Products are constantly becoming better. Or at least that’s what “people” developing them like to believe. I am “people.” And being a product person, I understand that as markets continue to evolve, product alone is no longer a powerful differentiator. Experience is. It’s a vital cog to turn prospects into paying customers and increase the longevity of existing customers. So, it’s non-negotiable to keep a track of how customers feel about your products and brand.
This is where sentiment analysis comes into play. How? Continue reading to find out!
Winning the Customer Experience (CX) Battle with Sentiment Analysis
Before we jump the gun and talk about how effective sentiment analysis can help you score a CX home run, let us quickly go through what it is.
Simply put, sentiment analysis, also called opinion mining, is a natural language processing (NLP) technique that classifies data as positive, negative, or neutral. It is performed on text-based data like customer feedback and conversations to help businesses gauge their brand and product reputation while also shedding light on customer needs.
But, why is it important?
To explain that, first, I need to tell you about the time sentiment analysis missed by a mile.
In 2017, Indigo—the airline giant—misplaced the baggage of one of its passengers. The disgruntled customer vented his frustration on Twitter with a sarcastic tweet, thanking them.
One misfire seriously tattered Indigo's reputation piece by piece.
Now let’s look at another example where sentiment analysis hit the bull's eye.
What started as a positive tweet is actually a complaint. Sentiment analysis can be crucial when dealing with dissatisfied customers. And JetBlue Airline’s correct sentiment analysis addressed it with élan and circumvented an internet gaffe.
Sentiment analysis has moved beyond being just a high-tech whim and is quickly becoming an indispensable tool for all forward-thinking companies. By incorporating sentiment analysis into their existing systems and analytics, organizations glean new and valuable insights into the needs of customers. Additionally, it empowers teams to take CX and CSAT scores at their zenith by not just working faster but also with greater accuracy.
5 Practical Use Cases of Sentiment Analysis
Sentiment analysis gives you a reality check of your brand’s reputation, and its benefits are abundant.
1. Predict and Curtail Escalations
According to Forbes, 83% of companies believe it’s important to make customers happy and also experience growing revenue.
One prerequisite to keep customers happy is constantly monitoring their conversations. That empowers support engineers to hop in at the right moment and, if need be, diffuse a potential bomb before it explodes. Sentiment analysis makes this possible.
In addition to proactive support, sentiment analysis can also help you better manage incoming tickets to keep escalations at bay. It leverages NLU to analyze the available case data in real-time and flag cases where customers are frustrated or disgruntled. Thereafter, agents can prioritize the tickets and curtail escalations by rendering the most relevant answer to their problem.
2. Streamline Ticket Triaging and Expedite Case Resolution
More often than not, users only raise a ticket after all self-service channels have failed them. So odds are, when they contact you, they’re looking for instant resolutions. But since organizations receive multiple tickets every day, picking them on the basis of inky, pinky, ponky could spell disaster. This is where customer sentiment analysis dazzles.
It helps firms pick support tickets that have a higher chance of escalating as opposed to others. Once that is sorted, the ticket is directed to the best agent right off the bat based on their expertise and case history. As a result, escalations are kept at bay and SLA requirements are adhered to. Win-win!
3. Enable Product Development
The key to unlocking a flywheel of success is incorporating VoC-led product growth. But to do that, organizations need technology that simplifies deciphering customer needs from their feedback. Here again, sentiment analysis comes into play.
To start with, it enables firms to identify common pain points. These insights can help galvanize vital product tweaks. And, that’s what differentiates trendsetters from laggards. For instance, if multiple customers face a similar recurring problem during software updates, the product team can immediately get the ball rolling and fix the issue.
4. Improve Agent Training
One of the most important use cases of sentiment analysis is its utility as a performance indicator. It provides a clear view of customer satisfaction, agent by agent. Managers can use these insights to provide suitable training sessions and improve agent performance.
For instance, Manager Z receives a complaint regarding agent X’s behavior from a disgruntled customer. However, agent X has always been one of the star performers. Mr. Z decides to delve deeper into the matter. Turns out, X often used to rush customers or cut corners to close the ticket quickly. Now that the cat is out of the bag, X is undergoing training to improve their customer handling skills.
5. Propels Personalization
According to Epsilon’s research, 80% of consumers are more likely to purchase when brands offer a personalized experience.
Delivering the kind of personalized experience they seek can be challenging. Yet again, real AI and sentiment analysis come to your rescue. They actively infer the user’s mood from a conversation. If a user seems dissatisfied with the experience, enterprises can analyze available support ticket data to detect the tone in real time. Leveraging these insights, the agents can empathize and personalize accordingly. The result? Fewer service catastrophes and happier customers.
Jumpstart Your Journey To Deliver Unmatched CX with Customer Sentiment Analysis
In today’s fast-paced world, where customers are always on the brink to churn, real-time sentiment analysis ensures organizations deliver experiences that encourage loyalty.
Interested to learn more about the enabling role cognitive technology and NLP can play in real-time sentiment analysis? Read this ebook to explore its business applications - especially for the customer service vertical and check out AppExchange to find solutions to get you started.
About the author: Vishal Sharma is the CTO of SearchUnify. With close to 15 years of experience in deploying enterprise search solutions and working on support optimization models, which eventually ensued the cognitive search brainwave, he is the face of SearchUnify, a unified cognitive search platform. As the product’s architect, he is the central point for technology innovation, from defining the solution’s product vision to enabling leading high-tech customers to save millions of dollars in case deflection and sales cycle acceleration.
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