clean explanation that fits the pattern, but it's a hypothesis until the longer-window conversion data lands.
🌀 Claude

Data Narrative Writer

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CLAUDE-5-SONNET
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Turns a set of numbers into a narrative that explains what happened and why it matters, without overstating what they prove. Leads with the pattern, ranks likely causes by plausibility with what would confirm or rule out each, names what the data can't tell you, and gives a calibrated confidence read instead of a flat "the data shows X" recap. Won't claim a cause from a correlation, and flags when a move is just noise. One of 40 in the Pemway Power User Pack.
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Added 6 hours ago
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