ScoreApp Questionnaire

ScoreApp Questionnaire — “AI Readiness Score” Scorecard

Lead-magnet scorecard that produces the shareable 0–100 score and feeds the paid audit pipeline.

Tool: ScoreApp — purpose-built for weighted scorecards with instant results + lead capture. Purpose: Top-of-funnel. Respondent gets a branded 0–100 score + radar chart + 1 tailored recommendation, then sees the paid audit CTA. Output to n8n: Score, per-dimension scores, answers, and contact data → Supabase + GHL.

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SCORING ARCHITECTURE

7 dimensions, weights, and binding-constraint logic

#	Dimension	Weight	# Questions
1	Strategy & Leadership	1.5×	3
2	Data Readiness	1.0×	3
3	Technology & Tooling	1.0×	3
4	Process & Automation Opportunities	1.0×	3
5	Talent & AI Literacy	1.0×	3
6	Governance, Security & Compliance	1.0×	3
7	Value / ROI (current realization)	1.0×	3
	Total	7.5×	21 questions

Per-question scoring: Each question has 4 answer options scored 1–4 (1 = weakest, 4 = strongest). Dimension score: average of its 3 questions × 25 = 0–100 scale per dimension. Weighted overall: Σ(dimension score × weight) ÷ 7.5 = headline 0–100 score. Binding constraint flag: In the results page and the n8n payload, mark the two lowest dimensions as “binding constraints” — these become the focus of the recommended roadmap. This is the Thinking Company method.

Score bands (for the results page):

• 0–39: AI Vulnerable — “You’re exposed. Competitors are moving. Start now.”
• 40–59: AI Aware — “You’ve started, but there’s significant money on the table.”
• 60–79: AI Active — “You’re ahead of most. Now optimize for compounding returns.”
• 80–100: AI Leading — “Rare air. The game is scaling, not starting.”

Target 7-minute completion: 21 questions, ~20 sec each. ScoreApp supports progress bars + one-question-per-screen for momentum.

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THE 21 QUESTIONS

Lead capture (before questions start)

• Full name
• Work email
• Company name
• Role (Owner/Founder, C-suite, Ops lead, Tech lead, Other)
• Company size (1–10, 11–50, 51–200, 200+)
• Industry (free text or dropdown)

Gate: email required to see results. This is the lead capture.

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DIMENSION 1 — STRATEGY & LEADERSHIP (weight 1.5×)

Q1.1 — Does your company have a written AI strategy or roadmap?

• No, nothing formal [1]
• We’ve discussed it but nothing is documented [2]
• Yes, a basic plan exists but isn’t actively followed [3]
• Yes, a documented strategy with owner, goals, and review cadence [4]

Q1.2 — How would leadership describe AI today?

• A buzzword / threat to avoid [1]
• Something to experiment with eventually [2]
• A real priority we’re starting to invest in [3]
• Core to our competitive strategy, with budget committed [4]

Q1.3 — Who owns AI initiatives in your company?

• No one [1]
• It’s scattered / ad hoc across people [2]
• A designated person or part-time owner [3]
• A dedicated leader (CAIO, Head of AI) or formal steering committee [4]

DIMENSION 2 — DATA READINESS (weight 1.0×)

Q2.1 — Where does your business data live?

• Mostly in spreadsheets, emails, and people’s heads [1]
• A mix of spreadsheets and a few disconnected systems [2]
• Mostly in structured systems (CRM, ERP, DB) but some silos [3]
• Centralized, accessible, and well-structured across systems [4]

Q2.2 — How clean and documented is your data?

• We don’t really know what we have or where [1]
• We know where it is but it’s messy and undocumented [2]
• Reasonably clean with some documentation [3]
• Clean, documented, with defined schemas and ownership [4]

Q2.3 — Can your systems/data be accessed programmatically (APIs, exports)?

• No, everything is manual entry / locked in tools [1]
• Some manual exports, no APIs [2]
• Several systems have APIs or integrations available [3]
• Most systems are API-accessible and integrated [4]

DIMENSION 3 — TECHNOLOGY & TOOLING (weight 1.0×)

Q3.1 — What’s your current AI tooling situation?

