Customer Experience

6 Best Contact Center Analytics Software of 2024 (Improve CX)

6 Best Contact Center Analytics Software of 2024 (Improve CX)
Customer Service Researcher
LinkedIn icon
6 Best Contact Center Analytics Software of 2024 (Improve CX)

In this article

In this article, we’ll introduce you to SentiSum (our AI-powered contact center analytics software) and show how it excels in the above areas.

Then, we’ll list five alternative tools, so you can make an informed decision about which is the right tool for you.

The 6 Best Contact Center Analytics Software - A Summary

In a nutshell, here are the six contact center analytics tools we'll review in-depth today:

  1. SentiSum: An AI-powered speech & text analytics software that gets detailed insights on all channels
  2. Qualtrics: An enterprise solution that's great for training frontline staff
  3. Nextiva: A one-stop contact center solution with speech analytics
  4. Talkdesk: A specialist in speech analytics
  5. Dialpad: A great for call transcription and real-time agent response suggestions
  6. Nice CXOne: A good choice for basic analytics across all channels

1. SentiSum: Best for Detailed Insights Across All Channels (Text and Voice)

SentiSum is an AI-powered customer analytics engine that extracts granular insights from every support conversation, survey, and review in real time. 

It auto-analyzes and tags every interaction, delivering powerful insights quickly and easily.

While there are many text & sentiment analytics tools out there, very few are useful to contact centers specifically, as they fail to cover all conversation channels—most don't have text and voice analytics capabilities.

SentiSum's language-processing AI covers both voice and text analytics, and gives you insights like:

  • Topics and subtopics mentioned by customers—quantified across all calls.
  • Sentiment analysis—showing you which issues cause customer frustration.
  • Patterns & trends in real-time.
  • Automated feedback on agent performance—speeding up your QA processes.
“SentiSum uncovers two core data points from qualitative text: sentiment and meaning, “That gives a really clear idea of what’s driving friction and which issues should be fixed first.”- Sharad Khandelwal, CEO of SentiSum

How It Works

SentiSum uses machine learning-based AI to understand and analyze qualitative text from any voice of the customer channel.

In a nutshell, here’s how it works:

  • Natural language processing (NLP) technology consumes and analyzes your voice of customer data.
  • Machine learning applies granular tags on customer sentiment, topics, keywords, and more.
  • A simple yet customizable dashboard centralizes insights from all channels for easy access from Customer Support leaders and managers.
  • ChatGPT-like interf

The 4 Factors | How SentiSum Benefits You

So, let’s dive a little deeper into SentiSum. How do we stack up against the four factors that make an effective contact center analytics tool?

Factor 1: SentiSum analyzes customer conversations across all your channels.

SentiSum analyzes customer conversations from from every channel, including:

  • Support tickets (email, chat, social media)
  • Phone calls
  • Surveys (CSAT, NPS)
  • Reviews

It uses advanced natural language processing (NLP) and machine learning to analyze conversations across 100+ languages. This gives you a unified view of the customer journey. 

You even analyze voice calls to unlock insights typically hidden in call center interactions, something that few customer analytics platforms can do.

Factor 2: SentiSum gives you accurate, actionable insights from your data.

If you have thousands of support calls, texts, and emails every day, it’s impossible to analyze them all manually.

So, most Customer Support Leaders now either:

  1. Listen to a handful of calls and extrapolate general learnings from it
  2. Conduct advanced data analytics once a year

But the problem with method #1 is that you might understand what customers are saying, but you might not have the confidence to use this to push improvements. 

The problem with method #2 is that it takes a high level of technical skills to make it happen AND to understand the output. It’s also not scalable, and because you only do it once a year, the insights you get are outdated. 

A contact center analytics platform like SentiSum solves these problems. 

SentiSum gives you confidence to create change by analyzing ALL your call center calls, and giving you deep, granular insights that you wouldn’t be able to access otherwise.  

For instance, SentiSum helped British Airways to aggregate 100,000s of customer reviews and make sense of them in minutes.

Head of Customer Service, British Airways, Read the full case study here.

