AI Marketing Canvas Assessment

AI Marketing Canvas Assessment

Use When

• Use this skill when the requested outcome is specifically a scored assessment and the supplied brief falls within ai marketing canvas assessment.

Do Not Use When

• Use ai-readiness-diagnostic when its narrower output is the real deliverable; do not use this skill as a generic substitute.
• Do not use it to publish, send, spend, alter a live account, or make unsupported legal, platform, performance, or certification claims.

Required Inputs

Capability and Permission Boundaries

Default to read-only: inspect supplied material and report findings. Editing, publishing, contacting people, spending, or changing live systems requires separate explicit authority. Minimum capabilities are read access to supplied files and search across the authorised evidence set. Use only the files, tools, accounts and evidence made available for the engagement, expose every unassessed check, and obtain explicit authority before any mutation.

Degraded Mode

Fallback: if files, network access, platform data, language review or production tools are unavailable, return the narrowest useful qualified scored assessment; mark unavailable checks not assessed and never convert them into a pass.

Decision Rules

Workflow

1. Confirm the exact scored assessment, consumer, market, channel and approval boundary; route to ai-readiness-diagnostic if it is the closer match.
2. Inventory supplied facts, source provenance, constraints and missing inputs; stop if the objective, audience or authority is unknowable.
3. Select the domain method and record the material decision behind it before drafting.
4. Produce the smallest complete scored assessment; keep facts traceable and placeholders visibly unresolved.
5. Test the result against the decision table, domain quality criteria and anti-slop gate; recover by narrowing or qualifying unsupported portions.
6. Deliver the artefact with evidence, assumptions, unassessed checks and the next approval or verification step.

Outputs

Evidence Produced

Quality Standards

• Preserve the domain guidance and East African market context below; replace it only when the requester names another market.
• Use British English unless the target language or market requires otherwise, and verify names, figures, quotations and platform rules before use.
• Make the key choice visible, cover failure and edge cases, and keep the result ready for its named consumer.
• Run the repository's anti-ai-slop ship gate; a blocking factual, cultural, safety or permission defect stops release.

Anti-Patterns

• Writing before the objective and audience are known. Fix: stop and obtain the missing brief fields.
• Reusing a neighbouring skill's template because the headings look similar. Fix: route by the requested scored assessment, not vocabulary overlap.
• Adding a price, result, quotation, platform limit or cultural claim without a traceable source. Fix: verify it or qualify/remove it.
• Treating missing access, evidence or native-language review as approval. Fix: mark the check not assessed and narrow the result.
• Publishing, sending, spending or changing a live account from drafting authority alone. Fix: obtain explicit action-specific authority and retain the approval record.

References

• ai-readiness-diagnostic is the nearest routing comparison for this skill.
• Repository agent guide defines the engine-wide market, safety and anti-slop gates.

Purpose

Most businesses talk about AI in marketing without knowing where they actually stand or what "progress" looks like for their size and context. This skill produces a completed AI Marketing Canvas — a structured diagnostic and roadmap grounded in Venkatesan and Lecinski's (2026) five-step model — that tells a client exactly what step they are on, what they should do in each of the four customer moments, and what their next 12 months should look like.

For the full 41-item AI readiness diagnostic, use the sister skill ai-readiness-diagnostic. This skill focuses on canvas completion and roadmap output.

Framework source: Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd ed. Stanford Business Books.

Required Input

Before generating any output, ask for the following:

1. Client business name — the trading name used in all deliverables.
2. Industry — what sector is the client in (e.g., retail, hospitality, financial services, NGO)?
3. Country / city — where is the business based and where is its primary audience? (Default: Uganda / East Africa)
4. Primary marketing goal — what is the single most important marketing outcome this year?
5. Current tools in use — list any CRM, content tools, scheduling platforms, and analytics tools currently in use. If none, say so.
6. Team size — solo operator, 2–5, 6–20, or 20+ people in the marketing function.
7. Monthly marketing budget range (UGX) — approximate band: under 500k, 500k–2M, 2M–10M, 10M+. If a different currency applies, note it.

Step 1 — Run the Canvas Diagnostic

Ask the client the following nine questions. Record yes/no answers.