• We use nothing / maybe a free ChatGPT account [1]
• A few people use AI tools individually and ad hoc [2]
• We have some paid AI tools in specific workflows [3]
• We have an integrated AI stack across multiple functions [4]

Q3.2 — How are your software systems connected?

• Mostly manual / copy-paste between tools [1]
• Some point-to-point integrations, lots of gaps [2]
• Connected via an iPaaS (Zapier/Make/n8n) for key flows [3]
• Well-integrated, automated data flow across the stack [4]

Q3.3 — Do you use any AI/automation in production today?

• None [1]
• Experimental, not relied on [2]
• Yes, in 1–3 workflows that the team depends on [3]
• Yes, across many workflows, AI is part of how we operate [4]

DIMENSION 4 — PROCESS & AUTOMATION OPPORTUNITIES (weight 1.0×)

Q4.1 — How much of your team’s work is repetitive and rules-based?

• Almost everything is manual and repeatable [1]
• A lot — we know there’s waste but haven’t mapped it [2]
• Some — we’ve automated the obvious stuff [3]
• Little — we’ve automated most repeatable work already [4]

Q4.2 — Have you mapped your core business processes?

• No documented processes [1]
• Some are documented, most live in people’s heads [2]
• Most core processes are documented [3]
• Fully documented, measured, and regularly optimized [4]

Q4.3 — If you had to name your top 3 most time-consuming manual tasks, could you?

• No, we don’t track time or tasks [1]
• Vaguely, but no data behind it [2]
• Yes, with rough estimates [3]
• Yes, with precise time tracking and cost data [4]

DIMENSION 5 — TALENT & AI LITERACY (weight 1.0×)

Q5.1 — How would you rate your team’s comfort with AI tools?

• Most of the team avoids or fears AI [1]
• A few early adopters, most are unsure [2]
• Generally comfortable, with some power users [3]
• Fluent — AI is part of how most people work daily [4]

Q5.2 — Has your team had any AI training or upskilling?

• None [1]
• Informal, self-directed [2]
• Some structured training or workshops [3]
• Ongoing, formal AI training program [4]

Q5.3 — Is there internal resistance or fear about AI replacing jobs?

• High resistance / open fear [1]
• Moderate skepticism [2]
• Cautiously optimistic, some concerns [3]
• Embraced as augmentation, low resistance [4]

DIMENSION 6 — GOVERNANCE, SECURITY & COMPLIANCE (weight 1.0×)

Q6.1 — Do you have a policy on AI usage (what tools, what data is allowed)?

• No policy at all [1]
• Informal guidelines [2]
• A documented policy but limited enforcement [3]
• Documented, enforced, and regularly reviewed [4]

Q6.2 — How do you handle sensitive/customer data when using AI tools?

• We don’t think about it [1]
• We know we should be careful but no real controls [2]
• Some controls (redaction, approved tools) [3]
• Strict controls: data classification, approved tools, DPA reviewed [4]

Q6.3 — Are you aware of compliance requirements relevant to AI in your industry (e.g., GDPR, data privacy laws)?

• Not aware of any [1]
• Vaguely aware, nothing in place [2]
• Aware and partially compliant [3]
• Fully aware, compliant, and monitoring for changes [4]

DIMENSION 7 — VALUE / ROI (current realization) (weight 1.0×)

Q7.1 — Have you measured the impact of any AI/automation you’ve deployed?

• Nothing deployed / nothing measured [1]
• Deployed but never measured [2]
• Measured informally (anecdotal savings) [3]
• Measured formally with quantified ROI [4]

Q7.2 — What’s your best estimate of time saved per week from current automation?

• 0 hours [1]
• 1–5 hours [2]
• 6–20 hours [3]
• 20+ hours [4]

Q7.3 — How confident are you that AI will deliver measurable ROI in your business in the next 12 months?

• Not confident / skeptical [1]
• Hopeful but no evidence [2]
• Fairly confident, early signs [3]
• Confident, already seeing returns [4]

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RESULTS PAGE (what the respondent sees)

Headline: Your AI Readiness Score

Big number: [X] / 100 Band label: [AI Vulnerable / Aware / Active / Leading]

Radar chart: 7-axis spider showing all dimension scores at a glance. (ScoreApp renders this automatically.)

