R-Analyst

What is it?

R-Analyst is an intelligent system that transforms large volumes of customer reviews into clear and actionable insights.

It reveals the real picture of customer sentiment, highlights key topics, and shows what exactly should be improved in product, service, and communication.

This is not about star ratings — it’s about meaning, patterns, and priorities for change.

With R-Analyst, teams stop drowning in text and start managing customer experience based on data.

What can R-Analyst do?

• Sentiment analysis: positive, negative, neutral, mixed
• Aspect extraction: quality, delivery, price, support, service, packaging, etc
• Issue detection: highlights dissatisfaction reasons and growth opportunities
• Analytics generation: clear charts and tables across slices (language, region, issues, aspects, categories)
• AI-chat: answers questions about analytics, gives recommendations and improvement steps

How does it function?

Understanding: NLP models determine sentiment (positive/negative/neutral/mixed) and extract key aspects (quality, delivery, price, support, packaging, etc.).

Topic modeling: groups similar themes to clearly see 'what customers are really talking about.'

Issue detection: identifies recurring problems such as mismatched descriptions, delays, defects, and poor support.

Dynamics: tracks how sentiment changes over weeks or months and what triggers spikes (releases, promotions, seasonality).

Segmentation: filters by language, region, channel, category, SKU, and aspects to quickly find weak points.

Visualization: generates clear charts and tables for fast decisions and presentations.

Dialogue: the AI-chat answers questions about analytics, formulates conclusions, and suggests improvement steps.

Benefits of automation

• High speed in processing large datasets
• Reduced subjective bias in feedback evaluation
• Ready-made visualizations for team discussions and decisions
• Unified view across regions and languages without manual translation

Which problems does it solve?

• Too many reviews for manual analysis — important signals are lost
• Valuable insights are hidden in text and remain unnoticed
• No clear picture of how sentiment changes over time or what drives it
• Hard to decide what to fix first: product, delivery, support, or price
• Reports take too long to prepare, delaying decisions

Why does it matter for you?

• Time-saving: seconds instead of hours of manual analytics
• Objectivity: fewer subjective interpretations, more fact-based insights
• Convenience: ready-made visualizations and structured data for quick decisions
• Multilingual support: reviews analyzed across major languages with auto-translation
• Action focus: the system helps identify what will deliver the biggest impact

Who is Q-Assistant for?

• Product managers
  Validate hypotheses with data and plan improvements based on real customer pain points
• Marketers
  Understand which strengths to emphasize and which objections to address
• Support teams
  Identify recurring problems faster and reduce workload
• Executives
  See how customer experience impacts business metrics and prioritize initiatives