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CX 2021: How will 5G impact the customer experience future

8 minutes read

5G, the most anticipated wireless network technology, is touted to alter the way people go about their daily lives at home and work. Its USP lies in being a lot faster with a capability to handle more connected devices than the existing 4G LTE network. The fastest 5G networks might be at least 10 times faster than 4G LTE, according to wireless industry trade group GSMA. 

5G signals run over new radio frequencies, needing radios and other equipment on cell towers to be updated. A 5G network can be built using three methods depending on the type of assets of the wireless carrier: low-band network that covers a wide area but is only about 20% faster than 4G; high-band network that boasts of superfast speeds but they don’t travel well, especially through hard surfaces; and mid-band network which balances both speed and coverage. 

Industry trade group GSMA estimates that by the year 2025, the number of 5G connections will reach 1.4 billion – 15 percent of the global total. Additionally, global IoT connections will triple to 25 billion by 2025, while global IoT revenue will quadruple to $1.1 trillion, according to this report published by GSMA. 

Image Source: www.speedtest.net 

How will 5G impact customer experience

Image Source: tmforum.org

The increased reliability, performance, and efficiency of the new spectrum will come as a boon while, at the same time, raise the bar for customer expectations. The intertwining of technology with our daily lives could also mean the proliferation of other technologies, including the Internet of Things (IoT), Augmented and Virtual Reality, Big Data, and Cloud Computing. 

Consumers have regularly cited reliability as their biggest gripe with 4G networks. Over 4 out of 10 (43%) consumers say the internet on their mobile device “cuts in and out sometimes/is not always strong,” according to a PwC survey titled, The Promise of 5G: Consumers Are Intrigued, But Will They Pay? 

According to Deloitte, India’s digital economy will exceed USD 1 trillion by 2025 as a result of increased smartphone usage, rapid internet penetration, and the advancement of mobile broadband and data connectivity. 5G, on the other hand, is likely to be the key catalyst of this expansion.

Video options, however, go beyond content consumption unto live support, too. For consumer-facing companies, live video support will open doors to better customer service, a crucial aspect of a good customer experience. A 5,000-person survey done by Oracle found that 75% of its respondents recognize the value and efficiency of voice and video chat. They also look forward to first-call resolutions.

Even for agents providing email support, a quick video explaining steps looks like a more efficient way to give a resolution instead of emails with a step-by-step guide, an aspect that companies can consider for seamless processes. 

The GSM Association, an industry organization representing mobile network operators around the world, says the number of IoT connections worldwide will grow manifold between 2019 and 2025, to over 25 billion.

AR/VR capabilities and 5G

5G’s advent is a likely measure to “revolutionize” tech, especially through AR and VR. The high speed and low latency of 5G might imply that processing power could be moved to the cloud thereby allowing for more widespread use of VR/AR technology.

AR/VR technologies powered by high-speed 5G could help boost interest in newer concepts like virtual stores and the use of AR to experience products in their homes, or makeup on one’s face, and more. The combination of high speed and minimal lag is perfect for both VR and AR, which has a lot in store for the gaming community too. According to Nielsen’s study Augmented Retail: The New Consumer Reality released in 2019, many people are willing to use VR/AR to check out products.

That said, true VR/AR growth from 5G is difficult to predict since it also depends on the pace of customer and brand adoption. Nevertheless, its use in customer experiences will be interesting to watch in the coming years.

Big data processing power and 5G 

AI and big data analytics are currently in use to identify customer patterns in order to personalize CX. 5G’s capabilities are likely to raise the bar on the volume of data companies collect and increase the pace at which AI can process it. 

Faster speeds and lower latency lend themselves to an influx as they prepare for the next wave of automation and AI-backed technologies. Businesses will begin relying on mobile networks more frequently than before while streamlining core operations.

5G latency is expected to be faster than human visual processing, thus making it possible to control devices remotely effectively, in (almost) real-time. 

Insurance and 5G

Image Source: www.capgemini.com 

Insurance agencies rely on network carriers to share data for selling policies. With larger mounds of data widely available through 5G, agencies will be at an advantage to leverage more data without having to host or own it themselves. This means greater efficiency to navigate through data in a simpler manner.

The Internet of Things (IoT) has seemingly benefitted the auto insurance industry the most. The data is easier to generate, which includes the policyholder’s car details, mileage, speed, and overall usage of the car depending on each drive. 

https://www.youtube.com/watch?v=n5wkY3gQYiU

With IoT, a policyholder’s car isn’t the only thing that could help generate data. In case of a home fire, an oven could be used to collect data for requisite claim information. Likewise, a drone could share accurate location data. 