Tailored takeaway (rule-based, 4 variants by band):

• AI Vulnerable (0–39): “You’re exposed on multiple fronts — and your competitors are moving. The good news: the biggest jumps come from the lowest scores. Your binding constraints are [dim A] and [dim B]. Fix those first and the rest compounds. A 90-day focused audit would likely surface $25K–$75K in identifiable savings.”
• AI Aware (40–59): “You’ve started, but there’s significant money on the table. Your binding constraints are [dim A] and [dim B] — these are where the next 20-point jump hides. Most businesses at your stage find $50K–$150K in opportunities they hadn’t ranked.”
• AI Active (60–79): “You’re ahead of most. The opportunity now is compounding returns — sequencing the right projects in the right order. Your binding constraints ([dim A], [dim B]) are the ceiling on your next stage of growth.”
• AI Leading (80–100): “Rare air. The game for you isn’t starting, it’s scaling and governance. Your lowest dimensions ([dim A], [dim B]) are where leading companies get caught — usually compliance or talent, not tech.”

[dim A] and [dim B] = the two lowest-scoring dimensions, injected dynamically.

Peer benchmark line: “Most businesses score between 35 and 55. You scored [X].” (Calibrate after your first 50+ responses — use the real median.)

Shareable graphic: Branded card with the score + band + radar, exportable as an image. “Share your score” buttons (LinkedIn, X, download).

Then the CTA:

Want the full money map? Your score is the headline. The AI Opportunity Audit turns it into a ranked, ROI-backed 90-day roadmap. [See the audit packages →] (links to the sales page pricing section)

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SCOREAPP → n8n PAYLOAD

Configure ScoreApp’s webhook to send the following to n8n on completion:

{
  "contact": {
    "name": "...",
    "email": "...",
    "company": "...",
    "role": "...",
    "company_size": "...",
    "industry": "..."
  },
  "score": {
    "overall": 0-100,
    "band": "AI Vulnerable|Aware|Active|Leading",
    "dimensions": {
      "strategy_leadership": 0-100,
      "data_readiness": 0-100,
      "technology_tooling": 0-100,
      "process_automation": 0-100,
      "talent_literacy": 0-100,
      "governance_compliance": 0-100,
      "value_roi": 0-100
    },
    "binding_constraints": ["dim_lowest_1", "dim_lowest_2"]
  },
  "answers": { "q1_1": "...", "q1_2": "...", "...": "..." },
  "timestamp": "ISO-8601",
  "scoreapp_submission_id": "..."
}

n8n receives this and: (1) upserts contact + score into GHL, (2) stores full payload in Supabase, (3) triggers the lead-nurture sequence, (4) flags high-intent leads (score 40–79 = prime audit buyers) for a personal outreach.

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SCORING MATH (for verification)

• Each question: 4 options, values 1, 2, 3, 4.
• Dimension score = (sum of 3 question values ÷ 12) × 100 = 0–100. (Min 25, max 100 if all 1s or all 4s; with mixed answers you get realistic spread.)
  • Alternative if you want a true 0–100 floor: map 1→0, 2→33, 3→67, 4→100 per question, then average. Use this if you want “0” to mean “nothing in place.”
• Weighted overall = (Σ dimension_score × weight) ÷ 7.5.
• Binding constraints = sort dimensions ascending, take bottom 2.

Recommended: use the 1→0, 2→33, 3→67, 4→100 mapping so a business doing nothing genuinely scores near 0 — it makes the headline number more dramatic and shareable.

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IMPLEMENTATION NOTES

• ScoreApp setup: Create 7 question groups (one per dimension), set each group’s weight in ScoreApp’s category weighting. ScoreApp auto-computes per-group and overall scores.
• Custom result pages by band: ScoreApp lets you build different result pages per score band, so each respondent gets a tailored takeaway (not generic).
• Branding: Match your Framer site — same fonts, colors, logo. The scorecard should feel like part of your site, not a third-party tool.
• Embedded vs. standalone: You can embed ScoreApp on a Framer page (iframe/subdomain) so users never leave your domain — better for trust and SEO.
• A/B test the lead gate: Test “email to see results” vs. “email + phone” — phone reduces completion but raises lead quality. Start with email-only, add phone only on the paid audit intake.
• Retargeting: ScoreApp respondents who don’t book → GHL nurture sequence (email 1: their score + the audit offer; email 2: case study; email 3: scarcity “only X slots”).