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Since 1999/07/09

평범한 선생님은 말을 하고, 좋은 선생님은 설명을 하며, 뛰어난 선생님은 몸소 보여주고, 위대한 선생님은 영감을 준다
In today’s e-commerce environment, customer experience is one of the strongest competitive advantages. It is no longer enough to rely on product quality and fast delivery — what matters is understanding why customers are satisfied, what they appreciate, and what repeatedly causes frustration.

This is exactly why ReviewBrain.online was created — an AI-based review analysis platform that processes feedback from sources such as Heureka, Google Reviews, Pricemania and internal surveys. Instead of manually reading hundreds of comments, ReviewBrain provides a clear, data-driven overview in a matter of minutes.

Why star ratings are not enough
Most e-commerce platforms show only basic star ratings and short comments. However, these numbers rarely reveal deeper insights. Behind a 4.7 or 4.9 score there are drivers of satisfaction, common complaints, emotional reactions, and patterns that are crucial for marketing, product management and customer support.

When the number of reviews grows, manually reading and grouping them becomes nearly impossible. Many online stores only react when a negative issue snowballs — often too late. ReviewBrain solves this by automatically analyzing review text using AI and converting it into digestible dashboards, charts and insights that help e-shops improve immediately.

What ReviewBrain offers
1. Sentiment analysis over time
ReviewBrain monitors how customer sentiment shifts across weeks, months or seasons. You can immediately identify whether feedback becomes more negative after changes in logistics, product quality or customer communication.

2. Key themes, praises and recurring issues
Using large language models, ReviewBrain extracts the most recurring topics in reviews:

What customers praise — speed of delivery, product quality, packaging, friendly support.
What they criticize — damaged goods, unclear product information, delay in shipping.
Words and expressions customers use when describing your brand.
These insights help companies strengthen their advantages and quickly address issues that may affect conversions or decrease returning customers.

3. Best-performing and risky products
ReviewBrain identifies products that generate exceptionally positive feedback — as well as those that repeatedly appear in complaints or returns. This allows teams to:

promote high-performing products more effectively,
review or improve weaker items in the catalog,
optimize marketing budgets based on real experience.
4. Marketing-ready quotes and insights
Real customer quotes are powerful across all marketing channels. ReviewBrain helps you extract:

social proof for landing pages and banners,
USP claims based on real customer language,
email content powered by authentic feedback,
SEO-friendly text based on what shoppers truly care about.
Instead of guessing messages, you build campaigns based on the vocabulary and emotions of your audience.

Who is ReviewBrain for?
ReviewBrain brings value to a wide range of online stores:

Small e-shops gain clarity on what needs quick improvement.
Medium and large e-commerce projects get category- and product-level insights in seconds.
Marketing teams discover real phrases and arguments that convert.
Product managers better understand what influences satisfaction and retention.
BETA program — limited availability
ReviewBrain is currently being launched as part of a BETA program. This means:

limited onboarding capacity per month,
individual assessment for each applicant,
gradual scaling with close feedback from early partners.
Not every e-shop can be onboarded immediately — each request is evaluated based on review volume and connection options. Selected stores receive detailed guidance and a suitable BETA plan (Pilot, Start or Pro).

How to join
If you want to understand what truly drives customer satisfaction and use this data to improve your marketing, product strategy and customer experience, visit:

www.reviewbrain.online

There you will find more information about how ReviewBrain works, along with the form to request access to the BETA program.class=
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