With our latest advancements in speech-to-text technology, businesses can now analyze support and sales calls directly within Chattermill, unlocking brand-new insights, eliminating data silos, and consolidating all data in one place.
CX and Product teams rely on Chattermill to analyze millions of customer comments every year to understand feedback from surveys, product reviews, social media channels, and support tickets at scale. But what about understanding what customers actually say in thousands of support and sales calls your teams handle weekly or monthly?
Your customer and prospect calls are one of the richest sources of customer feedback, full of context, nuances and details. And yet, too often, CX and Product teams don't have access to voice data stored in separate tools and systems. These silos ultimately slow CX and Product decisions and make it hard to get a holistic understanding of customer experiences.
That’s why as of today, you can connect your favorite tools, like Aircall, Dixa, Gong, or 8x8, with Chattermill and start analyzing every support and sales conversation to tap into one of the most valuable sources of customer feedback. We're introducing Chattermill’s Speech Analytics - a powerful tool for unlocking valuable insights in every conversation.
Insights from customer and prospect calls are no longer siloed
The biggest obstacle to understanding key issues, concerns, or customer preferences in your support and sales calls is simply access to the data. While your organization likely uses various tools to record and store these conversations, voice data is often siloed within individual departments. And if you're one of the CX leaders, Product Managers, or UX Specialists lucky enough to gain access, you’re still limited to listening to only a fraction of the calls.
What if you could analyze thousands of support calls to uncover all the reasons why your customers reach out? What if you could capture new product ideas directly from prospect interactions? And what if your entire organization could monitor these insights in real-time, spotting trends and patterns as they emerge?
Chattermill's Speech Analytics gives your organization unlimited access to insights from every call recording, keeping you connected to what your customers are saying every single day.
What is Speech Analytics?
Speech Analytics, (also called Voice Analytics or Conversational Analytics), is a technology that processes audio recordings, such as customer support and sales calls, to extract valuable insights from human speech. It uses various techniques, such as automatic speech recognition (ASR), natural language processing (NLP), and machine learning, to identify patterns, trends, and sentiments in customer interactions.
Speech Analytics helps organizations leverage call recordings and transcripts to improve customer experiences, build better products, and drive business growth. It helps identify critical insights, customer preferences, and emerging trends from audio data (MP3 files) that might be currently stored in various tools and platforms, such as:
- Customer Support Calls: Aircall, Dixa, Zendesk Talk, Talkdesk, Intercom Voice, Freshworks, Five9, Salesforce Service Cloud, Twilio
- Sales Calls: Gong
Chattermill's Speech Analytics translates conversations in over 99+ languages and transcribes them into text, making it easy to analyze and act on.
The science behind Speech Analytics
Chattermill's Speech Analytics transforms spoken language into valuable insights through a series of complex processes.
Speech-to-Text Transcription:
Chattermill's speech-to-text technology is a foundational element in converting audio files into structured text, setting the stage for detailed NLP-driven analysis by Chattermill. This technology ensures high accuracy and scalability.
- Automatic Speech Recognition: Initially, audio files are processed through Automatic Speech Recognition (ASR) technology to produce text from audio with high speed and accuracy. This step makes it feasible to handle large volumes of data effectively, creating a reliable base for subsequent analysis.
- Language Detection and Translation: Automatically identifying the dominant language in each audio file, Chattermill's Speech Analytics translates non-English text into English where needed. This capability accommodates over 99 languages and dialects, ensuring global compatibility.
- Post-Processing for Accuracy: Our technology refines transcriptions by correcting likely errors, normalizing spelling for brand or entity names, and standardizing punctuation. This additional layer of error correction improves readability and consistency in the transcript, as well as the accuracy of analysis.
- Speaker Identification: By assigning labels like "agent" or "customer" to each speaker, it's easier to identify who said what during multi-speaker conversations. This improves the clarity of the data, making it more useful in detecting themes and analyzing sentiment.
Natural Language Processing (NLP):
Chattermill uses its proprietary AI engine, Lyra AI, to analyze transcribed text from audio and video files, ensuring high accuracy in customer feedback analysis.
- Theme Identification: Our advanced AI models detect and categorize the main topics or themes in a large set of text data. This involves analyzing the text for patterns, keywords, and concepts to group related ideas or discussions under broader themes.
- Aspect-Based Sentiment Analysis: Lyra AI determines sentiment towards specific aspects identified in the audio transcript, providing deeper insights into customer opinions on components like "product quality" or "customer service."
- Phrase Detection: Chattermill's Lyra AI excels at pinpointing contextually intelligent and granular keyphrases, facilitating the generation of actionable and granular insights.
- AI-Powered Summaries: Chattermill leverages the latest Generative AI technology to create instant summaries, highlighting recurring customer issues, pain points, and questions. Chattermill automatically summarizes all calls, delivering insights into every customer interaction.
Speech Analytics common use cases and applications
Here's how CX, Customer Insights, and Product teams can put Chattermill's Speech Analytics to use:
Enhancing customer experiences: Speech Analytics captures customer sentiment from voice calls, enabling businesses to prioritize customer complaints, needs, and preferences. As a result, companies can tailor their products and services to enhance the overall customer experience.
Understanding customer support contact reasons: Analyzing customer support inquiries at scale helps teams identify the most frequent reasons customers reach out, such as questions about order status or shipping delays. With accurate and consistent analysis, teams can reduce inquiry volume without spending hours on manual analysis.
Identifying product issues: When the number of support calls suddenly spike, Product Teams typically depend on customer-facing teams to identify the underlying issues. With Speech Analytics, they can quickly uncover the product problems driving customer frustration and respond effectively - eliminating the need for time-consuming manual analysis.
Reducing customer churn: When teams take a closer look at churn reasons, customer support calls may reveal more detail and nuance than traditional feedback channels. Speech analytics helps identify signs of dissatisfaction, reasons for returns, or mentions of competitor brands to mitigate the risk of churn.
Improving operational efficiency: Customer support calls and sales conversations can provide valuable insights into logistics and delivery challenges. With Speech Analytics, teams can identify and quantify the impact of shipping delays, incorrect tracking information, or missed deliveries.
Identifying product defects: By examining support calls, teams can uncover significant customer concerns related to product quality or sizing issues. This insight can help prevent further returns, refunds, and cancellations.
Informing the product roadmap: Product teams often rely on various tools and processes to gather feedback from different departments, resulting in a lot of noise and minimal actionable insights. By analyzing voice data from all sales calls, support calls, and customer interviews over time, teams can make informed product decisions without needing to compile ad-hoc requests from sales and customer success teams.
Ready to transform how you use Chattermill?
Voice data is just one aspect of customer interaction with your business. Customers also provide feedback through product reviews, surveys, customer support emails, and social media. To gain a comprehensive understanding, it’s essential to monitor customer experience across all channels.
Chattermill's Speech Analytics, integrated into the Customer Experience Intelligence platform, combines voice data with feedback from various sources, giving you a complete view of your customer journey.
If you’d like to see Speech Analytics in action, take a moment to watch our video about how Qonto uses this technology to make informed product decisions.
If you're eager to explore the possibilities further, reach out to our team for a personalized demo.
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