Understand the drivers of customer sentiment and make targeted improvements
We analyse every customer interaction in real time, detecting emotions like gratitude, praise, frustration, and confusion. With sentence-level precision, our platform uncovers insights to improve customer experience and agent performance.
- Quantify issues driving negative sentiment.
- Identify agent behaviour and tone-of-voice variations.
- Make sentiment insights central to the "Voice of the Customer."
- Use customer feedback to drive operational decisions.
Understand What’s Driving Customer Emotions
Recognise these roadblocks?
- Difficulty tracking agent adherence to protocol.
- Reactive customer support.
- Challenges flagging difficult or at-risk customer interactions.
- Hard to review average sentiment per agent.
- Agent blind spots.
- Unapproved brand tone or statements from agents.
- Lack of agent comparison to spot improvement areas.
- Can’t find the root cause of customer frustration.
- Struggling to improve CSAT.
- Struggling to track customer sentiment.
- Surveys not capturing the full picture.
- Missed grammatical errors or spelling mistakes by agents.
Granular emotion insights at your fingertips
Filter interactions by emotion
See only those customer interactions that contain frustration, praise, gratitude, or confusion, allowing you to focus on the most critical conversations.
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Analyse agent performance
Compare how different agents handle customer queries to assess soft skills and identify coaching opportunities.
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Track emotion over time
Monitor shifts in customer sentiment across teams, topics, or products to spot trends and address concerns before they escalate, feeding these insights back into the business.
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What our customers are saying about us
Book Your DemoNick Brazitis
Global Customer Care Manager
“The onboarding process was super easy, the team was very agreeable and made the process seamless. We are very impressed with EdgeTier’s responsiveness – we typically get a response to any question almost immediately.”
Vladimir Greavu
Director of Customer Service Berlin Brands Group
“If we didn’t have EdgeTier it would feel like going back to the stone age."
James Waghorn
Director of Customer Contact at CarTrawler
“EdgeTier has improved data visibility and has ultimately helped us understand our business better”
Deborah Guivisdalsky
COO, Codere
"We now have a highly detailed understanding of agent performance, not just on key agent metrics, but also on how customers react to our agents and the emotions our customers feel when talking to our team."
Marily Tsega
Head of Customer Operations. Novibet
“EdgeTier provides us with details and insights into agents' conversations, and this helps us identify areas for training and development. Before this, we relied on a manual review process, which was time-consuming and less effective in pinpointing specific training needs."
Afroditi Pina
Director of Customer Service. Novibet
“We have managed a saving or if you wish, a return on investment by applying EdgeTier in Novibet, saving something close to six full-time employees during the last six months from efficiencies.”
The only customer sentiment intelligence you’ll ever need
- AI-powered interaction analysis
- Omnichannel feedback capture
- Real-time sentiment analysis
- Standardised agent review evaluations
- Send feedback directly to agents
- Seamless integration
- Go live in 2 hours
- Real-time reporting
- Support in 140+ languages
Gather comprehensive customer insights
EdgeTier integrates seamlessly with major platforms like Salesforce, Zendesk, Intercom, LivePerson, and LiveAgent. Once connected, we scan and analyse data from all your support channels, helping you understand what’s really going on with your customers.
Greater strategic credibility
Easily filter conversations based on your key focuses, like phrasing and customer sentiment, so that you can flag frustrated and problematic interactions. Quickly zero in on which ones need a closer review.
Share strategic customer feedback across the business
Improve customer satisfaction and retention by identifying the key drivers of poor sentiment and taking action to fix the customer experience.
Key Features
AI-Anomaly Detection & Alerts
Comprehensive Conversation Analysis
Real-Time Data Integration
Targeted Agent Coaching
Smart Tagging
Multilingual Translation and Support
Customer Emotion Detection
Fast and Easy Setup
Secure Data Handling and Compliance
Integrates effortlessly with your preferred software.
Pull and push data with your existing software stack so your existing business processes still work, just better. EdgeTier is ready with integrations to all major players such as Salesforce, Live Person, Zendesk, Kustomer etc. as well as a simple API to connect to in-house system. Go live in less than 2 hours, with zero IT time required from your team.
View All IntegrationsGet your free demo
Give us 30 minutes and we’ll show you how to detect emerging issues, gain 100% visibility into customer attitudes, and boost agent performance with targeted coaching.
Frequently asked questions
FAQ's
Everything you need to know about EdgeTier’s dedication to Quality Assurance.
What is customer sentiment analysis, and how does it benefit my contact centre?
Customer sentiment analysis is the process of analysing customer messages and conversations to determine whether the sentiment is positive, negative, or neutral. It helps contact centres understand the emotions behind customer interactions—such as satisfaction or frustration—and enables teams to take proactive steps to improve customer experiences. On the EdgeTier platform, sentiment analysis is performed using advanced machine learning models trained specifically for customer service contexts, which provides actionable insights that can be used to enhance agent performance and improve customer satisfaction (CSAT) and Net Promoter Score (NPS).
How can sentiment analysis be applied to conversation transcripts?
Sentiment analysis can be run on chat transcripts, emails, and phone call transcriptions (via speech-to-text) to gauge customer emotions during interactions. This helps customer service teams understand customer satisfaction or dissatisfaction and track trends in customer experience.
How does EdgeTier detect emotions and sentiment within customer interactions?
EdgeTier uses specialised natural language processing (NLP) models to analyse every message or utterance in a customer interaction. These models are trained to detect key emotions such as praise, gratitude, confusion, and frustration—emotions that directly correlate with customer satisfaction metrics, like CSAT and NPS. By analysing interactions on a sentence-by-sentence basis, EdgeTier provides granular insights, helping contact centre managers understand customer emotions and identify areas that may need immediate attention.
Can EdgeTier's sentiment analysis be customised for different industries or languages?
Yes, EdgeTier’s sentiment analysis models are multilingual and industry-specific. These models have been trained on customer-service-focused datasets tailored to industries such as travel, retail, and gaming. This ensures high levels of accuracy when detecting emotions in customer interactions, even across different languages.
How can I view and act on customer sentiment insights in EdgeTier?
The platform makes it easy to explore customer sentiment through its intuitive interface. You can filter interactions based on detected emotions—such as frustration or praise—on the Index feature. Additionally, each message within an interaction is tagged with the relevant emotions, allowing contact centre teams to quickly assess and respond to customer sentiment. The platform also provides tools for comparing emotion patterns across agents, teams, and tags, giving managers deeper insights into areas needing improvement or recognition.
How does EdgeTier's emotion detection improve agent performance?
By detecting emotions such as frustration, praise, and gratitude in customer interactions, helps managers identify agents who may need targeted coaching or those who consistently receive positive feedback. EdgeTier also allows managers to compare emotion trends across agents, which can highlight opportunities for performance reviews or help in identifying agents excelling in customer satisfaction.
How can sentiment analysis be used with customer survey data?
Sentiment analysis can be applied to customer survey submissions to identify emotional responses. It allows teams to pinpoint issues causing negative sentiment and quantify how widespread those issues are, leading to better decision-making and prioritisation of fixes.
Can sentiment analysis help assess the severity of anomalies in customer care?
Yes, sentiment analysis can be used to gauge how serious or widespread issues are in the customer care environment. If an anomaly is detected but does not generate negative sentiment, it may suggest that the issue is less critical, helping teams prioritise more pressing problems.
Still have questions?
Get in touch with our knowledgeable team! We're happy to answer any questions you have about our AI-powered VoC software.
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