✳ CONFIDENCE / CUSTOMER PROOF10TURTLE / SYSTEM 05 OF 06
05 / CONFIDENCE BOOSTER · SMART REVIEWS

Let the proof
find the shopper.

Bring useful customer proof to the shopper instead of making them search for it.

EXPLORE SYSTEM ↘
05
reviews solution illustration
05 / 06BUILT TO REMOVE FRICTION
Customer proofRelevanceTrustSCROLL TO DISCOVER ↓
[01]✳ THE IDEA10T / COMMERCE SYSTEMS

Real experiences. Right where they matter.

Designed for an existing store, grounded in how shoppers actually think and behave.

05↗
Customer proofRelevanceTrust

When a shopper lands on a product page, our system doesn’t leave hundreds of reviews hidden below the product. After a suitable time interval, it automatically pops up a relevant review.

As the shopper continues browsing, another useful review can appear, showing different experiences, use cases or product benefits without requiring the customer to search through reviews manually.

Real customer experience stays a Customer Review. AI interpretation stays an AI Product Insight.

[02]✳ THE EVIDENCE10T / COMMERCE SYSTEMS

Trust needs evidence, not claims.

The studies and established principles informing how this experience is designed.

EVI-
DENCE↗

Research translated into practical interfaces.

Meta-analysis: online reviews
RESEARCH PAPER

How Online Reviews Affect Purchase Intention: A Meta-Analysis Across Contextual and Cultural Factors

Keda Qiu & Liyi Zhang · Data and Information Management, 2024 · Principle: Online Review Influence

156studies
214effect sizes
69,006observations
r = 0.563review valence: strongest combined effect

The researchers found significant relationships between online-review factors and purchase intention.

HOW WE APPLY ITReviews shouldn’t be passive content sitting at the bottom of the page. We bring useful review information directly into the shopper’s product experience while the purchase is being considered.
Impact 9/10
Review structure and helpfulness
RESEARCH PAPER

The Role of Review Structure in Perceived Helpfulness

Yingyue Luna Luan & Yeun Joon Kim · University of Queensland & University of Cambridge · Scientific Reports, 2026 · Principle: Review Helpfulness

195,675Amazon reviews analyzed

Perceived helpfulness depends not only on whether a review is positive or negative, but also on how its information is structured. Different review structures worked better depending on the product’s overall rating.

HOW WE APPLY ITWe don’t simply rotate random five-star reviews. The system can prioritize reviews that contain clear, useful information about different product concerns and use cases.
Impact 9/10
Undisclosed ChatGPT usage in reviews
RESEARCH PAPER

Consumer Reactions to Perceived Undisclosed ChatGPT Usage in an Online Review Context

Clinton Amos & Lixuan Zhang · Telematics and Informatics, 2024 · Principle: Authenticity & Transparency

Across three studies using TripAdvisor and Yelp review settings, reviews perceived as ChatGPT-generated were rated less useful, less trustworthy and less authentic than human-generated reviews. Perceived authenticity helped explain those differences.

HOW WE APPLY ITAI can analyze product images, descriptions and specifications and generate useful supporting information, but we do not present that content as if a customer wrote it. That distinction protects the trust that makes reviews valuable in the first place.
Impact 9/10
[03]✳ LIVE EXPERIENCE10T / COMMERCE SYSTEMS

Watch confidence build.

Interact with the walkthrough to explore what the experience does at every step.

Swipe for the next step

Swipe the demo or use the arrows for the next step. Click a step above to jump to it.

✳ WORKING EXPERIENCEINTERACTIVE
WALKTHROUGH

The product is designed to work inside the existing ecommerce experience, not as a separate destination.

EXPLORE THE METHOD ↘
[04]✳ BEHIND THE SYSTEM10T / COMMERCE SYSTEMS

Surface what matters.

Each interaction follows an intentional sequence—not an arbitrary collection of features.

05

CONFIDENCE / CUSTOMER PROOF

AT A GLANCE / THE FLOW
Shopper lands on the product→Relevant customer review appears automatically→Different useful reviews rotate over time→AI selects information relevant to different buying concerns→AI-generated observations are clearly identified→Useful proof, without searching hundreds of reviews
✳ WHAT IT ALL ADDS UP TO

Put authentic customer evidence to work.

A smart review layer that brings relevant customer experiences into the product page at the right moments, with clearly separated AI Product Insights that make product information easier to understand.