Our machine-learning based NLP technology auto-analyzes and auto-tags every customer conversation with topic, subtopic, sentiment, urgency, and more. 

This means you can:

  • Quickly identify the root causes of negative sentiment. SentiSum works by immediately analyzing and tagging your voice calls for keywords and sentiment. 

So, you can quickly see relevant key phrases that come up a lot across all your calls—and then dig deeper into sub-tags to get more information.

  • Search your customer calls for mentions of specific products. You may be interested to hear how customers are responding to a new product or a particular service. 

Search for mentions of that product within your calls—or across all your other support channels—and you’ll quickly have access to every relevant conversation.

  • Simply access any other insight by asking SentiSum’s AI assistant. Whatever it is you need, you can ask SentiSum a question in natural language and your AI assistant will instantly feed you the answer.
  • Understand how your staff are responding too. SentiSum also provides insight into your teams’ customer service performance. For instance, you can track how customer sentiment changes throughout the call, to gain an understanding of how staff can improve.

Factor 3: SentiSum is simple to use, by anyone who needs it.

A powerful analytics tool shouldn’t come with a high learning curve.

With SentiSum, you can be up, running, and analyzing your sentiment data in a matter of minutes. 

  • Simply log in to SentiSum to get a clear, real-time understanding of your call center trends. In one easy-to-use dashboard, you can see all the important negative drivers, sentiment changes, agent performance, and more. 
  • Easily flip between different channels to see the key insights for each. Simply choose the channel you need from a drop-down list and all the data will be there for you. (You can see it for yourself in the GIF below ⬇️)
  • Ask natural language questions to the AI assistant for quick answers. Want to quickly bring up data on how customers feel about a specific product? Ask SentiSum’s AI assistant in everyday language.
  • Make beautiful reports in seconds. If a call center analyst needs to share data with company leaders, that’s easy. You can create clear and detailed reports in a matter of clicks.

This self-serve access empowers every department and team to leverage customer insights right away, without the need for technical expertise.

Bhavik Patel, Hopin, Read the full case study here.

Factor 4: SentiSum integrates with your current tech stack. 

SentiSum offers seamless out-of-the-box integration with all major platforms, such as:

  • Zendesk
  • Intercom
  • Trustpilot
  • G2
  • Google Play
  • Apple Store
  • SurveyMonkey
  • Typeform
  • And many more.

We're completely secure and follow strict data security regulations—with clients of our size, we're used to managing complex security needs.

You can build standardized automation flows with a custom AI model and push insights to these tools. 

This allows you to set up prioritization and triage rules based on customer sentiment and urgency.

Reviews

SentiSum has an overall rating of 4.8/5 stars on G2, based on reviews from companies like Gousto, Hotjar, Scandinavian Biolabs, and James Villas.

Pricing

SentiSum is a strong fit for companies with over 3,000 monthly support tickets, where the manual effort to analyze and tag tickets becomes a constant challenge. 

Here’s an overview of our pricing structure:

  • Pro: For mid-market companies starting at $3,000/month. Supports up to 5,000 conversations/month, 6 months of historical data, and more features.
  • Enterprise: Fully customizable pricing. Scales with the number of users, conversations, and languages — including additional capabilities like workflow automation.

Want to see SentiSum’s customer analytics platform in action? Book a demo below ⬇️

2. Qualtrics: The Best Contact Center Analytics Platform for Training Frontline CX Teams

Qualtrics is a complete experience management (XM) platform for product, people operations, and customer support teams. 

It uses behavioral cues (like session duration and click-through rates) and conversational data (like call recordings and chat transcripts) to visualize the whole customer journey.

How it Works

Qualtrics aggregates customer interactions with contact centers across 35 channels, including calls, chats, texts, social media posts, and surveys. 

Then, it analyzes those interactions to identify churn risks and upsell opportunities. 

You can start by defining your scoring criteria so that Qualtrics knows what good customer service looks like to you. 

There’s an out-of-the-box scorecard builder that you can use to define expectations, like agent knowledge, empathy, and script compliance. Qualtrics will use these to evaluate each conversation.

The platform also offers a suite of AI features to reduce manual effort. 

