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Conversational Intelligence: The Next Big Thing In Customer Experience

2 minutes 30 seconds read

Conversational AI is the technology that makes human-computer conversations emotionally intelligent, and less scripted. It allows AI-led chatbots to interact with people in a human-like manner, thereby keeping this human-computer interaction as natural as possible, yet high on its emotional quotient.

Conversational AI is trained to comprehend and engage in contextual dialogue using Natural Language Processing (NLP) and additional AI algorithms.

Conversational AI is one among a few other new-age technologies that continue to emerge on the scene including augmented intelligence, edge AI, data labeling, and explainable AI.

How Conversational AI helps with better CX? 

Conversational AI uses a combination of natural language processing (NLP), machine learning (ML), speech recognition, natural language understanding (NLU), among other language technologies to process and contextualize voice or text messages and accordingly respond with the most suitable answer. 

Through NLP, the computer can ascertain the intents and entities of the customer on the other end, while identifying statistically significant patterns that it has been trained on. This enables it to learn your business needs and get smarter with time, thus helping a more evolved customer experience. 

Why is it important to invest in Conversational AI?

Gartner had predicted that, by the year 2020, customers would manage 85% of their interactions with businesses without interacting with a human. It’s predicted that in the upcoming decade, basic automation and apps will be replaced with advanced AI technologies with an objective to improve the overall customer experience metric by proactively gauging the customer’s needs and intent and engaging on an emotional level. 

An increased amount of AR and VR innovations across industries are set to be the norm by 2025 as part of an expected customer experience offering. 

“The greatest advantage of having a conversational AI solution is the instant response rate. Answering inquiries within an hour means 7X greater probability of converting over a lead. Clients are bound to discuss a negative encounter than a positive one,” reports AnalyticsInsight.net. 

Image Courtesy: www.kore.ai

Conversational AI in Insurance 

Conversational AI is an ideal addition for service, healthcare, insurance organizations to name a few, as it helps with helping support agents streamline their work, take after-call notes in the CRM system, or complete the missing details that will help by building a seamless customer service system. The technology also helps predict or react to changing call patterns and/or any real-time guidance the agent might require. 

Additionally, customers can first engage in self-service aided by conversational intelligence to save time, improve efficiency and get the desired results sooner. While rebranding Care Health Insurance’s (erstwhile Religare) website and app, Mantra Labs deployed Hitee, their AR-based virtual support that helped with the first-level solution for the customer and in turn, led to higher New Business Conversions by a factor of 10X and an overall drop in customer queries over voice support by 20%.  

2021 Customer Support Trends Report says that inferior customer experience costs companies at least $62 billion annually. 56% of support leaders shared that their current chatbot implementations don’t carry intelligent tools in this report, and customers are increasingly demanding convenience from businesses they interact with. 

Intelligent chatbots make apps simple, and more human to use. Their USP is to create device-agnostic experiences across channels, thus becoming a key factor in driving intelligent customer experiences. 

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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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