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Found 17 Skills
Analyzes positive customer reviews to surface deep customer insights for ad copy. Use this whenever a user provides customer reviews and wants to understand their customers better, extract VOC (voice of customer), find ad-ready language, or build messaging strategy from real customer language. Trigger for any request involving "analyze these reviews," "what are customers saying," "find insights in these reviews," "VOC analysis," or any variation of wanting to mine customer reviews for creative strategy inputs. Output is always organized by product (if multiple), and surfaces five buckets of insight: pain points, trigger moments, objections, transformations, and standout language.
Create product positioning and messaging frameworks with validation and iteration guidance.
Facilitates the fifth step of a proven ideal-customer (ICP) method: mapping inciting events — the specific trigger moments that move a perfect-fit customer from could-buy-someday to buying-today. Takes a keystones file (K1, K2, … with market segments) and, when available, customer-interview findings; walks the keystones one at a time, harvesting real trigger stories from interview evidence (marked observed) and working backward through brainstorm lenses — crises, seasonal cycles, strategic windows, personal life-changes — for the rest (marked hypothesized), recording each event with the keystone it couples to and how to find prospects in that condition, in INCITING-EVENTS.md (E1, E2, …). Load when the user has keystones and asks what makes customers buy now, what triggers a purchase, or 'run the inciting-events step.' Do NOT load to derive keystones or deal-breakers (previous steps), to write the final ideal-customer definition (next step), or to write the ads themselves.
Facilitates the second step of a proven ideal-customer (ICP) method: distilling raw company observations into the few deep-truth attributes that matter, then classifying each as a strength, a weakness, or deliberately both. Takes an observations list (O1, O2, … — file or pasted), proposes attributes one at a time with their supporting observations, kills generic ones with the Opposite Test ('we love our customers' dies), classifies each with a concrete rubric (a third of the market sees it that way, or some customers buy/refuse for it alone), and records the result in STRENGTHS-WEAKNESSES.md (S1, S2, … / W1, W2, …). Load when the user has raw observations and wants to distill them, asks 'what are our real strengths and weaknesses,' or wants to classify what they learned from the honest-look exercise. Do NOT load to gather the raw observations (the previous step), to derive keystones or deal-breakers from classified attributes (later steps), or for a person's individual strengths and weaknesses.
Builds a customer Needs Stack — the ladder in which every need is a means to the end one level up (buy infrastructure → set up a WordPress site → have a personal website → get a book deal). Anchors the level the user's product satisfies, phrased as the customer's own goal in the customer's own words, then walks downward (the steps the product makes obsolete) and upward (what the customer really wants), crystallizing every level — specific wording, a true means-to-an-end link, named real-world occupants — before moving on. Records the stack in NEEDS-STACK.md with the user's level marked and each level's positioning role: what you do, promise, reference as aspiration, or brag about obviating. Load when the user asks what their customer really wants, what level their product operates at, who their real alternatives (not just competitors) are, or to 'build our needs stack.' Do NOT load to rewrite marketing copy from a finished stack — that is a separate positioning task that consumes this file.