Apart from providing after-call summaries that review how each interaction went, it can create real-time prompts to guide agents during support conversations.

Finally, the behavioral feedback component analyzes factors like session duration, click-through rate, and time spent on page to see how your customers interact with your product across various channels. 

Qualtrics uses these to visualize the entire customer journey so that you can identify areas of friction.

Reviews

Qualtrics CX for Contact Centers has an overall rating of 4.1/5 stars on G2. 

Customers often praise the accuracy of its insights. 

Negative reviews mention the UI, which is limited in customizability and makes accessing information harder.

3. Nextiva: One-Stop Contact Center Analytics Solution for Small and Mid-Sized Contact Centers

Nextiva is an affordable voice calling solution with its own speech analytics function for call centers. It offers detailed reports that monitor agent performance and analyze customer trends in real time. 

How it Works

Nextiva is a cloud-based phone system and communications platform. 

You can add users to an online portal and assign a phone number to each. Nextiva handles the phone infrastructure behind the scenes so users don't have to deal with on-site PBX hardware. 

It also provides a unified communication solution for live chat, video conferencing, and screen sharing. While analytics isn’t the primary focus, Nextiva does track common call center metrics like average talk time and number of calls per user.

All of the analytics data is visualized through graphs, charts, and reports that you can fully customize and share with your team. Nextiva even gamifies the data for you with agent leaderboards to improve employee productivity. 

There’s also an AI component that monitors conversations. It can summarize calls, surface prompts, and create custom chatbots that answer basic questions. 

You can also use AI to route customer calls to the most appropriate agent, reducing service time.

Reviews

Nextiva has an overall rating of 4.5/5 stars on G2. Positive reviews mention the platform’s customizability and accessibility. Negative reviews talk about occasional downtime, when the app seems to stop working for brief periods.

4. Talkdesk: Advanced Speech Analytics With Historical Data Tracking

Talkdesk, like Nextiva, offers a cloud-based contact center management solution for voice calling and support automation. Its customer analytics tool also uses AI and NLP to analyze call recordings.

How it Works

Talkdesk is a one-stop contact center management and analytics platform powered by Voice-over-Internet-Protocol technology (VoIP). 

It uses AI to analyze voice calls with customers. However, the main focus is on providing call center automation and softphone solutions.

Once signed up with Talkdesk, an admin can configure call flows, create prompts, manage users, and monitor call activity through the online portal. 

Agents can see caller information pop up on the screen when receiving calls.

Talkdesk uses NLP to analyze conversations for common pain points, customer sentiment, and agent skill. Trends are visualized using charts and graphs on the dashboard. 

With the new GPT-4 add-on, you can also generate contextual recommendations and summarize conversations with AI.

There’s also a self-service chatbot that enables customers to quickly resolve basic issues. Customers can ask questions and get answers in natural language 24/7, reducing the workload for human agents.

Reviews

Talkdesk has an overall rating of 4.4/5 stars on G2. Many reviews talk about the accuracy of the insights, while negative ones mention a difficult interface that hampers navigation.

Now, let's look at our next tool of the article.

5. Dialpad - Best AI-Powered Workspace for Contact Center Teams

Dialpad - Learn More Here

Dialpad is an AI contact center and an analytics platform combined. In one user-friendly workspace, you can take calls, respond to messages, and get insights into trending topics and customer sentiment.

How it works

Dialpad is useful for both managers and individual customer service agents.

The agent can take calls and respond to messages right on the main workspace. While they’re on a call, Dialpad’s AI automatically takes notes and transcribes the conversation. 

It also provides suggestions on how to resolve requests when it recognizes specific keywords (e.g. “refund”).

Managers can easily see which agents need extra support by analyzing customer sentiment. 

For instance, if a conversation was tagged “Negative”, managers can read the real-time transcript and even hop on the call to help resolve the issue.

They can also:

  • Get updates on SLA changes or response times
  • Drill into heatmaps to check on call volumes
  • Use keyword search to see which support topics are trending

Dialpad’s built-in AI also analyzes hundreds of customer conversations and tracks customer satisfaction by combining predictive insights with CSAT survey results.

