Market Pulse

When the user wants to track App Store chart rank changes, find top gainers and losers, detect breakout apps entering the top 100, or identify apps dropping out of charts. Also use when the user mentions "chart movers", "rank changes", "who's rising", "who's falling", "new chart entries", "top gainers", or "market shifts". For broader market overview, see market-pulse. For competitive keyword analysis, see competitor-analysis.

When the user wants to design, deploy, or measure Apple Custom Product Pages (CPP) — the alternate App Store product pages with different screenshots, preview videos, and promo text shown to users coming from specific URLs (typically ad campaigns or social posts). Use when the user mentions "Custom Product Page", "CPP", "alternate product page", "App Store URL variant", "ASA CPP", "campaign-specific landing page", "product page per audience", "App Store Connect CPP", "ppoUrl", "?cpp=" parameter, or "show different screenshots to different ad audiences". For App Store A/B tests on the default page, see ab-test-store-listing. For paid ad campaigns that route to CPPs, see apple-search-ads or ua-campaign.

Design and execute insect population surveys covering survey design, sampling methods, field execution, specimen identification, diversity index calculation including Shannon-Wiener and Simpson indices, statistical analysis, and reporting. Covers defining survey objectives, selecting study sites, determining sampling intensity and replication, choosing sampling methods appropriate to target taxa, standardizing collection effort, recording environmental covariates, identifying specimens to the lowest practical taxonomic level, calculating species richness, Shannon-Wiener diversity (H'), Simpson diversity (1-D), evenness, rarefaction curves, multivariate ordination, and producing survey reports with species lists and conservation implications. Use when conducting baseline biodiversity assessments, monitoring insect populations over time, comparing insect communities across habitats or treatments, assessing environmental impact, or supporting conservation planning with quantitative ecological data.

Fit cognitive drift-diffusion models (Ratcliff DDM) to reaction time and accuracy data with parameter estimation (drift rate, boundary separation, non-decision time), model comparison, and parameter recovery validation. Use when modeling binary decision-making with reaction time data, estimating cognitive parameters from experimental data, comparing sequential sampling model variants, or decomposing speed-accuracy tradeoff effects into latent cognitive components.

Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.