220건 · 관련도순
Build three-tier bookings forecasts from sales opportunities and historical conversion data. Project recurring revenue by customer cohort, assess the reliability of each sales stage, and present forecast numbers alongside their assumptions.
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Structure a cohort analysis for retention, LTV, or behavioural patterns. Use when asked to run a cohort analysis, analyse retention by cohort, segment users by behaviour over time, or calculate lifetime value by acquisition period. Produces a complete cohort analysis framework with methodology, cohort definitions, retention curves, and prioritised interventions.
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Prepare semester-end handoff memos for legal clinic cases using deadlines, case history, and client communication logs. Produce individual case records and a cohort summary covering ownership transitions, unassigned cases, and priorities for incoming students.
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Designs retrospective or prospective clinical cohort study protocols for biomedical and clinical research. Always use this skill when the user needs a cohort-based study plan rather than a general study idea, evidence summary, or mechanistic experiment design. Focus on cohort appropriateness, enrollment logic, baseline time-zero definition, follow-up structure, endpoint definition, variable collection, confounding control, and a coherent primary statistical analysis line. Do not invent data availability, follow-up completeness, outcome ascertainment quality, sample size adequacy, or causal interpretability.
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Plan a user interview topic in PostHog — pick who to target (cohort, emails, or PostHog distinct IDs), draft what to ask about, and prepare the voice-agent context plus a question list. Use when the user asks to "talk to users", "check how users feel about X", "interview some customers", "set up a user interview", "run a user-research call", "find users to ask about Y", or otherwise wants qualitative feedback through a conversation. Walks the user through targeting (cohorts-list, persons-list, or accepting emails / distinct IDs directly), captures the topic, and prompts for agent context and questions before calling user-interview-topics-create. Cohort targeting is resolved to explicit emails/distinct_ids at create time — topics snapshot their audience and do not re-evaluate cohort membership later. Do NOT trigger when the user is uploading a recorded interview audio file (that's the separate UserInterview/transcript flow) or only browsing existing topics with user-interview-topics-list.
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Automate Amplitude tasks through Rube MCP and Composio. Send tracking events, retrieve user activity, update user properties, and manage cohorts, saved groups of users, with checks for identifiers and asynchronous update status.
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Analyze customer profitability and revenue durability for SaaS, subscription, and other recurring businesses. Examine acquisition costs, retention, and revenue trends by customer group, then produce an Excel workbook, summary slide, and issues for further investigation.
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Analyze users grouped by signup period or another shared characteristic to compare retention and feature adoption over time. Produce charts, highlight unusual changes, and recommend follow-up research or experiments to investigate the patterns.
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Evaluates the quality of cohort studies using the Newcastle-Ottawa Scale (NOS). Use when the user provides a cohort study article or text and needs a quality assessment report.
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Fit a retention curve to observed cohort data and project LTV — computed, not estimated. Use when someone has real cohort retention numbers (month 0, 1, 2…) and asks what lifetime value, lifetime periods, or long-run retention they imply, or whether retention is flattening or leaking. Produces a fitted power curve (parameters, R², retention floor), a 24-36 period projection, and a real .xlsx with live formulas where editing ARPU recalculates LTV — via the bundled zero-dependency script.
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Run cohort analysis: retention matrix and LTV by cohort. Churn scoring → churn-risk. "build a retention matrix"
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Time-based cohort analysis with retention and behaviour tracking. Activate when you need to measure how groups of users/customers behave over time — retention rates, revenue by cohort, or feature adoption curves.
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Use when looking for research topics a longitudinal cohort database can answer (NHIS, UK Biobank, an institutional EMR or registry). Profiles the cohort, matches PI expertise, scans literature saturation and returns ranked topic proposals with gap evidence.
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Expert in live learning experiences - cohort-based courses, workshops, webinars, coaching sessions, and real-time facilitation. Covers designing for synchronous learning, building peer accountability, and creating transformative live experiences that self-paced courses can't match. Use when "cohort course, live course, workshop, webinar, group coaching, live session, cohort-based, " mentioned.
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Deconstructs customer cohort behavior with retention curves, LTV progression, and vintage-over-vintage comparison analysis. Use when analyzing cohort data, assessing customer quality, or modeling lifetime value trajectories.
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Build AI cohort analysis systems. TRIGGERS - Use when user needs help with ai-cohort-analyzer related tasks.
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"Conduct cohort analysis to track user behavior over time, build retention matrices, and compare cohort performance. Use this skill when the user needs to measure retention, understand how user behavior changes after acquisition, compare product versions' impact on engagement, or predict LTV — even if they say 'what's our retention rate', 'are newer users behaving differently', 'build a retention table', or 'how long do customers stick around'.".
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Configuring or troubleshooting the Nonprofit Success Pack Program Management Module (PMM) - program delivery, cohort setup, service scheduling, service delivery recording, and attendance tracking for beneficiaries. Trigger keywords: program management module, PMM, Program__c, ProgramEngagement__c, ServiceDelivery__c, cohort setup, bulk service delivery, service schedule, service participant. NOT for designing which outcomes and indicators to measure - use admin/program-outcome-tracking-design. NOT for NPSP donor, household and giving-rollup data - use data/nonprofit-data-architecture.
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Build AI cohort analysis systems. TRIGGERS - Use when user needs help with ai-cohort-analyzer related tasks.
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Prepare and check research documents for clinical decision-support evaluation, including evidence profiles, cohort tables, survival plans, and model assessments. Work with aggregate or synthetic inputs, record sources and review status, and keep outputs outside patient care.
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Design KPI dashboards that help teams make decisions using clearly defined performance measures. Choose relevant metrics, organize summary and detail views, document calculations, and address inconsistent figures, database load, and excessive alerts.
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Plan or run inherited DNA variant detection from whole-genome, exome, or targeted-panel sequencing. Check reference compatibility, sample quality, and combined analysis across samples, with documented commands, resource versions, and paths to variant and annotation outputs.
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Compare cell-type composition and spatial features across conditions in IMC/MIBI cohorts with the patient as the experimental unit, covering pseudoreplication, per-patient aggregation, mixed models, compositional (Dirichlet/scCODA) differential abundance, diffcyt, per-image-to-patient spatial differential testing (SpaceANOVA), batch covariates, and FDR. Use when testing whether a cell type or spatial niche differs between groups, avoiding cell-level pseudoreplication, choosing a differential-abundance method, or correctly powering an IMC cohort comparison.
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Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.
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