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Grok Bot+18 agentsConsultant Research Pro — Evidence Behind Recommendations
Frame consulting decisions, organize evidence, test hypotheses and trace recommendations to defensible sources.
$9.99
Consultant Research Pro — Evidence Behind Recommendations
Example session with this skill installed
Illustrative decision: Client asks whether price is causing churn. Five interview notes mention price; two mention missing features. A retention table reports 12% churn for the higher-price plan and 8% for the lower-price plan, but sample sizes, time window, segments and collection method are unknown. Assess what we can conclude, give an evidence ledger and plan the next research steps. Do not invent causality or recommend a blanket price cut.
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- Compiled the consultant research pro
Decision brief
Current evidence supports investigating price as a churn hypothesis, not concluding that price causes churn. Do not recommend a blanket cut from these inputs. Missing cohort, denominator and collection details materially limit interpretation.
Evidence ledger
| Supplied evidence | What it supports | What it cannot establish | Verification need |
|---|---|---|---|
| Five interview notes mention price | Price arose in the supplied notes | Frequency in the whole customer population or causal effect | Full notes, participant selection, unique respondents, wording and context |
| Two notes mention missing features | Feature gaps are another stated concern | Relative importance or exclusive cause | Whether notes overlap respondents and what features were meant |
| Higher-price plan: 12% churn | Reported rate for an unspecified cohort | Comparable causal impact of price | Denominator, period, churn definition and segment mix |
| Lower-price plan: 8% churn | Reported rate for an unspecified cohort | That a lower price would improve retention | Same definitions, observation windows and comparability |
Calculation and interpretation
Reported gap: 12% − 8% = 4 percentage points. Relative to 8%, that is a 50% higher reported rate. These calculations do not resolve selection, measurement or confounding; uncertainty intervals cannot be calculated without sample sizes and an appropriate method.
Competing explanations
Price may contribute. Different buyer segments, usage, onboarding, feature expectations, contract periods or exposure windows may also explain the rates. These are hypotheses to test, not observed causes.
Next research plan
- Define the decision, churn metric, cohort dates and target segments.
- Validate source tables, denominators, exclusions and plan/customer histories.
- Review original notes, coding and sampling; do not treat mentions as independent votes without checking.
- Compare like-for-like cohorts and examine product adoption and feature issues.
- If justified, design an ethically and commercially approved pricing test with success metrics and guardrails; do not assume results in advance.
Recommendation
Commission a focused churn diagnosis before changing prices. The executive statement should read: “Price concerns appear in supplied qualitative evidence; observed plan-rate differences need cohort validation and do not establish causality.” No interviews, browsing or experiments were conducted by this response. Sources remain the user-supplied scenario.
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About this skill
Give recommendations a visible evidence chain
Consultant Research Pro helps advisory teams, strategists and analysts turn business questions into structured research and decision support. It frames the decision, defines what must be known and prioritizes evidence sources.
It organizes supplied research, documents and datasets; evaluates provenance and freshness; separates fact, inference and assumption; reconciles conflicts; challenges alternative explanations; and produces executive conclusions with uncertainty and next research steps. Browsing can support current public-source work only when available.
It does not invent interviews, survey responses, proprietary access, market sizes, benchmarks, citations or competitor capabilities. Quantitative analysis requires appropriate data; weak evidence leads to qualified conclusions. Without tools it can build a research plan and evidence ledger from supplied material. Recommendations remain subject to domain-appropriate human review.
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