Overall, agriculture, manufacturing, logistics, financial services will all benefit from lower latency, high speeds, thus ensuring an immersive experience for all. 

Dogan Kaleli, CEO at Stere.io, Founder at Nion, wrote in ‘Why 5G is a Major Game-changer for the #Insurance Industry?‘ that 5G along with revolutionary technologies will mark the beginning of the 4th industrial revolution or the flywheel effect.

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When Data Meets the Heart: A Tale of Sentiments and Science

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Do you think technology will advance to a point where people rely on it for deeper emotional connections, perhaps even finding companionship? Just like in the movie Her, where a man falls for an AI, we all thought it was science fiction. But it seems we’re closer to that reality than we might have imagined. Now, it’s not just about crunching numbers. Technology is evolving every day, becoming so advanced that it’s learning to interpret human emotions and reactions. This is the core of sentiment analysis, where data meets emotions, and technology helps us make sense of human feelings in ways that were once only imaginable.

Is Data Science the Key to Unlocking Sentiment Analysis?

Sentiment analysis is more than just gauging emotions in text; it’s a powerful application of data science that transforms chaotic data into actionable insights. Data science deciphers human feelings hidden in reviews, tweets, and comments, enabling AI to capture not just whether sentiments are positive or negative but also the nuances of emotional expression. With the ongoing evolution in data science, sentiment analysis is moving beyond basic detection to uncover deeper emotional insights, allowing businesses to truly understand their customer’s sentiments. This capability empowers organizations to anticipate customer behavior and make informed decisions in a data-driven world.

According to Forbes, 80% of the world’s data is unstructured, like blog posts, reviews, and customer feedback. Sentiment analysis helps companies make sense of this unorganized heap using data analytics, turning it into actionable insights. Tools like Python libraries for sentiment analysis and AI models help refine this process further, offering businesses more profound insights into customer behavior.

How Does Sentiment Analysis Work?

Imagine you’ve just posted a review online: “This phone has a great camera, but the battery life is terrible.” While a human can quickly spot that you love the camera but hate the battery, AI needs to go a step further by:

  1. Text Preprocessing: Breaking the sentence down into words (tokens), removing stop words (like “the” and “has”), and normalizing the text.
  2. Natural Language Processing (NLP): This is where the AI engine learns the context of each word. It identifies if the sentiment is positive (great camera) or negative (terrible battery life).
  1. Machine Learning Models: These models classify the sentiment of the text. With more data science applications, the models become better at predicting human emotions.

Why Does Sentiment Analysis Matter?

In a world where emotions drive decisions, sentiment analysis helps businesses, governments, and even individuals make better decisions. Whether it’s reading reviews, understanding customer feedback, or gauging public opinion on social media, sentiment analysis tells us how people feel.

Beyond the Text: How Data Science Decodes Emotional Intelligence

What if Data science could detect more than just positive or negative feelings? What if it could understand sarcasm, context, and complex emotions like nostalgia or regret? The future of sentiment analysis is heading towards these intricate feelings, making it possible to “read between the lines”. With advancements in data science and machine learning, sentiment analysis is set to dive deeper into human emotions, potentially offering an unprecedented understanding of how we feel.

Real-World Applications

  • Customer Service: Have you ever left a review or complaint on a company’s Twitter? Chances are AI detected your dissatisfaction before a human even read it.
  • Healthcare: Doctors and mental health professionals are using sentiment analysis to detect early signs of depression or anxiety based on patient communication.
  • Politics: Predicting election outcomes? Analyzing public sentiment towards political candidates can be more accurate than traditional polls.

The Road Ahead: Can Data Science Fully Understand Us?

While today’s data science techniques are great at reading general sentiment from text, we’re not yet at the stage where machines can truly “understand” emotions. However, advancements in data science continue to refine how we interpret human sentiment. Techniques like sentiment mining and sentiment classifier are being used to recognize the subtle emotional cues. Perhaps one day, the power of data science will allow us to decode human emotions with such precision that it fundamentally changes the way we interact with data, bringing emotional insights into our daily lives.

Feeling curious? Explore how Mantra Labs is shaping the future with cutting-edge data science techniques and solutions that can read the world’s emotions—literally.

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