Speech vs Text Analytics: 3 Crucial Differences
speech analytics, text analytics, conversational ai, voice analytics, iovox insights,
With speech and text analytics, businesses can easily improve their operating performance.
How?
By boosting revenue or creating a better user experience when customers call for support.
And you, too, may want in on this for your business if you have a contact center or a customer-facing sales team.
But the main question is:
Should you go for speech or text analytics, and how are they different from one another?
In this article, we’ll compare speech vs text analytics and learn if there’s an overlap between the two. We’ll also tell you why you should go for speech analytics and cover some analytics FAQs.
This Article Contains:
(Click on a link to jump to a specific section)
- Speech vs Text Analytics: 3 Key Differences
- Can Speech Analytics and Text Analytics Overlap
- Why Choose Speech Analytics for Your Business
- 2 FAQs on Analytics Technologies
Speech vs Text Analytics: 3 Key Differences
Here are some of the top differences between speech and text analytics:
Definition
Let’s start with their definitions.
Speech Analytics
Speech analytics is often called interaction analytics. This technology leverages Artificial Intelligence (AI) to extract meaning from audio call recordings.
Its main function includes the analysis of the collected data from spoken words for meaningful customer insight and business intelligence. It also transcribes audio calls to make them searchable.
Several industries, especially call centers, use speech analytics technology to discover valuable customer insight and improve quality management.
Note: Speech and voice analytics is often used interchangeably. However, they have different functions.
Check out our ultimate guide to speech analytics to learn more about the technology.
Text Analytics
Text analytics draws meaningful information from text — instead of phone calls like speech analytics.
Text analytics is extensively used in customer experience management and improvement – across chat, social media, email, etc., to gain business insight.
Basic Functions
The two technologies may sound similar but play distinct roles in business.
Speech Analytics
Speech analytics or interaction analytics uses technologies like Natural Language Processing (NLP), Automatic Speech Recognition (ASR) or automated speech, Artificial lntelligence (AI), and Machine Learning (ML) to carry out multiple functions, including:
- Recording calls
- Transcribing calls
- Spotting keywords and phrases
- Generating predictive analytics
Text Analytics
Text analytics, too, uses technologies like Natural Language Processing (NLP), Natural Language Understanding, and Machine Learning for:
- Language identification
- Syntax parsing
- Sentiment analysis
Benefits
Since speech and text analytics have distinct functions, they offer different benefits to various industries depending on their needs.
Speech Analytics
Here are the exciting benefits of employing speech analytics technology in your business:
- Quality Management and Assurance
Speech analytics helps you monitor every agent interaction in real-time and encourages agents to follow the approved scripts or phrases. In doing so, companies don’t have to worry about legal issues and can effectively maintain high customer satisfaction.
- Improve Agent Coaching and Performance
Since speech analytics uses AI and automation, it lets you listen to every customer call. This ability empowers managers by helping them identify coaching opportunities when they spot well-executed calls for training purposes.
A speech analytics tool also offers managers insight into how each agent performs on calls. This way, they can provide feedback and continue improving sales or customer service agents’ performance with every customer interaction.
- Address Customer Pain Points
Speech analytics lets businesses detect customers’ pain points while identifying actions that can improve customer engagement and satisfaction.
Analytics can also provide valuable insight that improves self-service tools. As a result, customers become more independent and don’t need to contact live agents — who are more expensive to maintain.
- Improve Agent Experience
Speech analytics software automates numerous tasks like data entry, recommending knowledge base data, and more, drastically reducing the burden of multitasking for customer service agents.
This way, speech analytics saves agents from unproductive tasks, boosting employee retention.
Moreover, agents will have more time to perform other core business tasks that help your company grow.
- Drive Customer Satisfaction
Speech analytics has the ability to identify keywords and phrases that you deem important to your business and customers.
This means you can use speech analytics software to keep an eye on calls and flag things when certain phrases are mentioned, as they could require further attention.
It also helps you monitor agents and their use of language and phrases that result in customer dissatisfaction. Monitoring the call language and phrases will ensure that a consistent standard of communication is delivered across your company.
Check out 8 more impressive benefits of speech analytics and if you’re curious, take a look at these 7 practical use cases of speech analytics as well.
- Quality Management and Assurance
Text Analytics
Here are the benefits of using text analytics:
- Analyzes Text Content in Any Language and Format
Text analytics can analyze and acquire valuable insight from any text data across different languages and formats like video, images, or written content.
The format and language compatibility eliminates the time needed to process data into a suitable format before inputting it into a system.
