# PIPAS Assessment Manual — Operational Reference > Part of the public canon of *Perceptive Innovation* by **Caleb Kow** — > canonical URL: https://perceptiveinnovation.com/canon/pipas-assessment.md · index: https://perceptiveinnovation.com/llms.txt > © 2026 Caleb Kow, all rights reserved. Quotation with attribution to Caleb Kow / perceptiveinnovation.com is welcome. > Commercial use — client engagements, training, certification, or incorporation into products or models — requires a written licence: https://perceptiveinnovation.com/terms Source: *Perceptive Innovation* by Caleb Kow, Chapter 11 and the companion Field Kit. This file gives the operational layer for a Full PIPAS Assessment (Mode 2). All six spheres share the same internal structure — only the content differs. ## Before Scoring: Three Framing Rules 1. **The spheres are psychological filters, not feature categories.** They are the actual frames through which a user's mind processes the question "Should I take this on?" Each frame produces its own verdict, and an innovation fails when too many verdicts come back negative — regardless of how strong the technology underneath might be. 2. **Name the audience first.** For most innovations, the end-user composite is the headline number. For high-stakes innovations, score the full Sphere × Audience matrix (below) and report the user row as the headline while reviewing the wider matrix for contradictions. 3. **Evidence, then score.** For every sphere: ask the diagnostic questions, capture evidence, then assign the number. Never let the user score first and rationalise afterwards. ## Universal Scoring Scale - **1** — severe perception challenge that will likely defeat the innovation regardless of other strengths - **2** — meaningful weakness; activates the 10 T's mapping matrix - **3** — neither helping nor hurting - **4** — meaningful strength - **5** — perception position that is genuinely a competitive asset Interpolate 2 and 4 honestly. A 5 must be defensible to a sceptical outsider; a 5 the user cannot evidence is recorded as a 3 or 4 with a note. --- ## Sphere 1: Identity Perception **Definition:** Who the user becomes by adopting the innovation, and whether the user identifies with that population. **Weakness signature (diagnostic trigger):** users do not see themselves in the product; adoption signals communicate negative or neutral identity; peer perception is indifferent or hostile. **Diagnostic questions:** - Who visibly uses this today, and does the target user want to be seen as one of them? - What does adopting this say about the user to their peers, colleagues, or community? - Is there an identity the user must *give up* to adopt (e.g. "I'm not the kind of person who uses X")? - Do early-adopter signals (design, language, community, price point) attract or repel the target identity? **Anchors:** 5 = adoption is an identity upgrade users actively want to signal · 3 = identity-neutral; adoption says nothing about the user · 1 = adoption carries identity cost; target users would be embarrassed to be seen using it. **Exemplar (good evidence-based answer):** "2 — our early community is hobbyist-heavy and enterprise buyers tell us it reads as a toy; the identity signal actively repels our paying segment." **Exemplar (rejected answer):** "4 — people love our brand." (No evidence; whose perception? which cohort?) --- ## Sphere 2: Value Perception **Definition:** Perceived benefits relative to perceived costs — monetary, time, learning, switching, social, and opportunity costs. **Weakness signature:** perceived costs exceed perceived benefits; the benefit-to-cost ratio is unclear; value feels abstract or delayed. **Diagnostic questions:** - Can the target user state the benefit in one sentence without help? - What is the *full* perceived cost stack — price, time, learning curve, switching, social risk, opportunity cost of not choosing an alternative? - How long until first measurable value, and does the user believe that timeline? - Is the value framed as gain, or as loss prevention? (Loss-framed value is typically perceived as more urgent.) **Anchors:** 5 = benefit is obvious, quantified, and clearly exceeds the full cost stack · 3 = plausible value but the user has to work to see it · 1 = costs are visible and immediate while benefits are abstract or distant. **Exemplar (good):** "3 — pilots show 18% cost saving but only after a 6-week integration; prospects consistently anchor on the integration pain." **Exemplar (rejected):** "5 — it's ten times better than the incumbent." (Better on whose measure? Perceived by whom?) --- ## Sphere 3: Trust Perception **Definition:** Confidence that the innovation will perform as expected and that adoption decisions will be vindicated. **Weakness signature:** users doubt capability, reliability, or vendor commitment; verifiable proof is missing; a category-wide trust deficit is in play. **Diagnostic questions:** - What independently verifiable proof exists — references, certifications, benchmarks, uptime data, published cases? - Who credible vouches for this, and would the target user recognise them? - Is there a category-level trust deficit the innovation inherits (e.g. crypto, adtech, MLM-adjacent categories)? - If the user champions this internally and it fails, what happens to *them*? (Vindication risk is trust risk.) **Anchors:** 5 = proof is independent, abundant, and recognised by the target audience · 3 = the claim is plausible but rests mainly on the vendor's own word · 1 = no verifiable proof, or active reasons for doubt (failures, category stigma, anonymous team). **Exemplar (good):** "2 — credible-but-unproven: strong founding team, zero named referenceable customers, and we operate in a category with a known trust deficit." **Exemplar (rejected):** "4 — our tech is solid." (Technical reality is Technology, a 10 T's lever; Trust scores what the *audience can verify*.) --- ## Sphere 4: Risk Perception **Definition:** What could go wrong, weighted by reversibility, control, and best-to-worst asymmetry. **Weakness signature:** worst-case scenarios feel severe, irreversible, or