Speech analytics software enables companies and organizations to track, record, analyze, and optimize customer and agent phone calls in order to improve customer experience via sentiment analysis, transcription, language detection, and more. Compare and read user reviews of the best Speech Analytics software currently available using the table below. This list is updated regularly.
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CallFinder
CallTrackingMetrics
Twilio
Call Center Studio
Ozonetel
OrecX
Observe.AI
Stratifyd
Yandex
Delacon
MiaRec
Audioburst
Castel Communications
talvala
Marsview
Siro
Knowlarity Communications Pvt. Ltd.
Natterbox
CallMiner
Eleveo
DialConnection
Appen
Prodigal Technologies
Capturi
Xdroid
Level AI
Hinduja Global Solutions
Sestek
Happitu
MOJO-CX
Speech analytics software is a powerful tool that can help businesses better understand customer needs and provide insights into how customers interact with your company. It works by transcribing spoken conversations with customers into text, which allows for automated analysis of customer conversations. The data it provides can be used to optimize processes such as customer service and contact center operations, sales performance, marketing campaigns, product training, and more.
The primary purpose of speech analytics software is to provide companies with deep insights into the conversations they have with their customers across all channels—phone calls, web chats, email communications—and on any platform or device. This in-depth analysis helps reveal areas for improvement in customer experience (CX), communication effectiveness, process optimization, sentiment analysis towards brand/products/services, trends/patterns across conversation topics and more. Speech analytics also enables organizations to quickly identify cause-effect relationships between various consumer touchpoints such as phone calls and website visits or other interactions with the brand on social media platforms.
Speech analytics technology works by first transcribing audio recordings of customer interactions into text using sophisticated speech recognition algorithms. This transcription process is often referred to as ‘speech-to-text’ conversion. Once the transcript has been generated, speech analytics software then uses natural language processing (NLP) algorithms to analyze the text automatically so that it can be sorted into various categories and tagged according to specific parameters such as sentiment or topic of conversation. In addition to sorting through the data manually and applying tags based on predefined criteria manually set by the user(s), many speech analytics tools today come equipped with preconfigured AI models such as sentiment analysis capabilities that allow for automatic categorization of transcripts based on AI-driven models trained by supervised learning methods from a large corpus of labeled data points.
Once the raw data has been organized into relevant categories based on user input (or predefined models), further machine learning techniques are often employed by businesses in order to uncover deeper levels of insights from their analyzed conversations —such as trending topics over time across certain demographics or groupings within those demographics—further enabling them to make informed decisions regarding operations improvements or marketing strategies tailored around customer needs while also gaining an understanding of their target audience’s perception towards their products/services/brand at large scales more quickly than traditional methods would have allowed otherwise thanks to automation.
Overall, speech analytics software offers businesses countless opportunities for continuous improvement across all facets of their operations (and beyond) thanks to its ability to easily distill actionable insights out of extremely large datasets containing detailed information about customer interactions in real time in both digital & physical spaces -allowing them not only predict and respond faster but think smarter too when it comes optimizing CX performance while driving business growth simultaneously through effective decision making.
The cost of speech analytics software can vary greatly, depending on the type of features and functionality you need for your specific business needs. Generally speaking, entry-level speech analytics software starts around $1,000 per user license. However, more comprehensive solutions with additional features may cost up to $10,000 or more per user license. Additionally, some providers charge subscription fees instead of one-time costs. Depending on the provider, these subscriptions may range from a few hundred dollars per month to thousands of dollars annually. Choosing the right platform and understanding your budget will help you find a speech analytics solution that meets your needs without breaking the bank.
Speech analytics software is capable of integrating with a variety of software to help gather, analyze and store data. Depending on the use case and desired outcomes, it can be integrated with customer relationship management (CRM) software, contact center recording solutions, audio transcription services, virtual assistant platforms like Alexa for Business or Google Home, data visualization tools and business intelligence (BI) tools. Additionally, speech analytics can provide insights from emails, chat logs and surveys when integrated with the appropriate applications. By leveraging these integrations, speech analytics software can assess customer sentiment with greater accuracy and efficiency.
When selecting speech analytics software, consider a few different factors.
First and foremost, the type of customer interactions that need to be analyzed should be considered — does the software offer capabilities for analyzing customer service, sales or marketing calls? Also, look for features such as speech recognition accuracy, natural language processing capabilities and other advanced analysis functions that are required for your organization's specific needs. Utilize the tools given on this page to examine speech analytics software in terms of price, features, integrations, user reviews, and more.
Next, decide which types of data should be collected - such as customer sentiment scores or key word searches - and research whether the software you are evaluating allows you to capture this kind of data. Additionally, think about how easily the software can integrate with your other existing technologies; it’s important that it connects well with your systems so that data can be quickly processed and mined.
Finally, make sure that you understand the cost associated with the software – particularly if there is any additional licensing fees or subscription costs. You also want to ensure that handling and storage technologies offered by the vendor have sufficient security measures in place to protect sensitive information.
By taking all these factors into consideration when researching speech analytics software, you will be able to select a solution that fits best for your business needs.