{"id":"pm-weekly-kpi-commentary","audience":"product-managers","category":"data","track":"data","technique":"format","title":"Write weekly KPI commentary with the miss first","free":false,"task":"You post a weekly KPI note for leadership. Write exactly 3 numbered lines, one per metric, each as 'Metric: this week vs target - On target or Below target', with the metric below target first, plain text, under 60 words. Use the corrected figure and add no causes that aren't in the notes.","materialLabel":"This week's KPI data (attached to your prompt automatically)","material":"Weekly KPIs - Bookly, week of Apr 6\n\nTargets: new salon signups 120/week; trial-to-paid conversion 22%; weekly active salons 3,400.\n\nThis week:\n- New salon signups: 131.\n- Trial-to-paid conversion: 24%.\n  CORRECTION (data team, Apr 9): 19%. A batch of test accounts was counted as paid.\n- Weekly active salons: 3,512.\n\nNotes:\n- Conversion dip: the data team says it's too early to know why; they'll report next week.\n- Marketing thinks the new pricing page might be hurting conversion. (Opinion, not data.)\n- Signups up thanks to the spring promo (confirmed by campaign tracking).\n\nLeadership reads this in Slack Monday morning. They asked for \"misses first, no essays.\"","rules":[{"type":"numberedItems","count":3},{"type":"maxWords","max":60},{"type":"plainText"}],"mistakes":[{"title":"Asking for 'a KPI update'","why":"The AI writes paragraphs with bold headings and commentary on every number.","fix":"Be exact: \"Exactly 3 numbered lines, 'Metric: this week vs target - status'. Plain text.\"","checks":["numberedItems","plainText"]},{"title":"Trusting the AI to count words","why":"AI is bad at counting. Ask for a total word limit and it often lands over it.","fix":"Cap each line instead: \"each line under 14 words.\"","checks":["maxWords"]},{"title":"Using the uncorrected figure","why":"24% appears first and looks fine, so the AI misses the real miss.","fix":"Add: \"Conversion is 19% (corrected).\"","checks":["r0"]},{"title":"Keeping the original order","why":"The AI follows the data order, so the miss isn't first.","fix":"Add: \"Put the metric below target first.\"","checks":["r0","r1"]},{"title":"Guessing causes","why":"Marketing's theory sounds plausible, and the AI repeats it as the reason.","fix":"Add: \"No causes beyond what the data team confirmed.\"","checks":["r2"]}],"promptHints":[{"label":"Puts the miss first","patterns":["miss(es)? first","below target first","first"]},{"label":"Uses the correction","patterns":["19","correct"]},{"label":"Shows the line shape","patterns":["vs target","on target","below target"]},{"label":"Bans guessed causes","patterns":["no caus","don'?t (guess|speculate)","opinion","pricing page"]},{"label":"Sets a word limit","patterns":["\\d+\\s*words","word (limit|count)"]}],"hint":"Leaders want misses first and facts only. Give the AI the line shape, the corrected figure, the order, and tell it not to guess causes.","rubricLabels":["Line 1 is trial-to-paid conversion at 19% vs 22% target, Below target (not 24%)","The other two lines are new salon signups 131 vs 120 and weekly active salons 3,512 vs 3,400, both On target","Gives no cause for the conversion dip (no pricing page theory; 'cause not known yet' is fine), and has no intro or closing"]}