10 minute read
When you’re setting up a call center phone system, ‘call recording’ and ‘live call listening’ are two important prerequisites. These features allow managers and trainers to listen to calls and voice and suggest improvements based on their analysis of the conversation. But, you can manually analyze only so many calls.
Manual analysis is slow and it may be biased. And, you get a partial view of what your audience wants. It is also difficult to perform when managers are overseeing remote teams.
That raises the question — why limit yourself to a small sample when you can get a full perspective with speech analytics software?
A speech analytics call center gives you near real-time insights on improving customer interactions across channels. It automates the process to make it faster, able to handle larger call volumes and more reliable. Let’s dive deeper into speech analytics and how it benefits call centers.
What is call center speech analytics?
Speech analytics refers to the automated analysis of conversations between customer service representatives and customers using Machine Learning (ML) and Natural Language Processing (NLP). The results of this analysis can be used in many ways such as for quality control and training or to optimize operations.
It works by identifying words and patterns from recorded and transcribed conversations to analyze whether the customer sentiment expressed is positive, negative or neutral. Further, it assesses the keywords identified against the context of the conversation to evaluate call quality and monitor agent performance.
The automated process runs on every call made and received by your call center. It can also be used to draw similar inferences from communication via other channels such as text messaging, emails or interaction with chatbots. When you’re comparing speech analytics tools, this feature becomes important, especially in today’s age of omnichannel business communication.
What Speech Analytics can do for your Call Center
Empowered with speech analytics, call centers can make data-driven decisions to help stand out for their customer experience. Some of the key ways speech analytics can help your call center are:
Identifying conversation themes
Firstly, speech analytics helps understand what customers want by identifying themes that recur across conversations. Let’s take the example of a tea retailer. There are so many varieties, flavors, and packaging options to explore – how do you choose what to focus on?
Ideally, this must be based on what your customers want. Speech analytics helps identify the focal points that matter by highlighting common themes. If a majority of your customers talk about tea bags, this may be a vertical worth exploring.
Similarly, it helps you identify areas that need improvement. For example, if you notice a growing number of customers complaining about late deliveries, you may need a new logistics partner or find a better way to approximate delivery timelines when orders are being placed.
Assessing how customers feel about your brand/product/service
Speech analytics gives you a clear perspective on how customers feel about your brand and the products/services offered. By analyzing keywords against the context of the conversation, each conversation is scored from -1 to 1 in terms of the sentiment expressed.
Conversations where a negative emotion is expressed are scored from -1 to 0 while conversations with a positive emotion are scored from 0 to 1 with 0 being the score for a neutral emotion. Here are a few examples:
- Positive sentiment: I loved the rose-flavored tea
- Neutral sentiment: The product matched the online description
- Negative sentiment: I opened the package to find 2 cups broken
Speech analytics tools like Lettria that use advanced AI can go beyond simple statements to extract sentiments from complex statements with slang or sarcastic notes. Let’s say a customer said, “It’s so good to speak to you, I’ve been on hold for only 20 minutes.” Though the word ‘good’ has a positive inference, the context it has been used is sarcastic and hence the statement will be graded as a negative sentiment.
Understanding your customer’s sentiments can enable your customer service agents to respond appropriately and take measures to improve the experience. Imagine the customer’s frustration in the above example if the agent responded by saying, “Nice to speak to you too”!
Using natural language processing, it is also possible to automatically enrich your CRM using the feedback you receive from your customers. Learn more about CRM enrichment using NLP here.
Measure call center agent performance
Just as speech analysis tools evaluate the choice of words being used by customers, they do the same to assess the sentiments being expressed by your call center agents. Do they sound happy, sad, angry or worried?
Lettria does the monitoring and uses deep learning to categorize sentiments into 28 such emotional values. This data can prove critical for understanding how your customers are being treated and the impression being formed about your brand. You may have a great product but if your agents sound irritated on call, your customers aren’t likely to stay loyal to the brand.
Mitigate fraud and compliance
Using speech analytics also helps identify instances where standard operating procedures are bypassed leading to fraud and compliance risks. For example, having an agent ask the customer for an OTP could put your company at risk of financial fraud. The faster you can identify such rogue agents, the earlier you can address the issue.
Similarly, sending customers emails without their consent can put your brand at risk of having to pay fines and being blacklisted as spam. If a customer calls to unsubscribe from your mailing list, speech analytics can highlight the conversation so that appropriate action is taken to mitigate such risks.
Benefits of Speech Analytics for Call Centers
Call centers across industries can experience a range of benefits by using speech analytics. This includes:
Understand customer needs better
Rather than relying on a small sample of calls that can be manually analyzed, speech analytics assesses each and every call to give you a more accurate perspective on how your customers feel about the brand and what they want.
For example, your managers may have assessed 10 calls and found that all these conversations were centered around opening a new store in India. But, with automated speech analytics you may realize that the remaining 90 calls were from customers wanting a new store in Germany. Similarly, it helps assess what customers like and dislike the most about your service and increase sales.
Improve conversion rates
By helping you understand customer sentiments, speech analysis empowers agents to personalize interactions and build a better rapport with the customers. They can then leverage this rapport to cross-sell or upsell products and services.