You can watch the full demo here.

Reviews

The platform has a G2 rating of 4.5/5 stars.

Pricing

Dialpad starts from $23/user/month but this can quickly snowball to a few hundred if you have a large customer support team. 

6. Nice CXOne - The Best Contact Center Analytics Software for Omnichannel Analytics

Nice CXOne is an AI-powered analytics software that analyzes speech and text data from all your channels (phone calls, emails, chats, and more). 

How It Works

With CXOne, you can:

1/ Analyze customer sentiment: Nice’s sentiment analytics AI surfaces pain points related to process issues, product defects, agent performance, and more. The dashboard also shows the emotions of each negative conversation, like ‘frustration’.

2/ Identify churn risk: You can also identify which customers are dissatisfied based on their sentiment, frustration detection, and discussion topics. Then, resolve issues fast for these customers so they don't churn.

3/ Uncover root causes: Dig deeper into the root causes of frustration or negative sentiment. This is key to improve handle times and reduce repeat contacts. 

  1. Track agent performance: You can also custom rules to better track agent performance and detect whether key phrases are used to ensure agents are in compliance.

Reviews

Nice CXOne scores 4.3 out of 5 stars on G2. 

Pricing

Nice CXOne starts from $71/agent/month for “digital agent” (excluding voice and omnichannel agents). 

The Essential Suite (including all agents) is $135/agent/month.

The 6 Best Contact Center Analytics Software - Summary

A summary of 6 best contact center analytics software - SentiSum
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Customer Experience

6 Best Contact Center Analytics Software of 2024 (Improve CX)

March 29, 2024
Ben Goodey
Customer Service Researcher
In this article
Understand your customer’s problems and get actionable insights
See pricing

What makes the best contact center analytics software? 

Based on our research, it boils down to four main things:

4 Factors to Look for in a Contact Center Analytics Software

Factor 1: Does the Tool Analyze Data From All Customer Feedback Channels?

If you're a mid-sized or enterprise company, you probably have thousands of customer conversations happening across different platforms (e.g. surveys, reviews, customer support chats, emails, calls). 

Make sure the analytics software you choose analyzes data from ALL your channels – both the traditional ones and the more obscure ones like phone calls. 

Factor 2: Are the Insights Genuinely Useful and Trustable?

Great contact center analytics tools turn large volumes of raw conversations into helpful, quantifiable insights. 

Actionable insights are accurate, granular, and easy to access. 

The latest developments in AI have made these even more to achieve—there’s really no excuse for your provider to not use AI.

We recommend heading into your purchase decision with a few questions you’d like answered about your customers. If the tools can give you those answers confidently, that’s a great sign.

Factor 3: Is the Tool Easy to Use for Anyone Who Needs It?

The best customer experience analytics software is simple and easy to use. Anyone (not just the CS team) should be able to just log in and start reading insights right away. 

This is critical to make sure the insights you find get implemented organization-wide.

Factor 4: Does the Tool Integrate With Your Existing Tech Stack?

Your voice of customer data likely comes from tools like Zendesk, SurveyMonkey, and Reviews (or the equivalent competitors). 

We recommend making sure the integrations are seamless and two-way.

For example, SentiSum does advanced AI tagging to analyze support conversations.

These tags are used for insights and analytics, but we also push them back to your helpdesk so you can set up prioritization and triage rules.

Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.

In this article

In this article, we’ll introduce you to SentiSum (our AI-powered contact center analytics software) and show how it excels in the above areas.

Then, we’ll list five alternative tools, so you can make an informed decision about which is the right tool for you.

The 6 Best Contact Center Analytics Software - A Summary

In a nutshell, here are the six contact center analytics tools we'll review in-depth today:

  1. SentiSum: An AI-powered speech & text analytics software that gets detailed insights on all channels
  2. Qualtrics: An enterprise solution that's great for training frontline staff
  3. Nextiva: A one-stop contact center solution with speech analytics
  4. Talkdesk: A specialist in speech analytics
  5. Dialpad: A great for call transcription and real-time agent response suggestions
  6. Nice CXOne: A good choice for basic analytics across all channels

1. SentiSum: Best for Detailed Insights Across All Channels (Text and Voice)

SentiSum is an AI-powered customer analytics engine that extracts granular insights from every support conversation, survey, and review in real time. 

