ChatGPT Treats Uploaded JSON as Plain Text Instead of Structured Data
Upload a JSON file expecting ChatGPT to query keys and aggregate values. It instead reads the file as a wall of text and answers by string-matching.
Articles tagged with #Data analysis
Upload a JSON file expecting ChatGPT to query keys and aggregate values. It instead reads the file as a wall of text and answers by string-matching.
Turn a finished A/B test into a 1-page summary with winner, lift, CI, segment caveats, novelty risk, and a clean ship/hold/kill decision.
Turn a finalised budget into a 300-word narrative that names variances, justifies investments, and surfaces risks — the document leadership actually reads.
Analyse operational data (support tickets, sales calls, web analytics) with AI — one-line answer, three supporting data points, one caveat, and the next analysis to run.
Generate three caption variants for a chart or table — descriptive, interpretive, actionable — and a 'common misreading' callout so your reader does not draw the wrong conclusion.
Use AI to turn each chart in your deck into a 2-sentence takeaway that names the pattern and the implication — not just describes the bars.
Assemble a structured competitor analysis with AI — positioning, pricing, GTM motion, strengths, vulnerabilities — plus a fact-check pass that catches invented claims.
A workflow for using AI to assemble side-by-side competitor comparisons that hold up under scrutiny, surface real gaps, and feed strategy decisions.
Post a 4-line weekly Slack takeaway your team actually reads — not 'here is the dashboard link.' Lead with what moved, name the cause, surface one surprise, ask the right question.
Read A/B test results with AI as a critical analyst: significance, effect size, sample-size sanity check, validity threats, and the right next action.
Compress a 200-page 10-K into a one-page brief — business model, revenue mix, risks, opportunities, soft-pedalled warnings — tailored to your reader's lens.
An analyst's workflow for using AI to surface trends, anomalies, and hypotheses in monthly financial data — the inputs, the prompt, the validation checks, and where AI tends to mislead.
Identify the step with the biggest gap vs benchmark — not the biggest absolute drop — and surface the one test that has the highest expected ROI, plus the tests not worth running.
Move from 'activation is up 4 points' to 'here is what likely caused it, here is what is still unknown, and here is what data would resolve the ambiguity' — without overclaiming.
Use AI to turn the week's metrics into a sharp KPI summary — TL;DR, 3 wins, 3 risks, and one ask — without losing the narrative.
Turn this week's KPI table into a 200-word weekly report with grounded hypotheses, anomaly callouts, and a single 'thing to watch' — in the time it takes to refill your coffee.
Turn 20+ pages of competitor teardowns and customer-interview notes into a sharp competitive-landscape doc with segments, real gaps, and a named kill-switch assumption — by Thursday.
Turn five PDFs and a folder of slides into a decision-ready one-pager with market size, trends, risks, and a recommendation.
Use AI to apply open and axial coding to qualitative transcripts at scale, with reliability checks that catch hallucinated codes before they reach your analysis.
Turn a 12 × 12 retention cohort grid into a 3-sentence leadership readout that names the actual problem — week-1 direction, long-tail shape, and the one outlier cohort worth digging into.
A repeatable workflow for using AI to cluster open-ended survey responses, extract verifiable themes, and avoid the trap of cherry-picked quotes.
Turn 200 survey responses into a one-page narrative organized by the 2-3 decisions the survey was meant to inform — with verbatim quotes, prior-contradiction flags, and an honest 'too thin to conclude' section.
Compress a packed table into a one-paragraph plain-English summary plus three 'what to do with this' bullets — without re-listing the cells.
Turn hundreds of app reviews, NPS comments, or support tickets into 5-10 themes a PM can act on this sprint.
Advanced Data Analysis turns ChatGPT into a real Python notebook. Here is how to use it without getting fooled by pretty charts.
A repeatable workflow for getting answers out of files instead of paraphrases.
11 prompts that feed AI schemas and aggregates instead of 5,000 raw rows — clean columns, outlier hunts, pivots, narrative reports, formula explainers, sanity audits.