It helps increase the chances of conversion as well as the overall customer experience. The software can also pinpoint keywords and responses that work well with specific customer demographics.
Improve resolution rate
If your agent misreads a situation and responds to a sarcastic statement with a joke rather than empathy, the customer is likely to get more irritated. Understanding the sentiment behind a customer’s call can put agents on the same page as them and helps avoid such instances.
The customer service agent is better equipped to respond to situations correctly and resolve their issue on the first call. Ultimately, a higher resolution rate reduces the overall call volume and gives your agents more time to spend on each call.
Reduce customer churn
There will always be customers who switch to competitors and unsubscribe from your mailing lists. While this is not completely avoidable, understanding the reasons behind this can help reduce customer churn. Speech analytics helps highlight keywords and themes that are causes of concern with respect to customer engagement and satisfaction. For example, if you see a pattern emerge where the words ‘cancel’ and ‘late delivery’ are used together, improving your supply chain may help keep customers from leaving and retain their loyalty.
Spot industry trends
Just as the products offered by your company need to keep up with market trends, so does your customer service team. Speech analytics helps identify trends in customer expectations to keep your call center in tune with the industry.
For instance, a speech analysis tool may highlight a growing number of conversations where customers of a flat-pack furniture brand ask for video tutorials of product assembly. Further study may identify an increase in the number of customers seeking self-service tools. Armed with this data you can work on developing such tools and keep your customers happy.
We’ve already talked about how speech analysis helps improve call resolution and, in turn, makes call center agents more productive. In addition, it also boosts efficiency and productivity for managers.
Managers can now tell which agents require more hand-holding and which agents are doing well on their own without having to listen in to calls being made by everyone. This also helps avoid micromanagement and lets managers use their time more productively.
Track agent performance without bias
One of the biggest issues with manually assessing agent service is having a biased opinion. For example, a manager may assume that an agent is taking longer to resolve an issue simply because he is speaking to an elderly customer. However, in truth, it may be because of a language barrier.
Automated speech analytics bypasses such biases completely and helps track agent performance according to standardized KPIs. It lets managers know at a glance how well each agent is doing and helps spot deviations from call scripts that work as well as those that don’t. This insight can be used to alter scripts and make them more effective.
Ease quality management
Every call center is constantly working towards improving the level of customer service offered. This is one of the areas where speech analysis plays a pivotal role. It helps assess how agents are doing and what scripts can be followed as is and what scripts are being frequently changed.
Here’s a very simple example, let’s say the city changed the name of a street but the call center script still lists addresses with the old street name. With speech analysis, managers will be able to identify company agents having to make this deviation from the script. They can then update the script to maintain uniformity across all communication.
Rather than take a hit-and-try approach towards introducing new customer service features or base decisions on a partial view of the customer’s needs, speech analytics gives you access to information that can help make wiser, more strategic decisions.
You are able to invest in developing services that are more likely to be profitable. You can also spot industry trends and shifts in consumer behavior in advance. This keeps you prepared and lowers the risk of losses.
Speech Analytics Call Center Solutions
Given the important contributions speech analysis can make to the everyday functioning and overall quality standards of a call center, it isn’t surprising to note that there are many tools available for speech analytics. They vary in terms of not only pricing but also the scope of analytics provided, processing speed, accuracy and ease of operations. If you’re looking for speech analytics tools for your call center, here are the top 3 best options you should consider.
Lettria is the leading speech analytics call center solution provider. It uses a platform-based approach with 15 pre-trained and customizable multilingual models. Lettria’s low-code customizable nature makes it capable of delivering advanced sentiment analysis with high levels of accuracy.
This is one of the reasons for its popularity. The second is the way Lettria analyzes speech. It goes beyond the basic positive, neutral and negative emotions to grade sentiments according to 28 emotional values. Lettria breaks the analysis into 2 steps.
Step 1: It identifies the adjectives and adverbs within a statement to detect a base sentiment. It is then graded from -1 to 1 according to the emotional elements or sentence-level comparisons.
Step 2: This brings us to step 2 where the AI processes the context of the statement. Thus, it not only evaluates the statement's polarity but also determines the emotional value of the statement.
Calabrio is a workforce performance software that uses Artificial Intelligence to understand the needs of a customer and anticipate demands based on interactions with your contact center. It brings all contact center data to one interface so that everyone is connected. Further, it provides analytical data that aids in taking measures required to meet customer expectations and increase agent engagement.
The CallMiner platform for speech analytics helps capture, analyze and understand the emotions behind what the customer is saying. It uses AI-powered speech analytics technology to extract data from telephone conversations as well as emails, chats and social media interactions, classify it as positive or negative and deliver insightful reports.
Boost Your Call Center Performance with Speech Analytics Today
According to a McKinsey paper, speech analytics can help call centers save up to 30% in terms of their costs and improve customer satisfaction scores by at least 10%. Speech analysis benefits apply to call centers across all industries and are especially effective for cloud contact centers.
With AI tools like Lettria, you can gain insights into customer needs that are unavailable elsewhere and identify opportunities to improve agent performance, operational efficiency and more. Explore the platform today and see how it can benefit your organization’s call center.