- Improves Experiences for Customers, Employees, and Stakeholders
Text analytics can just as easily be deployed internally as it can be for customer-facing functions. One can use it to analyze written feedback by employees, analyze trends in customer or partner emails/messages, etc.
- Process Unstructured Data Easily
Unstructured data comprises data that’s usually difficult to search, such as audio, video, and social media postings. On the other hand, structured data comprises clearly defined data types with patterns making them searchable. For example, phone numbers, zip codes, etc.
Businesses waste tons of time converting unstructured data into a structured format that standard analytics systems can comprehend.
Text analytics eliminates the need for this step as it can work with both structured and unstructured formats without the need for any conversion.
- Understands the Tone of Textual Content
One tiny social media comment or a Yelp review can challenge your brand’s reputation.
This is where text analytics really shines, as it can sift through structured or unstructured data at scale to detect tone with the help of sentiment analysis, revealing if your customers are happy or not.
This way, you can quickly step in when needed before things get out of hand.
- Analyzes Text Content in Any Language and Format
Now that we’ve distinguished speech and text analytics, let’s check out if there’s ever an overlap between the two.
Can Speech Analytics and Text Analytics Overlap?
You’ll often find an overlap between speech and text analytics in customer experience management.
Why?
The speech analytics tool first converts all speech into text with the help of Large Vocabulary Continuous Speech Recognition (LVCSR) or phonetic systems.
Once the transcription is ready, the analytics solution applies text analytics techniques like sentiment analysis, word frequency analysis, text classification, etc., to draw meaningful, actionable insights from the spoken words.
However, this in no way implies that text analytics can’t work without speech analytics.
Text analytics works for any alphanumeric string shared using email, chat, or social media.
Similarly, you can use speech analytics without employing text analytics.
For example, tracking a specific keyword or phrase mentioned on calls for compliance purposes or to learn what contributes to customer satisfaction.
So which one should you pick for your business?
Even though both technologies do a fine job, most businesses should opt for speech analytics first.
Here’s why:
Why Choose Speech Analytics for Your Business
Speech analytics can help with everything from gathering business intelligence and helping with cost savings to improving customer satisfaction and agent performance.
It’s also easy to deploy in your company — especially if you’ve got the right speech analytics solution by your side, like iovox Insights.
iovox Insights is the ultimate speech analytics solution that lets you transcribe recorded calls to draw business insight and spot trends.
Here are some of the capabilities of iovox’s speech analytics:
Make Every Customer Conversation Searchable
iovox’s speech analytics record and transcribe voice calls that you can read through at a later time. It also makes it easy to search every customer conversation, just like a text document.
As a result, important information is accessible to you at all times and increases transparency across all your customer interactions.
Managers and trainers can use the transcripts as study material for new agents to help them in their initial days.
Monitor Customer Calls with Keywords
If you want to track specific keywords or phrases, you can use the tool's powerful keyword spotter.
It lets you feed the Artificial Intelligence with specific phrases and keywords noteworthy for your business. The AI will automatically identify them from call recordings and track them.
You can also try advanced criteria like a trigger or filter to train the AI.
Measure KPIs to Improve Customer Experience
You can also record your customer calls to track and spot KPIs.
It also offers predictive analytics to predict outcomes based on your preferred metrics and criteria.
Just peek into the iovox dashboard for any actionable insight like total interaction or talk time, average calls per day, and your preferred keywords spotted in voice interactions.
Use these insights to monitor KPIs, helping you improve customer experience and agent performance.
And last but not least, the conversational AI will uncover more opportunities to train itself as it records more and more customer calls over time.
This means you’ll have a rich source of knowledge from every past and present customer interaction to help you increase your sales while improving the overall customer experience.
Got some more questions?
Let’s answer them to clarify things further.
2 FAQs on Analytics Technologies
Here are some analytics related questions and answers:
What is Voice Analytics?
Voice analytics uses voice recognition technology that studies the voice of the customer to analyze and record a spoken conversation. It translates speech to text data and can also identify speaker or customer sentiment by analyzing audio patterns.
How is Text Analytics Different From Text Analysis?
Text analysis is also known as text mining and provides insights of a qualitative nature.
On the other hand, text analytics combines these insights drawn through text mining and turns them into something you can quantify and visualize through charts and reports.
Final Thoughts
Speech and text analytics both have their advantages.
But there’s nothing more powerful than understanding customer needs directly from phone calls.
What customers tell you over voice calls can serve as a rich source of business intelligence, and that’s precisely what speech analytics draws for you.
Searching for a powerful speech analytics solution?
Look no further!
Start using iovox Insights today to discover the most powerful solution to generate actionable insight for your business to help you boost revenue today.
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