Voice analytics tool extracts key conversation insights from speech and elevates the customer experienceEnable Speech Analytics Call Center
Speech analytics software extracts meaningful data from the audio recordings of business calls by recording, transcribing them with the help of speech-to-text features, and finally analyzing the call scripts. Speech analytics solutions promise 100% call coverage of all business calls.
Most customer support agents run into various problems like
Speech analytics precisely helps you pinpoint these challenges, along with uncovering crucial customer insights and competitor intelligence.
APEX Credit management specializes in credit management, debt collection, and debt purchasing services; it got into trouble with debt collection after the pandemic hit.
From the mouth of Steve Mound, Chief Operating Officer (COO) at Apex states;
“With the significant downturn in the economy, and its impact on people’s ability to repay, we realized quite early that we needed to look elsewhere to optimize our processes and boost our collections revenues.”
To overcome this issue, they deployed speech analytics software, and the result;
Overall, speech analytics software achieved its anticipated 12-month return in just 7 months.
Isn’t that amazing?
Do you still need a speech analytics solution for your business?
Let’s list the importance of deploying speech analytics software for your business.
Speech analytics powered by voice analytics software is important in the contact center world. It enables businesses to gain valuable insights from customer interactions.
By analyzing spoken words, tone, sentiment, and other audio cues, voice analytics helps identify patterns, trends, and customer sentiments.
Voice analysis improves;
The software's most essential and fundamental side is converting verbal language into text. Translation helps agents read and understand granular details.
Sentiment analysis in speech analytics software uses natural language processing (NLP) algorithms to analyze spoken words', emotional tone, and sentiments.
For example, a customer who feels ignored on a call doesn’t respond politely and happily. The tone of the customer will automatically change and sound unhappy. The tone and change of words get captured in the sentiment analysis–resulting in a negative score.
Agents performing calls on a day-to-day basis are pressured by targets. Hence, there are high chances of violations, mis-selling, and rude behavior. And fintech, Insurtech, and healthcare are known to be the most notorious.
Edtech surfaced in the last couple of years as another industry where agents make false commitments to increase admissions.
In the customer service industry, voice analytics has played a massive role in identifying customer sentiments, detecting emerging trends, measuring agent performance, and ensuring compliance.
Switching from reactive to proactive selling has been possible due to AI-powered speech analytics solutions. An agent has more knowledge of conversion-driving factors, such as probing, discounts, etc., using voice analytics software.
Auditors and agents often focus on manual methods. For example, QA auditors manually listen to recorded calls(2-3% of all conversations) and score agents based on different parameters. Firstly, the process is time-consuming, and secondly, the chance of bias is high.
Speech analytics AI companies are eliminating this situation by making auditing and feedback a scalable and reliable exercise. Moreover, many contact centers have improved their evaluation efficiency by 5X.
Here’s a quick checklist to understand which product features and brand qualities to vet when purchasing voice analytics software.
Businesses end up losing $62 billion a year because of poor experiences with the brand. But wait, we have some good news too: businesses that use advanced speech analytics solutions to monitor their business calls reduce on an average handle time by 40%, boosting their conversion rate of sales calls by 50%.
This justifies that using voice analytics software like Convin can benefit us to a great extent:
The primary role of a speech analytics solution is to record and transcribe the conversation. The transcription quality of the conversation is high because of Convin’s robust NLP model. High-quality transcription dramatically reduces the manual review time of lengthy conversations.
When discussing quality management, we refer to your agent's performance.
But most importantly, speech analytics solutions add a sense of accountability. Agents know that all their calls are monitored and analyzed for their KPIs. They must always put their best foot forward in every call.
Speech analytics software significantly helps in understanding customers.
Using these insights, you can strategize your efforts and use them for creating call center scripts and messaging that resonate with your customers.
Speech analytics software like Convin possesses the power to display competition information. Your customers are approaching you because your competitors might have already contacted them. And they are evaluating the better software or product for their business, so they will discuss the competitor offerings and pricing to avail a better offer from you.
You can use this opportunity to extract these points and use them for future marketing and sales. As an intelligent habit, it’s always good to remember that all calls, even failed calls, are a form of opportunity.
