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Love-vs-like product diagnostic instrument

A measurement instrument that tells love from like across five signals (repeat use, fanatical users, the would-miss test, organic referral, willingness to pay), each with a metric, a numeric threshold, and a data source.

You receive: A JSON object { signals[]{name,question,metric,threshold,data_source}, scoring{love_rule,scale}, cadence } checked for all five signals covered, each measurable, and a scoring rule plus a re-run cadence.

Part of Validate Demand

Opens soon

Cost20 credits

AcceptanceAutomated check against your inputs

ProtectionHeld until verified delivery

This objective is verified and ready. It opens soon, once sign-in and payments are live.

Deliverable interface

The exact vocabulary the automated check enforces: keys, tokens, entry points, and worked examples. Generated from the verification source.

{
 "buyerParamKeys": [],
 "checkNames": [
  "parses_json",
  "five_signals_covered",
  "each_signal_measurable",
  "scoring_present",
  "cadence_present",
  "no_em_dash"
 ],
 "constants": {
  "_YC_EM_DASHES": [
   "—",
   "–"
  ],
  "_YC_LOVE_BUCKETS": {
   "fanatical": "fanatic|love|enthusias|passionate|advocate|raving",
   "organic_referral": "refer|word of mouth|word-of-mouth|organic|invite|\\bnps\\b|recommend",
   "repeat_use": "repeat|retention|return|come back|usage frequency|daily active|weekly active|\\bdau\\b|\\bwau\\b|\\bmau\\b",
   "willingness_to_pay": "\\bpay|paying|willing to pay|revenue|purchase|\\bwtp\\b|subscrib",
   "would_miss": "\\bmiss\\b|disappointed|sean ellis|hard to live without"
  }
 },
 "deliverableLabel": "yc_love_vs_like_diagnostic",
 "documentKeys": [
  "data_source",
  "love_rule",
  "metric",
  "scale",
  "scoring",
  "signals",
  "threshold"
 ],
 "enumLiterals": [],
 "submission": "a JSON document (submitted as a string), validated as data; every check below must pass",
 "tier": "doc-validator"
}

Example

A sample of what this objective produces. Your result is generated for your inputs.

Signals

repeat_use

QuestionDo users come back and use the product on their own without prompting?

MetricDay-30 retention (percent of new users active on day 30) plus weekly active sessions per retained user

ThresholdDay-30 retention >= 40 percent AND median >= 3 sessions per week

Data sourceProduct analytics events (e.g. Mixpanel, Amplitude, or warehouse cohort query)

fanatical_users

QuestionIs there a core segment that uses the product intensely and rates it at the top?

MetricPercent of active users in the top usage decile who also give a 9 or 10 satisfaction/NPS rating

Threshold>= 20 percent of active users are both top-decile usage AND rate 9-10

Data sourceUsage analytics joined to in-app NPS/CSAT survey responses

would_miss

QuestionHow would you feel if you could no longer use this product?

MetricSean Ellis test: percent answering 'very disappointed' (vs somewhat disappointed, not disappointed, n/a)

Threshold>= 40 percent answer 'very disappointed'

Data sourceIn-app or emailed Sean Ellis survey to users active in the last 2 weeks (min n=40)

organic_referral

QuestionDo users bring in new users on their own?

MetricOrganic/referral share of new signups AND viral coefficient k (invites sent x conversion rate)

ThresholdOrganic referral >= 25 percent of new signups OR k >= 0.5

Data sourceAcquisition attribution data plus referral/invite tracking

willingness_to_pay

QuestionWill users actually pay (or pay more) to keep the product?

MetricTrial-to-paid conversion rate (or for free products, percent stating they would pay at the proposed price via Van Westendorp)

ThresholdTrial-to-paid >= 25 percent OR >= 40 percent state willingness to pay at target price

Data sourceBilling/subscription system data plus pricing survey

Scoring

Love ruleScore 1 point per signal that meets or exceeds its threshold (max 5). LOVE = 4 or 5 signals passing AND would_miss must be one of them. LIKE = 2 or 3 signals passing. WEAK = 0 or 1 signals passing. would_miss is a mandatory gate: failing it caps the verdict at LIKE regardless of total.

Scale0 to 5 integer points, one per signal

Cadence

Re-run the full instrument every 90 days (quarterly), and re-run after any major release or pricing change; track each signal as a trendline, not a one-time snapshot.

Get early access to STUD the day it goes live.