VOCx vs Cipher: Which Should You Use?

VOCx and Cipher are complementary products that serve different purposes. This guide helps you understand when to use each product and how they work together.

Note on Terminology: Throughout this documentation, we use the terms "AI agent", "AI assistant", and "voice bot" interchangeably. They all refer to the same concept: autonomous AI systems that interact with users through conversation, whether text-based or voice-based.

Quick Comparison

Aspect	VOCx	Cipher
Primary Purpose	Customer feedback analysis	AI agent optimization
Data Sources	App stores, email, support tickets, surveys, social media	AI agent conversations
Key Output	Segments, buckets, classifications	Signals, patterns, evaluations
Main Users	Product managers, CX teams, support teams	AI/ML teams, support automation teams
Focus	Product improvements, feature prioritization	Agent performance, model optimization
Analysis Type	Feedback content and sentiment	Conversation quality and effectiveness

When to Use VOCx

Use VOCx when you need to:

• Analyze customer feedback from various sources (reviews, emails, tickets, surveys)

• Prioritize product improvements based on customer value and sentiment

• Track sentiment trends and customer satisfaction over time

• Identify feature requests and bugs from unstructured feedback

• Understand customer journey pain points

Who Uses VOCx:

• Product managers prioritizing features and improvements

• Customer experience teams tracking satisfaction and issues

• Support teams managing feedback volume

• Engineering teams focusing on high-impact bugs

When to Use Cipher

Use Cipher when you need to:

• Optimize AI agent performance and user experience

• Benchmark different models (GPT, Claude, Gemini) for your use case

• Analyze conversation quality and identify frustration points

• Improve support automation and reduce cost per ticket

• Measure agent effectiveness and resolution rates

Who Uses Cipher:

• AI/ML teams optimizing agent performance and model selection

• Product teams deploying in-product copilots

• Customer support teams automating with bots

• CX teams measuring agent effectiveness

How They Work Together

While VOCx and Cipher serve different purposes, they complement each other:

Complementary Insights

1. VOCx identifies what customers want and need from your product

2. Cipher ensures your AI agents deliver those needs effectively

Example Workflow

1. VOCx identifies that customers frequently ask about "refund policies" in feedback

2. Cipher analyzes how well your AI agent handles refund-related conversations

3. Together, they help you:

   • Understand the customer need (from VOCx)

   • Optimize the agent solution (from Cipher)

   • Measure the impact of improvements (both)

Feature Comparison

Data Sources

VOCx:

• Google Play Store reviews

• Apple App Store reviews

• Gmail, Outlook emails

• Zendesk, Intercom tickets

• Reddit discussions

• Surveys and manual uploads

Cipher:

• AI agent conversations

• Support bot interactions

• In-product copilot sessions

• Agentic workflow conversations

• Voice bot interactions

Analysis Capabilities

VOCx:

• Intent classification (bug report, feature request, etc.)

• Sentiment analysis

• Priority calculation

• Journey stage inference

• Product area mapping

• Business impact metrics

Cipher:

• User experience intelligence (UXI)

• Experience Quality Score (XQS)

• Model benchmarking

• Prompt optimization

• Signal extraction

• Operational metrics

Output Types

VOCx:

• Segments (individual feedback points)

• Buckets (grouped similar feedback)

• Classifications (intent, priority, sentiment)

• Analytics (volume, trends, business impact)

Cipher:

• Signals (observable facts)

• Patterns (interpreted insights)

• Evaluations (quality assessments)

• Benchmarks (model comparisons)

Decision Guide

Choose VOCx If:

• You need to analyze customer feedback from multiple sources

• You want to prioritize product improvements

• You need to track sentiment and trends

• You're managing feature requests and bugs

• Your focus is on product development

Choose Cipher If:

• You have AI agents (copilots, bots, workflows, voice bots)

• You need to optimize agent performance

• You want to benchmark models and prompts

• You're improving support automation

• Your focus is on AI/ML optimization

Use Both If:

• You have both customer feedback and AI agents

• You want complete visibility into customer experience

• You need to connect product needs with agent solutions

• You want to measure end-to-end customer experience

Next Steps

• VOCx Guide - Deep dive into Voice of Customer Analytics

• Cipher Guide - Deep dive into Conversation Intelligence

• Getting Started - Set up your first product