It auto-analyzes and tags every interaction, delivering powerful insights quickly and easily.

While there are many text & sentiment analytics tools out there, very few are useful to contact centers specifically, as they fail to cover all conversation channels—most don't have text and voice analytics capabilities.

SentiSum's language-processing AI covers both voice and text analytics, and gives you insights like:

  • Topics and subtopics mentioned by customers—quantified across all calls.
  • Sentiment analysis—showing you which issues cause customer frustration.
  • Patterns & trends in real-time.
  • Automated feedback on agent performance—speeding up your QA processes.
“SentiSum uncovers two core data points from qualitative text: sentiment and meaning, “That gives a really clear idea of what’s driving friction and which issues should be fixed first.”- Sharad Khandelwal, CEO of SentiSum

How It Works

SentiSum uses machine learning-based AI to understand and analyze qualitative text from any voice of the customer channel.

In a nutshell, here’s how it works:

  • Natural language processing (NLP) technology consumes and analyzes your voice of customer data.
  • Machine learning applies granular tags on customer sentiment, topics, keywords, and more.
  • A simple yet customizable dashboard centralizes insights from all channels for easy access from Customer Support leaders and managers.
  • ChatGPT-like interf

The 4 Factors | How SentiSum Benefits You

So, let’s dive a little deeper into SentiSum. How do we stack up against the four factors that make an effective contact center analytics tool?

Factor 1: SentiSum analyzes customer conversations across all your channels.

SentiSum analyzes customer conversations from from every channel, including:

  • Support tickets (email, chat, social media)
  • Phone calls
  • Surveys (CSAT, NPS)
  • Reviews

It uses advanced natural language processing (NLP) and machine learning to analyze conversations across 100+ languages. This gives you a unified view of the customer journey. 

You even analyze voice calls to unlock insights typically hidden in call center interactions, something that few customer analytics platforms can do.

Factor 2: SentiSum gives you accurate, actionable insights from your data.

If you have thousands of support calls, texts, and emails every day, it’s impossible to analyze them all manually.

So, most Customer Support Leaders now either:

  1. Listen to a handful of calls and extrapolate general learnings from it
  2. Conduct advanced data analytics once a year

But the problem with method #1 is that you might understand what customers are saying, but you might not have the confidence to use this to push improvements. 

The problem with method #2 is that it takes a high level of technical skills to make it happen AND to understand the output. It’s also not scalable, and because you only do it once a year, the insights you get are outdated. 

A contact center analytics platform like SentiSum solves these problems. 

SentiSum gives you confidence to create change by analyzing ALL your call center calls, and giving you deep, granular insights that you wouldn’t be able to access otherwise.  

For instance, SentiSum helped British Airways to aggregate 100,000s of customer reviews and make sense of them in minutes.

Head of Customer Service, British Airways, Read the full case study here.

Our machine-learning based NLP technology auto-analyzes and auto-tags every customer conversation with topic, subtopic, sentiment, urgency, and more. 

This means you can:

  • Quickly identify the root causes of negative sentiment. SentiSum works by immediately analyzing and tagging your voice calls for keywords and sentiment. 

So, you can quickly see relevant key phrases that come up a lot across all your calls—and then dig deeper into sub-tags to get more information.

  • Search your customer calls for mentions of specific products. You may be interested to hear how customers are responding to a new product or a particular service. 

Search for mentions of that product within your calls—or across all your other support channels—and you’ll quickly have access to every relevant conversation.

  • Simply access any other insight by asking SentiSum’s AI assistant. Whatever it is you need, you can ask SentiSum a question in natural language and your AI assistant will instantly feed you the answer.
  • Understand how your staff are responding too. SentiSum also provides insight into your teams’ customer service performance. For instance, you can track how customer sentiment changes throughout the call, to gain an understanding of how staff can improve.

