Prototype an interactive acquisition funnel
Use a coding assistant to turn a campaign idea into a quiz or interactive landing-page prototype.
How this works
Use a coding assistant to turn a campaign idea into a quiz or interactive landing-page prototype. An interactive funnel prototype should prove that the proposed visitor journey is understandable and logically complete. A quiz that produces an attractive result but mishandles answers, restarts, or registration is not ready for a campaign test.
Define the input-to-result rules, build a bounded prototype, and test every meaningful path. Use deterministic logic for scoring or routing unless the brief explicitly requires AI-generated responses. Keep illustrative outputs clearly labeled and preserve the distinction between prototype and production integration.
Before you start
Visitor objective
Define the useful result the interaction gives the visitor.
Logic specification
Provide questions, answer options, and result rules.
Prototype environment
Use the existing project or an approved local workspace.
Prepare the inputs
- journey_brief
- Required
States and desired action
Include start, progress, result, and optional registration.
- question_set
- Required
Questions and options
Avoid ambiguous or unsupported assessment claims.
- result_rules
- Required
Deterministic mapping
Every valid path must resolve.
- design_guidance
- Required
Brand and layout
Specify mobile constraints.
- integration_scope
- Required
Allowed endpoints
Use mocks when real writes are not authorized.
Implementation, step by step
Map the interaction
- List visitor states and transitions, including back and restart behavior.
- Define what constitutes completion and what data is needed.
Checkpoint: A complete journey map.
Specify result logic
- Translate answers into explicit routing or scoring rules.
- Create expected outputs for representative combinations before coding.
Checkpoint: A testable logic table.
Build the prototype
- Use available coding tools to implement the bounded experience.
- Keep unconfigured integrations mocked and visibly distinguish sample results.
Checkpoint: A runnable local prototype.
Validate all paths
- Exercise normal, boundary, blank, and contradictory inputs.
- Check back navigation and refresh do not produce inconsistent results.
Checkpoint: A path-validation record.
Review mobile usability
- Inspect touch targets, text wrapping, progress clarity, and keyboard operation.
- Ensure the result is useful before asking for unnecessary data.
Checkpoint: A corrected interaction design.
Prepare campaign-test handoff
- List remaining production dependencies and the exact version tested.
- Define the next experiment without claiming deployment or lead delivery that was not verified.
Checkpoint: A reviewed prototype package.
Decisions along the way
A result path is undefined
Hold completion and repair the rule table.
The brief asks for a diagnostic score without a validated rubric
Use an illustrative recommendation or clarify the limitation.
Lead integration is absent
Provide a mock or file-based handoff and label it.
What you will produce
interactive-funnel-prototype
Project filesSupports concrete stakeholder review.
Include: states · questions · rules · result_views · error_states
interaction-test-cases.csv
CSVChecks actual branching behavior.
Include: case_id · answers · expected_result · observed_result · status
Check the result
- Test every defined result class and transition.
- Compare outputs with the independent rule table.
- Check mobile overflow and keyboard accessibility.
- Verify no mock submission is described as a real lead.
When something goes wrong
Generated code changes the scoring rule
Restore the approved mapping and rerun tests.
State persists incorrectly after restart
Reset the relevant data and retest the complete journey.
Prototype sends data to an unintended endpoint
Remove the connection and use the approved mock path.
A worked example
SYNTHETIC EXAMPLE · NOT A REPORTED BUSINESS RESULT
Request
Prototype a quiz suggesting a reporting workflow.
Inputs
Synthetic example. Synthetic rules route weekly manual spreadsheets to option A and occasional ad hoc questions to option B.
Expected result
Synthetic expected result. The same answers always produce the same defined result. A missing frequency answer shows a prompt to complete it rather than guessing option A.
Run a small pilot
Start small
One short interaction with a few realistic users and complete path coverage.
Record the baseline
Record task completion and confusion in the current static funnel.
Agree success criteria
Agree usability and logic-correctness criteria before campaign deployment.
Stop or revise
Stop the test if results are misleading or data leaves the approved environment.
Keep the scope clear
- Prototype creation does not authorize deployment or traffic spend.
- Do not infer personality, ability, or sensitive traits from marketing answers.
Check before using
Check answer logic, tracking, mobile behavior, and the accuracy of recommendations.
Business activities
- Handle inbound enquiries
- Run advertising and acquisition tests
FROM A RECIPE TO YOUR WORKFLOW
Bring the company context together.
This workflow needs reliable inputs before it needs a better prompt. Moat8 Vault brings working information into a readable archive for the AI tools you use.
For this recipe: Campaign objective · Questions and result logic · Product messages
Start with one recurring task, agree which sources to use, and review the first result with your team.
Discuss this workflow