Product listings
AuraScore 85/100

Conversational AI Voice Checkout and Spec Advisor Script

Develop a structured dialogue script for an AI voice sales advisor handling complex formulation and dosage product queries.

Use this template to design voice-commerce assistant interactions for products with complex formulations, concentrations, or dosing rules. It builds decision logic, safety disclosures, and checkout conversion dialogue flows.

Template

Role: Conversational Commerce Architect and Regulatory Compliance Specialist

Context

  • Active Formulation: {{formulation_name}}
  • Bioactive / Chemical Specs: {{active_ingredient_data}}
  • Customer Input Profile: {{user_profile_parameters}}
  • Legal & Regulatory Constraints: {{regulatory_disclaimers}}
  • Unit Economics & Supply Sizes: {{unit_cost_structure}}
  • Application & Dosing Ratios: {{application_frequency_math}}

Task

Design a turnkey conversational dialogue script for an automated voice shopping assistant that evaluates user parameters, calculates exact usage recommendations, and guides the customer through listing checkout.

Method

  1. Map {{user_profile_parameters}} against {{active_ingredient_data}} to define eligibility and concentration matching rules.
  2. Translate {{application_frequency_math}} into simple conversational dosage or application cadence calculations.
  3. Draft the intake dialogue path where the assistant collects buyer constraints and goals.
  4. Script the analysis and recommendation turn, stating concentration fit and rationale clearly.
  5. Embed required safety notices from {{regulatory_disclaimers}} naturally without breaking conversational flow.
  6. Formulate pricing options and cost-per-day math derived from {{unit_cost_structure}}.
  7. Detail edge-case fallback branches for contraindicated user inputs or out-of-scope requests.
  8. Script smooth transition from product advisory directly into voice-authenticated cart checkout.

Constraints

  • Dialogue turns MUST follow strict conversational turn-taking syntax (User Prompt vs. Assistant Response).
  • Assistant responses MUST NOT exceed 45 words per individual turn to ensure audio intelligibility.
  • MUST include mandatory wording from {{regulatory_disclaimers}} word-for-word in the appropriate branch.
  • MUST NOT provide medical or engineering guarantees outside substantiated specification bounds.

Output format

  • Section 1: Interaction Architecture (State flow and logic branching map).
  • Section 2: Conversational Script Tracks (Primary Track, Sizing Adjustment Track, Fallback/Contraindication Track).
  • Section 3: Value Calculation Cheat-Sheet (Voice-delivered unit economics breakdown).

Self-review

  • Does the voice assistant calculate usage cadence accurately using {{application_frequency_math}}?
  • Are turn lengths optimized for low cognitive load and clear voice synthesis?
  • Are all legal disclaimers seamlessly integrated prior to cart checkout confirmation?
AuraScore breakdown
85/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

ecommerce-retail
ecom-listings
complex-reasoning-analysis-math
voice-commerce
conversational-ai
ecommerce-listing