Diagnosis logic — count total yes answers:

State the diagnosed step clearly at the top of the canvas output. Be honest: most East African SMEs will land at Step 1 or Step 2. Do not inflate the diagnosis.

Step 2 — Complete the AI Marketing Canvas

The canvas has five steps (rows) and four customer moments (columns), producing 20 cells. Populate every cell for the client's current step and next step in full. Summarise the remaining steps in one sentence each.

The Five Steps

Step 1 — Foundation AI is not yet deployed. The focus is data infrastructure and organisational readiness.

Step 2 — Experimentation Small, low-risk AI experiments begin. Content tools, basic scheduling automation, simple chatbots.

Step 3 — Expansion Successful experiments are scaled. AI is integrated into three or more marketing functions. An AI use policy is in place.

Step 4 — Transformation AI is core to the marketing operating model. Personalisation at scale. AI informs strategy and budget allocation.

Step 5 — Reinvention AI enables new business models and entirely new customer value propositions.

The Four Customer Moments (Columns)

• Acquisition — attracting new customers: awareness, consideration, trial.
• Retention — keeping customers engaged: satisfaction, loyalty, repeat purchase.
• Growth — increasing customer value: upsell, cross-sell, referral.
• Advocacy — turning customers into brand promoters: UGC, referral, word-of-mouth.

Canvas Cell Content

For each cell at the client's current and next step, include:

• AI capability — what AI tool or technique is deployed here.
• Data required — what data the client needs to make this work.
• Expected result — what measurable outcome this produces.

Reference Cell Content by Step and Moment

Use the following as the basis for populating cells, adapted to the client's context.

Step 1 — Foundation

Step 2 — Experimentation

Step 3 — Expansion

Step 4 — Transformation

Step 5 — Reinvention

Step 3 — Produce the 12-Month Roadmap

Structure the roadmap by quarter. Every action must include a named tool or channel, a named metric, and a Q assignment.

Standard roadmap template — adapt to client's diagnosed step and context:

Q1 — Diagnose and Establish

• Confirm current step based on diagnostic results.
• Complete a data audit: identify where customer data lives, who owns it, and what is missing.
• Set up or clean the customer contact list (CRM, spreadsheet minimum standard).
• Launch 1–2 low-risk AI experiments appropriate to current step (e.g., AI caption writing in ChatGPT, scheduling via FeedHive or Buffer).
• Metric: baseline content output volume, time spent on content creation per week.

Q2 — Measure and Scale One Experiment

• Review Q1 experiment results against baseline.
• Select the single most successful experiment and scale it (increase frequency, apply to more channels, or expand to a second content type).
• Begin mapping the customer journey for the retention moment.
• Metric: time saving from AI tools, engagement rate change, WhatsApp open or reply rate.

Q3 — Integrate and Expand

• Integrate AI into one additional marketing function beyond content creation.
• For EA context: consider WhatsApp automation for retention or sentiment monitoring for advocacy.
• Draft and publish an internal AI use policy (see playbook-ai-content-workflow for guidance).
• Metric: functions using AI (target: 3+), policy in place (yes/no).

Q4 — Review Canvas Progress and Set Year 2 Targets

• Re-run the nine-question diagnostic to check step progression.
• Update the canvas: complete the next step's cells for any moment where Q1–Q3 work is confirmed.
• Set SMART objectives for Year 2 based on confirmed capabilities.
• Metric: step movement (did the client advance one step?), Year 2 AI investment recommendation in UGX.

Step 4 — Write the Plain-Language Summary

After the canvas and roadmap, produce a section titled "What This Means for Your Business".

This section must:

• State the diagnosed step in plain language ("You are at Step 2 — Experimentation").
• Explain what that means in one paragraph without jargon.
• Name the single highest-impact action the client can take in the next 30 days.
• Be honest about the gap between current state and transformation — do not promise shortcuts.
• Be written as if speaking directly to a business owner, not a marketing professional.

