Insights Association · 2025 Edition

Code of Standards and Ethics for Market Research & Data Analytics

A comprehensive training program covering ethical practice, data protection, AI considerations, and your professional responsibilities under the IA Code.

📚 4 Modules 🎥 2 Videos ⏱ ~35–45 min ✓ Certificate included

About this course

What you'll learn

This course walks through all 11 sections of the IA Code, combining video content, guided reading, real-world scenario practice, and assessed knowledge checks.

Module 01

Foundations

The purpose of the Code, fundamental principles, and the key definitions you need to apply it correctly.

Module 02

Data Collection

Primary and passive data collection, consent requirements, and your duty of care to research subjects.

Module 03

AI, Data Use & Privacy

Artificial intelligence obligations, second/third-party data rules, and data protection requirements.

Module 04

Responsibilities & Enforcement

Obligations to clients and the public, professional responsibilities, and how the Code is enforced.

ℹ

Adherence to this Code is required by all IA members. By completing this training, you are affirming your understanding and commitment to these standards.

Module 1 · Video

Part 1: Foundations of the Code

This video introduces the Code's purpose, scope, and the fundamental principles that guide every section.

Part 1 of 2 · ~2 minutes

Key takeaways from this video

The Code establishes self-regulation and ensures public confidence in how research data is collected and used.

When the Code conflicts with applicable law, the more restrictive standard governs.

"Must" = required. "Should" = recommended. This distinction matters for compliance.

The Code is a living document—reviewed annually by the Standards Committee and Board.

Module 1 · Reading

Core Principles & Key Definitions

The Code rests on four fundamental principles and a precise glossary.

The four fundamental principles

1. Respect research subjects and their rights as specified by law, regulation, and this Code.

2. Be transparent about personal data collection; only collect with consent and ensure security in transit and at rest.

3. Act with high standards of integrity, professionalism, and transparency.

4. Comply with all applicable laws, regulations, privacy policies, and terms and conditions.

Key definitions

Research Subject — a human from whom data are collected or used for research purposes.
Consent — voluntary, informed agreement for participation and/or data collection.
Personal Data — information that can identify an individual, alone or combined with other data.
Non-Research Activity — direct action to persuade an individual using data collected in research.

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The distinction between research and non-research activity is critical. Using data collected in research to directly market to a participant without consent violates the Code.

Module 2 · Video

Part 2: Data Collection in Practice

Primary and passive data collection, consent obligations, and protections for vulnerable individuals.

Part 2 of 2 · ~2 minutes

Key takeaways from this video

Participation must always be voluntary. Researchers must respect the right to refuse or terminate participation.

AI avatars or chatbots that could be perceived as human must be disclosed at the beginning of the research.

For passive data collection, obtain informed consent wherever feasible.

Children and vulnerable individuals require verifiable consent from a parent or legal guardian.

Module 2 · Reading

Duty of Care, Consent & Vulnerable Populations

Sections 1–3 and 7 address your obligations during data collection.

Researchers must balance the interests of research subjects, research integrity, and business objectives; make reasonable efforts to ensure subjects are not harmed; be honest and transparent; and always distinguish between research and non-research activities.

Obtain consent for participation and data collection. If re-contact is planned, notify subjects at collection time (quality control re-contact is exempt). Obtain fresh consent before materially different data use.

Obtain informed consent wherever feasible. On shared devices, delete data not linked to the consenting individual. Apply stricter security for sensitive data.

Follow laws governing consent for children/vulnerable individuals. Obtain verifiable guardian consent when required. Never pressure or mislead vulnerable participants.

Module 2 · Scenario Practice

Apply the Code: real situations

Read each scenario and choose the correct action under the IA Code. These are not graded — they're practice.

⚡ Scenario A

A client asks you to add survey participants' contact details to a targeted email marketing list without re-obtaining consent.

What should you do?

This violates Section 1.5 and the definition of Non-Research Activity. Using research data for direct marketing without consent is prohibited regardless of the client relationship.

⚡ Scenario B

You're fielding a survey using an AI chatbot that closely mimics human conversation, with no disclosure to participants.

What does the Code require?

Section 2.4 requires disclosure of AI/chatbot use at the start of research — not after the fact.

Module 3 · Reading

AI, Data Use & Privacy Protection

Sections 4–6 cover AI governance, second/third-party data, and data protection.

Section 4 — Artificial Intelligence

Personal data must not be used in AI training without informed consent.
AI use, purpose, technique, model type, accuracy, and data source must be disclosed.
No AI system may operate without human judgment embedded in its lifecycle.

Section 5 — Second & Third-Party Data

Confirm data wasn't collected unlawfully. Ensure use is compatible with original consent. Be transparent about origins and IP ownership.

Section 6 — Data Protection & Privacy

Maintain a clear privacy policy. Obtain consent before third-party transfers. Limit data to what's necessary. Report breaches as required by law.

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AI presents 'incremental and evolving considerations' — expect this section to be updated as technology develops.

Module 3 · Scenario Practice

AI & data ethics in practice

Read each scenario and choose the correct action under the IA Code. These are not graded — they're practice.

⚡ Scenario C

Your team blends real survey responses with AI-generated synthetic data in a report, without labeling which is which.

What does the Code require?

Section 4.2 explicitly requires AI-generated data to be clearly distinguished from human-participant data in all reporting.

Module 4 · Reading

Responsibilities & Enforcement

Your obligations to clients, the public, and the profession — and how the Code is enforced.

Be honest about qualifications and conflicts of interest. Identify subcontractors on request. Use client data only for its intended purpose. Cite secondary data sources.

Obtain client approval before public release. Ensure findings aren't misleading. Provide technical detail for independent assessment. Correct errors promptly.

Comply with the Code and all applicable laws. Act with integrity. Do nothing that damages public confidence in research. Communicate with respect.

The IA Standards Committee handles all complaints. Contact: enforcement@insightsassociation.org. Sanctions range from a private Warning to public Expulsion (minimum 2 years).