Experiment Readout Deck — Evidence to Decision
Turn pasted experiment results into an evidence-linked seven-slide decision outline. It labels supplied facts, transparent arithmetic, and [UNVERIFIED] gaps separately, so a team can discuss rollout options without inventing significance, causality, or outcomes.
#Produtividade
Avaliação
São necessárias mais avaliações
Vendas
0
Como usar
Executar na Capafy
Também em aplicativos externos
Fornecido pelo publisher
DeepSeek V4.1 Flash
✨ Experiment evidence, shaped for the decision meeting
Paste your experiment brief, observed measures, qualitative notes, and decision deadline. This Agent turns the material you provide into a seven-slide narrative that keeps facts, arithmetic, uncertainty, and options visibly separate.
⚙️ How it works
- Paste the question, conditions, audience definition, period, measures, and success criteria.
- It creates an evidence ledger and labels every item
SUPPLIED,DERIVED, or[UNVERIFIED]. - It shows the formula for any arithmetic based on your numbers.
- It turns the result into a slide-by-slide decision outline with limits, options, and an action register.
📦 What you receive
| Deliverable | What it does |
|---|---|
| Decision brief | States the decision, observed result, limits, and unanswered questions |
| Evidence ledger | Keeps supplied facts distinct from arithmetic and missing inputs |
| Seven-slide outline | Provides a title, takeaway, evidence, and visual suggestion for each slide |
| Option matrix | Compares rollout, follow-up, or hold options against buyer-supplied criteria |
| Action register | Names missing evidence and uses supplied owners and dates when available |
💡 Why use it for each experiment cycle
Each new result changes the evidence, limits, and decision context. A fresh readout makes the next discussion comparable without copying old assumptions forward.
What makes it different
- It is for experiment-result decisions, not a general deck request.
- It puts denominator, period, and variant checks beside each comparison.
- Honesty first: it reasons from your pasted material and model knowledge only. It does not browse, retrieve records, or prove causality or statistical significance.
👤 Built for
Product, growth, marketing, and operations teams preparing a decision meeting from their own experiment notes and metrics.