Factor 3: SentiSum is simple to use, by anyone who needs it.

A powerful analytics tool shouldn’t come with a high learning curve.

With SentiSum, you can be up, running, and analyzing your sentiment data in a matter of minutes. 

  • Simply log in to SentiSum to get a clear, real-time understanding of your call center trends. In one easy-to-use dashboard, you can see all the important negative drivers, sentiment changes, agent performance, and more. 
  • Easily flip between different channels to see the key insights for each. Simply choose the channel you need from a drop-down list and all the data will be there for you. (You can see it for yourself in the GIF below ⬇️)
  • Ask natural language questions to the AI assistant for quick answers. Want to quickly bring up data on how customers feel about a specific product? Ask SentiSum’s AI assistant in everyday language.
  • Make beautiful reports in seconds. If a call center analyst needs to share data with company leaders, that’s easy. You can create clear and detailed reports in a matter of clicks.

This self-serve access empowers every department and team to leverage customer insights right away, without the need for technical expertise.

Bhavik Patel, Hopin, Read the full case study here.

Factor 4: SentiSum integrates with your current tech stack. 

SentiSum offers seamless out-of-the-box integration with all major platforms, such as:

  • Zendesk
  • Intercom
  • Trustpilot
  • G2
  • Google Play
  • Apple Store
  • SurveyMonkey
  • Typeform
  • And many more.

We're completely secure and follow strict data security regulations—with clients of our size, we're used to managing complex security needs.

You can build standardized automation flows with a custom AI model and push insights to these tools. 

This allows you to set up prioritization and triage rules based on customer sentiment and urgency.

Reviews

SentiSum has an overall rating of 4.8/5 stars on G2, based on reviews from companies like Gousto, Hotjar, Scandinavian Biolabs, and James Villas.

Pricing

SentiSum is a strong fit for companies with over 3,000 monthly support tickets, where the manual effort to analyze and tag tickets becomes a constant challenge. 

Here’s an overview of our pricing structure:

  • Pro: For mid-market companies starting at $3,000/month. Supports up to 5,000 conversations/month, 6 months of historical data, and more features.
  • Enterprise: Fully customizable pricing. Scales with the number of users, conversations, and languages — including additional capabilities like workflow automation.

Want to see SentiSum’s customer analytics platform in action? Book a demo below ⬇️

2. Qualtrics: The Best Contact Center Analytics Platform for Training Frontline CX Teams

Qualtrics is a complete experience management (XM) platform for product, people operations, and customer support teams. 

It uses behavioral cues (like session duration and click-through rates) and conversational data (like call recordings and chat transcripts) to visualize the whole customer journey.

How it Works

Qualtrics aggregates customer interactions with contact centers across 35 channels, including calls, chats, texts, social media posts, and surveys. 

Then, it analyzes those interactions to identify churn risks and upsell opportunities. 

You can start by defining your scoring criteria so that Qualtrics knows what good customer service looks like to you. 

There’s an out-of-the-box scorecard builder that you can use to define expectations, like agent knowledge, empathy, and script compliance. Qualtrics will use these to evaluate each conversation.

The platform also offers a suite of AI features to reduce manual effort. 

Apart from providing after-call summaries that review how each interaction went, it can create real-time prompts to guide agents during support conversations.

Finally, the behavioral feedback component analyzes factors like session duration, click-through rate, and time spent on page to see how your customers interact with your product across various channels. 

Qualtrics uses these to visualize the entire customer journey so that you can identify areas of friction.

Reviews

Qualtrics CX for Contact Centers has an overall rating of 4.1/5 stars on G2. 

Customers often praise the accuracy of its insights. 

Negative reviews mention the UI, which is limited in customizability and makes accessing information harder.

3. Nextiva: One-Stop Contact Center Analytics Solution for Small and Mid-Sized Contact Centers

Nextiva is an affordable voice calling solution with its own speech analytics function for call centers. It offers detailed reports that monitor agent performance and analyze customer trends in real time. 

How it Works

Nextiva is a cloud-based phone system and communications platform. 