Step 5 — Monetisation

At this stage, AI capabilities become a source of competitive advantage and new revenue:

• AI-powered products or services sold to customers (e.g. a personalisation engine licensed to partners)
• Proprietary audience data monetised through partnerships
• AI-driven efficiency gains reinvested into market expansion
• Brand reputation as an AI-first organisation attracts premium clients and talent

Consultancy note: Most EA clients will not reach Step 5 within a 12-month engagement. Frame it as a 3–5 year horizon goal and use it to demonstrate the long-term value of starting the Canvas journey now.

East Africa Context Notes

Apply these adaptations throughout the canvas and roadmap:

• Data scarcity — most EA SMEs have no CRM; customer data lives in WhatsApp groups, spreadsheets, or paper records. Step 1 must address this before any AI deployment.
• WhatsApp first — WhatsApp is the primary channel for retention and advocacy in Uganda and across East Africa. Prioritise WhatsApp automation at Step 2–3 over email sequences.
• Mobile Money — MTN Mobile Money and Airtel Money are transaction platforms; personalised promotions tied to Mobile Money behaviour are a Step 4 opportunity.
• Step 2 tools for EA context — ChatGPT or Claude for captions and blog briefs; FeedHive or Buffer for scheduling; Canva Magic Write for short-form copy; Google Alerts for brand monitoring.
• Step 3 tools for EA context — Africa's Talking for WhatsApp and SMS automation; Hootsuite Insights or Brandwatch (if budget allows) for sentiment monitoring.
• Most EA SMEs are at Step 1–2 — calibrate ambition accordingly. A Step 2 roadmap executed well is more valuable than a Step 4 roadmap that cannot be implemented.

Agile Sprint Approach (Venkatesan and Lecinski, 2026)

AI marketing initiatives fail when treated as annual strategic plans. Recommend monthly sprint cycles:

1. Sprint planning (Day 1): Select one AI use case to test this month
2. Pilot execution (Days 2–20): Run the experiment with a defined audience segment
3. Measurement (Days 21–25): Compare AI-assisted results vs human-led baseline
4. Review (Days 26–28): Replicate, iterate, or abandon based on results
5. Next sprint (Day 30): Select next use case based on learnings

KPI for each sprint: measure lift vs human-led control. A 10% improvement justifies scaling.

AI-to-AI Marketing Readiness (Venkatesan and Lecinski, 2026)

As consumers increasingly use AI agents (ChatGPT, Perplexity, Google Gemini) to research, compare, and purchase, brands must be readable by machines as well as humans. Assess:

• Are product pages structured with clear, machine-parseable pricing and features?
• Are brand values explicitly stated in factual, accessible language?
• Is content well-sourced and factually accurate (LLMs avoid citing inaccurate sources)?
• Does the website use structured data markup (Schema.org)?

This is a 2–5 year horizon for most EA markets but should inform content architecture decisions now. Brands that are not AI-readable risk becoming invisible as AI-native search and AI shopping agents become mainstream.

Quality Criteria

Output meets standard when it:

• Diagnoses the client's step based on evidence from the nine questions, not aspiration or optimism — step inflation is a failure mode.
• Addresses all four customer moments for both the current step and the next step in full, with named AI capabilities, required data, and expected results.
• Produces a roadmap that is concrete: every action names a tool, a channel, and a metric.
• Reflects East African context throughout — WhatsApp, Mobile Money, and data scarcity are noted where they affect the recommended approach.
• Assigns every roadmap action to a specific quarter (Q1, Q2, Q3, or Q4).
• Includes a plain-language "What This Means for Your Business" summary written for a business owner, not a marketing specialist.
• Is honest about step progression — a realistic Step 1–2 plan is better than an inflated Step 4 plan the client cannot execute.
• Cites Venkatesan and Lecinski (2026) on first use of the framework.

References

• Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd ed. Stanford Business Books.
• Chaffey, D. (2024) Digital Marketing: Strategy, Implementation and Practice. Pearson.
• Bodnar, K. and Cohen, J. (2012) The B2B Social Media Book. Wiley.

Related skills:

• ai-readiness-diagnostic — the full 41-item AI readiness diagnostic; run this before or alongside the canvas assessment for a more detailed organisational audit.
• playbook-ai-content-workflow — execution playbook for AI-assisted content production.
• playbook-ai-automation-workflow — automation and tool integration guidance.
• 05-social-media-strategy — full social media strategy; the canvas roadmap feeds into this.