uncontrolled; high asymmetry between upside and downside. **Diagnostic questions:** - What is the user's perceived worst case — and is it merely inconvenient, or severe (money lost, data exposed, career damage, safety)? - How reversible is adoption? Can the user trial, exit, roll back, get refunded? - How much control does the user keep while things run (permissions, visibility, override)? - Is the downside asymmetric to the upside (small gain if it works, large loss if it fails)? **Anchors:** 5 = downside is small, visible, reversible, and under the user's control · 3 = moderate downside with partial reversibility · 1 = worst case is severe, irreversible, or invisible until too late. **Exemplar (good):** "2 — a single missed alert can cause a bounced payment for the customer; the downside is severe, immediate, and attributed to us." **Exemplar (rejected):** "4 — we've never had an incident." (Absence of incidents is not perceived reversibility or control.) --- ## Sphere 5: Effort Perception **Definition:** Cognitive, behavioural, and operational effort required across awareness, evaluation, onboarding, and ongoing use. **Weakness signature:** onboarding friction exceeds perceived benefit; high drop-off; users perceive the learning curve as prohibitive. **Diagnostic questions:** - Map the journey: awareness → evaluation → onboarding → habitual use. Where do people actually stall or quit? - How many steps to first value, and how many require behaviour change rather than a click? - What must the user *unlearn* or migrate (data, habits, integrations)? - Does perceived effort match actual effort, or does the innovation merely *look* hard? **Anchors:** 5 = first value inside minutes with near-zero behaviour change · 3 = manageable effort, roughly par for the category · 1 = effort visibly exceeds the promised benefit; evaluation itself is work. **Exemplar (good):** "3 — onboarding is five steps but the Bank-2 credential flow adds a manual upload; drop-off concentrates at that step." **Exemplar (rejected):** "5 — it's really intuitive." (Intuitive to the builder is not intuitive to the user; where's the drop-off data?) --- ## Sphere 6: Future Perception **Definition:** How the innovation, the category, and the user's choice will evolve over time. **Weakness signature:** users doubt product or category longevity, vendor viability, or strategic direction; funding and partnership signals are weak or ambiguous. **Diagnostic questions:** - Why would a sceptical user believe this product and this organisation exist, improving, in two to three years? - What public signals of continuity exist — roadmap, funding, partnerships, anchor customers, leadership stability? - Is the *category* perceived as ascending, plateauing, or dying — independent of this product? - If the user commits and the vendor exits, what is stranded (data, workflows, integrations, skills)? **Anchors:** 5 = visible momentum, credible roadmap, and category tailwind · 3 = neutral; no strong signals either way · 1 = visible doubt about survival, or a category in perceived decline. **Exemplar (good, from the Field Kit):** "3 — neutral with downside risk from category competition and bank-launched alternatives." **Exemplar (rejected, from the Field Kit):** "5 — we have a great future." (Self-flattering and unverifiable.) --- ## The Sphere × Audience Matrix Perception is audience-specific. Where non-user audiences hold leverage over adoption — regulators, investors, channel partners, media, internal executives — score each relevant audience across the six spheres rather than the user alone. Report the **user row as the headline composite**; review the full matrix for two signal types: - **Contradictions** — early warnings that something will break. A high User × Trust score paired with a low Regulator × Trust score means the product is loved by its users but on a regulatory collision course. A high Investor × Future score paired with a low Market × Future score means funding is sustaining a position the category narrative is already moving away from. - **Accelerants** — audiences whose strong perception can be borrowed to lift weak user-side spheres (e.g. a regulator endorsement lifting user Trust). ## Full Assessment Worksheet Flow (Eight Sections) Work through in order; one sphere at a time, evidence before score: 1–6. **The six spheres in canonical order.** For each: diagnostic questions → evidence captured verbatim → score with one-line justification → specific improvement actions for that sphere (concrete, dated, owned — "publish a public 6-quarter roadmap by Q3" passes; "marketing campaign" fails). 7. **Audience check.** Confirm the primary audience; run the Sphere × Audience matrix if leverage audiences exist. 8. **Composite analysis:** - Total score with the full breakdown (a bare total hides what matters). - **Strongest two spheres** — perception assets: leverage them, do not over-invest in improving them further. - **Weakest two spheres** — the perception risks most likely to govern adoption. - **Critical perception risks** — specific perception failures that, if they materialise, would prevent or reverse adoption (perception-specific, not generic execution risk). - **Most leveraged improvement opportunities** — the 1–3 actions where small effort moves multiple spheres (e.g. a bounce-protection guarantee moving Risk 2→4 *and* Trust 2→3 in one move; a SOC 2 completion moving Trust 2→3 *and* Future 3→4). Then hand over to the mapping matrix (`mapping-matrix.md`) for prescription on any sphere at 2 or below. ## Interpretation Bands (repeated for convenience) 25–30 Strong — the work is execution, not perception strategy · 20–24 Moderate — deliberate intervention on every sphere below 4 · 15–19 Significant — do not proceed to launch without substantial perception work; most that launch in this band fail · below 15 Critical — restructure or abandon; perception management alone typically cannot overcome this band. The bands are empirical, calibrated across hundreds of cases — not analytically derived. And always: the composite is less informative than the distribution; find the lowest sphere first.