You can add users to an online portal and assign a phone number to each. Nextiva handles the phone infrastructure behind the scenes so users don't have to deal with on-site PBX hardware. 

It also provides a unified communication solution for live chat, video conferencing, and screen sharing. While analytics isn’t the primary focus, Nextiva does track common call center metrics like average talk time and number of calls per user.

All of the analytics data is visualized through graphs, charts, and reports that you can fully customize and share with your team. Nextiva even gamifies the data for you with agent leaderboards to improve employee productivity. 

There’s also an AI component that monitors conversations. It can summarize calls, surface prompts, and create custom chatbots that answer basic questions. 

You can also use AI to route customer calls to the most appropriate agent, reducing service time.

Reviews

Nextiva has an overall rating of 4.5/5 stars on G2. Positive reviews mention the platform’s customizability and accessibility. Negative reviews talk about occasional downtime, when the app seems to stop working for brief periods.

4. Talkdesk: Advanced Speech Analytics With Historical Data Tracking

Talkdesk, like Nextiva, offers a cloud-based contact center management solution for voice calling and support automation. Its customer analytics tool also uses AI and NLP to analyze call recordings.

How it Works

Talkdesk is a one-stop contact center management and analytics platform powered by Voice-over-Internet-Protocol technology (VoIP). 

It uses AI to analyze voice calls with customers. However, the main focus is on providing call center automation and softphone solutions.

Once signed up with Talkdesk, an admin can configure call flows, create prompts, manage users, and monitor call activity through the online portal. 

Agents can see caller information pop up on the screen when receiving calls.

Talkdesk uses NLP to analyze conversations for common pain points, customer sentiment, and agent skill. Trends are visualized using charts and graphs on the dashboard. 

With the new GPT-4 add-on, you can also generate contextual recommendations and summarize conversations with AI.

There’s also a self-service chatbot that enables customers to quickly resolve basic issues. Customers can ask questions and get answers in natural language 24/7, reducing the workload for human agents.

Reviews

Talkdesk has an overall rating of 4.4/5 stars on G2. Many reviews talk about the accuracy of the insights, while negative ones mention a difficult interface that hampers navigation.

Now, let's look at our next tool of the article.

5. Dialpad - Best AI-Powered Workspace for Contact Center Teams

Dialpad - Learn More Here

Dialpad is an AI contact center and an analytics platform combined. In one user-friendly workspace, you can take calls, respond to messages, and get insights into trending topics and customer sentiment.

How it works

Dialpad is useful for both managers and individual customer service agents.

The agent can take calls and respond to messages right on the main workspace. While they’re on a call, Dialpad’s AI automatically takes notes and transcribes the conversation. 

It also provides suggestions on how to resolve requests when it recognizes specific keywords (e.g. “refund”).

Managers can easily see which agents need extra support by analyzing customer sentiment. 

For instance, if a conversation was tagged “Negative”, managers can read the real-time transcript and even hop on the call to help resolve the issue.

They can also:

  • Get updates on SLA changes or response times
  • Drill into heatmaps to check on call volumes
  • Use keyword search to see which support topics are trending

Dialpad’s built-in AI also analyzes hundreds of customer conversations and tracks customer satisfaction by combining predictive insights with CSAT survey results.

You can watch the full demo here.

Reviews

The platform has a G2 rating of 4.5/5 stars.

Pricing

Dialpad starts from $23/user/month but this can quickly snowball to a few hundred if you have a large customer support team. 

6. Nice CXOne - The Best Contact Center Analytics Software for Omnichannel Analytics

Nice CXOne is an AI-powered analytics software that analyzes speech and text data from all your channels (phone calls, emails, chats, and more). 

How It Works

With CXOne, you can:

1/ Analyze customer sentiment: Nice’s sentiment analytics AI surfaces pain points related to process issues, product defects, agent performance, and more. The dashboard also shows the emotions of each negative conversation, like ‘frustration’.

2/ Identify churn risk: You can also identify which customers are dissatisfied based on their sentiment, frustration detection, and discussion topics. Then, resolve issues fast for these customers so they don't churn.