Assume you pay $3,000 monthly to an auditor in your call center. If your QA team has auditors, you’ll have a monthly expenditure of $15,000.
Instead of hiring more auditors, speech analytics software can help your call center reach 100% audit rates at a cheaper cost.
The investment in automated QA tools gets high returns quickly. Having every conversation audited reduces compliance violations and allows for better agent training.
Speech analytics software helps uncover and accumulate crucial call data from the siloed and unstructured recordings for streamlining the sales process for maximum ROI.
A human ear might miss crucial information and opportunity during a long video or audio call.
And sometimes, agents often zone out while listening to a customer.
But an AI-based speech analytics solution needs to catch up. It records and analyzes 100% of calls for all customer intelligence and opportunities.
And even saves the data in a call library, so you explore the call and its analytical report for future up-selling and cross-selling opportunities.
Your agents don’t have to wait weeks to receive feedback on their calls and then work on improving their performance.
Speech analytics analyzes 100% of all calls post meetings, highlighting the calls requiring special attention for manual review, thus shortening the feedback cycle.
One of the main challenges contact center leaders face is retrieving specific call recordings from siloed and unstructured drives for reviewing and new hires' training.
Speech analytics stores all call recordings under specific topics and allows managers to create playlists of your best call recordings, so you don’t have to spend hours fetching recordings.
How do you know how your customers are feeling on a support call? It’s daily challenging to gather this information. But collecting such nuances about the call can give you an early indication of the chances of a new call or a painful goodbye.
Speech analytics solution runs sentiment analysis by analyzing the call recordings to uncover how your customers feel about your offerings, services, products, etc.
Convin monitors and analyzes 100% of calls automatically based on custom parameters set by your organization. The conversation analysis offers winning behavior identification and last-mile automated agent coaching.
Convin’s call center tool automatically reviews 100% of customer calls, chats, and emails using custom call evaluation forms and spots agent performance challenges and unhappy customer conversations. Through automated quality management, managers and QA generate call scores that help establish coaching needs and staff dissatisfaction.
Convin also allows auditors to manually audit calls, chats, and emails and leave necessary feedback.
With the help of voice analytics and custom-tracking, Convin presents parameters that drive positive and negative outcomes for the business. Spot violations, winning parameters, customer sentiments, and threats to take proactive measures before the customer calls.
Convin’s system automatically generates coaching opportunities after reviewing agent performance. Based on the AI-driven call scores, the platform triggers personalized agent coaching based on the requirement.
Coaching instances are extracted from the top performers' conversations and best practices. This method improves call handling quality and reduces supervisor escalations.
Moreover, with Convin’s peer-to-peer coaching, managers and supervisors can add the best-performing agent’s conversations as a module into Convin’s library and assign it to agents who need further coaching. As a result of Convin’s automated agent coaching, businesses can reduce ramp-up time significantly and focus more on productivity.
CI records, transcribes, and analyzes conversations to generate call insights and transcriptions. The conversation intelligence software discourages manual conversation review and all other non-sales activities by automating notes, action items, and CRM entries.
Access agent performance KPI and customer experience quality criteria to produce consumable role-based reports pinpointing key challenges and opportunities. These reports are available on the Convin platform and periodically mailed to the managers.
At Convin, we understand the customer and call data security important; that’s why we ensure your data is entirely secure and safe in our in-house transcription and NLP engine. We ensure your conversation data security in the following ways:
Spoken words are converted to text using natural language processing and machine learning. Generative artificial intelligence is the newest technology we are using in Convin.
Speech analytics involves using software that employs automatic speech recognition (ASR) and natural language processing (NLP) algorithms to convert spoken words into text, and analyze the text for sentiment, keywords, and other patterns.
While the two are often used synonymously, there’s a difference that everyone should know. Voice analytics refers to the analysis of audio data to extract insights.
Speech analytics, on the other hand, involves the analysis of spoken words and language patterns in audio data.
The 10 best speech analytics software making rounds in 2023 are:
Identify winning trends, eliminate bottlenecks, and improve customer experience with Convin’s speech analytics software.