Category Entry Points Map

A Category Entry Points (CEP) map lists the buying situations — cues and contexts — that trigger people to enter a category. Unlike segments (who), CEPs answer when and why demand shows up. The map ranks situations by mental availability and a host-computed priority score so growth work focuses on the highest-leverage entry points.

Founders and marketing leaders who need an Ehrenberg-Bass-style entry-point map without a spreadsheet workshop. First-time users can discover /cep from Commands (search “CEP”); experienced product managers run it after a market scan to lock the top three situations worth owning.

Teams often over-invest in persona detail and under-invest in the moments that create category entry. CEP thinking keeps marketing and product bets tied to real buying situations — quarterly planning gaps, compliance deadlines, competitor failures — not vanity demographics. When you know which situations fire most often, and where your brand is already credible, content and acquisition spend stop chasing every segment equally.

After a basic market scan and before heavy brand or acquisition spend. Prerequisites: a clear category definition and at least a draft segment map (or best-in-class assumptions tagged as such). Revisit when a new channel, regulation, or rival launch changes how buyers enter. Pair with competitor-matrix work so competitive association scores stay honest about status-quo alternatives.

1. List 8–15 distinct buying situations — each is one moment, not a segment.
2. For every situation, capture required cues why (motive) and when (timing); add optional cues (where, while, with_whom, how_feeling, preceded_by) when they sharpen the moment.
3. Score prevalence, competitive_association, and brand_credibility as integers 1–5. Justify every 1 or 5. Always include a default alternative (doing nothing, generic AI chat, or spreadsheet).
4. Let the host compute priority_score as prevalence × brand_credibility × (6 − competitive_association) (maximum 125). Do not trust model arithmetic.
5. Sort the map by priority, pick a top-3 with trade-offs (you cannot own every situation), and link high-priority rows to marketing or content artefacts when you can.

• Situations vary in why and when — not eight restatements of the same cue.
• Scores show variance (not all threes); extreme scores have short rationales.
• Assumption-mode cues are tagged assumption until live evidence or validation exists.
• Singleton CEPMAP-001 shows the prioritisation table plus three recommendations with trade-offs.
• High-priority CEPs point toward content or channel work (MKTG-*), or the gap is explicit.

• Treating CEPs as SEG-* personas (“SMB founders”) instead of situations (“when quarterly planning exposes a strategy gap”).
• Inventing priority_score in the model instead of host recompute.
• Skipping the default alternative so competitive association ignores status quo.
• Blocking the canvas behind SerpAPI or connector entitlement — Phase A assumption-mode is free on all models.
• Owning everything in recommendations instead of trading off the top three.

A solo founder maps eight CEPs for “strategy coaching for indie hackers.” Highest priority: why = validate idea quickly, when = weekend hackathon — high prevalence, weak competitive association vs spreadsheets, moderate brand credibility. Top recommendation: own that situation with a lightweight workshop before chasing enterprise RFPs.

A product marketing lead runs /cep after /market. High-priority CEPs cluster around quarterly business reviews and board prep. Capture-gap work (later, with connectors) can show which of those situations the site already covers — but the assumption-mode map is usable without search spend.

1. Run /cep in chat (or emit CEPs during a /market turn).
2. Sculptor produces 8–15 CEP-* buying situations with required cues and scores.
3. Host recomputes priority_score and renders singleton CEPMAP-001 (cep-map) sorted by priority with top-3 recommendations.
4. Assumption-mode tags cues as assumption and keeps the canvas available without SerpAPI.

Open ⓘ on the canvas for this guide; Ask Mentor can critique your live map with asset context.

Malformed JSON shows a recoverable error with copy raw and Fix asset — never a blank canvas. Retry /cep or ask the coach to regenerate. On small local models, Sculptor may split cue generation from scoring so the map still completes without gating the canvas by model tier.