3/ Uncover root causes: Dig deeper into the root causes of frustration or negative sentiment. This is key to improve handle times and reduce repeat contacts. 

  1. Track agent performance: You can also custom rules to better track agent performance and detect whether key phrases are used to ensure agents are in compliance.

Reviews

Nice CXOne scores 4.3 out of 5 stars on G2. 

Pricing

Nice CXOne starts from $71/agent/month for “digital agent” (excluding voice and omnichannel agents). 

The Essential Suite (including all agents) is $135/agent/month.

The 6 Best Contact Center Analytics Software - Summary

A summary of 6 best contact center analytics software - SentiSum

Frequently asked questions

Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.

Do you integrate with my systems? How long is that going to take?

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What size company do you usually work with? Is this valuable for me?

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What is your term of the contract?

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How do you keep my data private?

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Contact Center Analytics Software - FAQ

What is contact center analytics?

Contact center analytics is the process of collecting, analyzing, and reporting call center data to help identify and improve trends in customer sentiment and agent performance.

The most useful data sources to analyze are your customer conversations, stored across email, chat, and call logs. You can also study your support tickets, feedback forms, and review pages.

What are the different types of contact center analytics?

Since your customer data lives in silos across different channels, combining various types of contact center analytics can give you a complete view of the customer experience. For example:

  • Speech Analytics: Analyzes voice calls between agents and customers to extract useful insights from conversations.
  • Text Analytics: Evaluates written communications such as emails, chat messages, and social media interactions with customers.
  • Survey Analytics: Assesses feedback from customer surveys to gauge satisfaction, understand experiences, and identify areas for improvement.
  • Sentiment Analytics: Specifically focuses on understanding emotions and sentiments expressed by customers in their interaction.
  • Omnichannel Analytics: Provides a holistic view of customer interactions across multiple channels, enabling a unified understanding of the customer journey and experiences.
  • Predictive Analytics: Utilizes historical data to forecast future trends, customer behaviors, and potential contact center challenges.

Which KPIs should I track for contact center performance analytics?

By collecting and analyzing customer data from different channels, you can improve key metrics like your CSAT and NPS scores. Here are some other KPIs you can improve with contact center analytics: 

  • CSAT Score: A metric for measuring and understanding customer satisfaction with a recent interaction, product, or service. 
  • FCR Percentage: The percentage of customer issues resolved on the first contact without needing further contact. 
  • NPS Score: A metric that measures customer loyalty and likelihood to recommend, scored from -100 to 100. 
  • Average Handle Time: The average duration of customer interactions, including talk, hold, and wrap-up time. 
  • Abandonment Rate: The percentage of callers who hang up while waiting in a queue, before reaching an agent. 
  • Service Level: The percentage of customer calls answered within a defined timeframe, usually 20-60 seconds.

What software do most call centers use?

Most call centers use different types of applications to manage and streamline their operations. Some common examples include:

  • Call Center Management Software: Used for handling inbound and outbound calls. Often offers automatic call distribution (ACD), interactive voice response (IVR), call queuing, and call recording.
  • Customer Relationship Management (CRM) Software: Helps call centers manage customer data, track interactions, and personalize customer communication. 
  • Analytics Software: Analyzes customer data and interactions to provide insights into customer behavior and preferences. 
  • Workforce Management Software: Used for scheduling agents, forecasting call volumes, and managing agent performance. 
  • Communication and Collaboration Tools: Used within call centers to facilitate communication and collaboration among team members. It includes platforms like Slack and Microsoft Teams.

How is AI used in call centers?

AI technology can be used across call centers in several different ways, for example: 

  • AI-powered chatbots can handle routine inquiries and provide instant responses to common customer questions, reducing wait times and freeing up human agents.
  • AI can analyze incoming calls in real time to determine the caller's needs and route them to the most appropriate agent.
  • AI can analyze historical data to predict future call volumes and customer behavior, helping call centers optimize staffing levels.
  • AI tools can assess the tone and sentiment of customer interactions, providing feedback on customer satisfaction and agent performance.
  • AI can transcribe and analyze voice interactions to identify trends, monitor compliance, and uncover insights for quality assurance.
Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.