Social proof · Australia

Popularity claims

Popularity claims is a working label for this design mechanism: Aggregate popularity or approval is presented to steer a choice where the metric, population, period or basis is unclear or unsupported. This is editorial implementation guidance for Australian journeys, not a finding of unlawfulness. From 1 July 2027, a similar interface is relevant to ACL section 28B only if the complete consumer-connection, manipulation or unreasonable-distortion and actual-or-likely-detriment test is met. Current ACL rules require a separate assessment.

Editorial implementation guidance
Also known as
  • best seller claim
  • most popular
  • aggregate social proof
  • most popular plan
  • number of customers
  • star rating
  • trending badge
Journey stages

Definition

What is this pattern?

Aggregate popularity or approval is presented to steer a choice where the metric, population, period or basis is unclear or unsupported. This is a design and research taxonomy for learning and evidence review, not a statutory offence label or an automatic finding that an interface is unlawful.

How it works

Aggregate popularity or approval is presented to steer a choice where the metric, population, period or basis is unclear or unsupported. A ranking or badge implies collective preference without a defined population, period and metric, or substitutes a commercial objective for actual popularity.

Warning signs

  • The claim asserts relative or aggregate popularity.
  • It is used near a choice or recommendation.
  • The relevant metric basis requires provenance verification before alleging deception.

Potential harms

  • The badge may steer users using an unsupported impression of collective preference.
  • Shoppers may interpret commercial ranking as genuine purchase popularity.

Learn by comparison

What does this look like?

These fictional examples make the design mechanism easier to recognise. They do not depict a real company and do not establish that an individual interface is unlawful.

Illustrative example 1 · “Most popular” has no defined metric

A fictional service labels its highest-margin plan “Most popular” without recording sales, selection period or the population being measured.

Potential consumer harm: The badge may steer users using an unsupported impression of collective preference.

Illustrative example 2 · Bestseller badge follows margin rather than sales

A fictional marketplace assigns “Bestseller” to whichever item yields the highest commission, regardless of units sold.

Potential consumer harm: Shoppers may interpret commercial ranking as genuine purchase popularity.

What is a fairer alternative?

Use popularity claims only with a defined population, period and metric; document the calculation beside the claim or replace it with factual product information.

Context matters

Context and boundary cases

  • The claim asserts relative or aggregate popularity.
  • It is used near a choice or recommendation.
  • The relevant metric basis requires provenance verification before alleging deception.
  • Boundary to test: Individual testimonial
  • Boundary to test: recent-activity message
  • Boundary to test: transparent internally computed recommendation not presented as social behaviour

When a similar design can serve a legitimate purpose

  • Individual testimonial
  • recent-activity message
  • transparent internally computed recommendation not presented as social behaviour

Operational review

What teams should review

Teams
  • Product
  • Design
  • Engineering
  • Legal
  • Compliance
  1. Which source record substantiates “Choose Pro”, including its population, period, metric and any commercial relationship?
  2. Place the compared prices, billing periods and material terms on one evidence sheet; where does it support “The claim asserts relative or aggregate popularity”?
  3. Can the claim be reproduced from a defined population and period, or does the evidence instead fit “Individual testimonial”?
  4. Which source record substantiates “Top customer choice”, including its population, period, metric and any commercial relationship?
  5. Record the claim, timestamp, data source and post-claim state; which evidence supports “It is used near a choice or recommendation”?
  6. Can the claim be reproduced from a defined population and period, or does the evidence instead fit “recent-activity message”?

Evidence to retain

  • Annotated pricing screenshots at each responsive breakpoint
  • The complete state sequence before, during and after the consumer decision
  • Design-system component, content, default and configuration records for the reviewed release
  • Operational records substantiating price, availability, timing and eligibility claims
  • Usability, accessibility, reversal, complaint and support evidence relevant to consumer impact
  • A dated product and legal review record identifying evidence, uncertainties and release decisions

Legal map and implementation tools

Evidence base

Sources

  1. Dark commercial patternsOrganisation for Economic Co-operation and Development · Secondary · checked 2026-09-14 · OECD Digital Economy Papers No. 336
  2. Competition and Consumer Amendment (Unfair Trading Practices) Act 2026Federal Register of Legislation · Primary · checked 2026-09-14 · C2026A00064
  3. Competition and Consumer Act 2010, including Schedule 2: Australian Consumer LawFederal Register of Legislation · Primary · checked 2026-09-14 · C2004A00109
  4. Unfair trading tricks and traps to be bannedTreasury Ministers · Primary · checked 2026-09-14
  5. Inquiry into the Competition and Consumer Amendment (Unfair Trading Practices) Bill 2026Senate Economics Legislation Committee · Primary · checked 2026-08-09