---
title: "Glossary: Key Company Terms & Metrics"
description: Learn the definitions of essential DataEQ terms like Net Sentiment, RPCS, EQEngine, and Benchmark Sentiment. This glossary helps users understand the metrics and methodologies that power accurate, actionable insights across the platform.
---

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# Glossary: Key Company Terms & Metrics

## Understand the core terms and metrics that power DataEQ’s solutions. This glossary defines essential concepts to help you get the most value from our platforms.

### **Net Sentiment**

**Net Sentiment** is a key metric used to evaluate brand perception by calculating the difference between positive and negative sentiment. This percentage-based score offers a clear snapshot of overall customer experience and reputation.

Subcategories of Net Sentiment include:

- **Public Net Sentiment** Measures sentiment in publicly available social media conversations, excluding direct messages.
- **Private Net Sentiment** Captures sentiment from direct messages (DMs) sent to a brand’s social media accounts. This is useful for assessing the quality of private customer interactions.
- **Operational Net Sentiment** Reflects sentiment from individuals engaged in the customer journey, including pre-purchase, active customers, and post-service feedback.
- **Reputational Net Sentiment** Focuses on mentions not directly related to the customer journey—such as sponsorships, campaigns, or general public commentary.
- **Benchmark Sentiment** Provides a normalised sentiment score for consistent cross-brand comparisons by using standardised search terms and excluding campaign-specific content.

---

### **RPCS (Risk, Purchase, Cancel, Service)**

**RPCS** represents four high-priority mention categories used across our solutions to help triage customer feedback and business risks:

- **Risk**: Mentions that highlight reputational or operational threats.
- **Purchase**: Opportunities for customer acquisition or product interest.
- **Cancel**: Indicators of potential churn or negative customer sentiment.
- **Service**: Mentions requesting help, support, or service resolution.

These classifications support real-time decision-making in Engage by surfacing the most critical interactions for customer care teams.

---

### **EQEngine**

**EQEngine** is DataEQ’s proprietary technology that powers the classification and verification of social media and digital mentions. By combining machine learning with advanced natural language processing, EQEngine ensures:

- High-accuracy sentiment detection
- Advanced topic and theme classification
- Relevance filtering to remove noise and off-topic content

EQEngine enables clients to access trusted, accurate data across languages and platforms, even in complex or nuanced conversations—delivering over 95% accuracy on critical metrics.

---

### **Indices**

**Indices** are industry reports generated by DataEQ to benchmark brand performance. These are compiled annually using standardised methodologies and include:

- Sentiment and volume comparisons across brands and sectors
- Data-driven insights to guide strategy and inform reputation management
- Competitive positioning through apples-to-apples analysis

Custom indices are available to address specific industries or regulatory frameworks.

#### **Troubleshooting Questions**

- **Why doesn’t my Net Sentiment match internal survey results?** Net Sentiment reflects real-time public and private online feedback, which may differ from survey-based internal scores.
- **Can RPCS tagging be customised for our workflow?** Yes, segment lists and tagging logic can be tailored to your industry and support priorities.
- **What makes EQEngine different from other sentiment tools?** EQEngine blends machine intelligence with verified processes to deliver accuracy that surpasses algorithm-only tools.
- **How can I use Indices to support my reporting?** Indices offer market-level context for brand performance. Speak to your Account Manager about relevant reports for your sector.
- **Can EQEngine classify mentions in multiple languages?** Yes, EQEngine supports multilingual processing across several key global languages.

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