Prompt catalog
Browse reusable AI prompts by topic, then open any prompt to copy and adapt it for your workflow.
375 prompts · page 7 of 42
Name the industry or niche, the target market, and up to three specific questions you need answered, and this prompt scopes out the competitive landscape from a blank page. It covers market size and growth trends, the top five competitors, gaps and opportunities, customer pain points, emerging trends, and barriers to entry, delivered as an executive summary plus a detailed breakdown — a useful first pass before commissioning deeper competitive or pricing work.
Supply an existing codebook built from earlier interviews plus a fresh transcript, and this prompt codes the new interview against it. - Passages matching established codes get quoted and labeled - Passages that don't fit any existing code are surfaced separately - New candidate code labels are suggested for those unmatched passages - Useful for spotting codebook drift when too many new codes keep appearing
Paste the slow query along with the database engine, approximate table sizes, current execution time, and any existing indexes, and this prompt diagnoses the real bottleneck — a full table scan, a missing index, an unnecessary join — before rewriting the query for performance. It proposes concrete CREATE INDEX statements, estimates the expected speedup, and suggests an alternative like a materialized view or pre-aggregation when a rewrite alone won't be enough, showing before-and-after versions with an explanation for each change.
Paste in user or customer data, define how cohorts should be grouped, pick a metric to track — retention, revenue, or engagement — and set the time period, for a lighter-weight cohort read than a full retention-table build. Covers cohort performance comparison, retention curves, revenue trends by cohort, behavioral patterns, drop-off points, and the factors separating strong cohorts from struggling ones, plus improvement opportunities.
Describe the recurring problem, its business impact, when it started, and what data you have available, and this prompt runs a structured 5 Whys investigation instead of a quick patch. - Asks why five times to pinpoint the actual root cause - Identifies contributing and systemic factors behind it - Produces corrective actions and preventive measures - Ends with a concrete implementation plan
Name the reporting cadence, the business area, and up to four report sections, and this prompt plans an entire recurring report's worth of visuals at once. For each section it recommends 2-3 charts with the exact source columns and encoding, writes a chart title that states the finding rather than just describing the data, and adds a fill-in-the-blank caption template, then generates a rerunnable Python script that builds every chart from one DataFrame and exports consistently styled PNGs each period.
Describe the product, its industry, and your current assumptions about the buyer, and this prompt researches and builds two or three detailed customer personas around them. Covers demographics and psychographics, pain points, goals and motivations, buying behavior, information sources, decision criteria, and objections to overcome — treat the result as hypotheses to validate with real customer interviews, not a finished answer.
Paste a draft set of interview questions to sanity-check before running them with real participants. - Flags leading language in each question - Flags ambiguity and structural problems - Offers a revised version alongside every critique - Pairs well as a review pass after drafting an interview guide
Specify the entity type being cohorted, how cohorts are defined (signup month, hire date, etc.), the key metric to track, the time granularity, and the relevant dataset columns, and this prompt builds a full cohort by time period retention or engagement table from raw data. It flags which cohorts meaningfully beat or lag the average, checks whether newer cohorts trend better or worse over time, runs a time-to-event calculation like time to 50% churn, and delivers the Python or SQL code that generates the whole analysis plus a heatmap.