Category: CX / Customer Experience

Bringing the Vision of unified Customer Experience (CX) to Fruition: Shining a Spotlight on Sprinklr | Blog

After previously zooming the lens in on how Salesforce has helped global enterprises to provide a holistic customer experience approach through its integrated set of offerings, this time we focus on another CX tech vendor, Sprinklr, that offers a unique category of enterprise software, which it terms as “Unified Customer Experience Management”.

Unified Customer Experience Management (Unified-CXM) empowers all customer-facing teams in an enterprise, from support, to sales and marketing, in order to then collaborate effectively, communicate across digital channels, and leverage an artificial intelligence (AI)-powered platform to deliver consistent and cohesive customer experiences at scale. In this blog, we shine a spotlight on Sprinklr and its evolution. Reach out to discuss this topic in depth.

Today’s consumers interact with brands across a range of touchpoints. Naturally, the modern customer journey is a complex and multi-faceted one, often involving a combination of channels and modalities.

Enterprises want a comprehensive view of these interactions—from marketing, through sales, to post-sales support—to maintain effective customer engagement across the lifecycle.

However, most enterprises still rely on legacy customer relationship management (CRM) systems that are not tightly integrated with customer facing tools and applications, which becomes a hindrance to delivering real-time personalized engagement. This leads to customer dissatisfaction and a loss of trust in many cases.

Sprinklr’s Unified-CXM platform is designed to address these challenges by helping enterprises eliminate silos, access and analyse unstructured digital data and leverage AI to generate a unified view of each customer’s journey. This approach allows customer facing teams to better assist customers, share knowledge, and collaborate, ultimately enhancing the overall customer experience.

Sprinklr’s platform is comprised of four product suites—Service, Marketing, Insights, and Social—which when brought together support enterprises in better managing the end-to-end customer journey.

These suites operate on a single, unified AI-powered platform, enabling enterprises to streamline customer interactions across multiple touchpoints. Each product suite offers distinct capabilities, which will be examined in more detail below.

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(Image courtesy: Sprinklr)

Sprinklr’s product suite:

With the rise of digital channels such as Instagram, TikTok, and WhatsApp, among others; customers are now more connected and empowered than ever before, offering continuous real-time feedback to express their concerns or frustrations.

This shift makes personalized and real-time customer engagement crucial for brands. Sprinklr’s product suite addresses these evolving needs, offering enterprises solutions to enhance engagement, gain insights into customer sentiment, and take proactive measures when necessary. Each suite provides a range of solutions that enterprises can implement either individually or as a bundle –

  • Sprinklr Social – This suite offers AI-powered tools to unify social media publishing and engagement across more than 30 channels. It enables enterprises to manage and analyze social media content, monitor conversations, and improve customer interactions. Key products include:
    • Social Publishing & Engagement: Supports teams with digital asset management, editorial calendaring, and omnichannel publishing
    • Employee Advocacy: Enables organizations to leverage employees in brand promotion, boosting awareness, and generating leads
  • Sprinklr Insights – Sprinklr Insights unifies data across customers, competition, as well as the industry, from both traditional and digital channels, allowing enterprises to monitor customer sentiment and industry trends in real time Key products include:
  • Social Listening: Which enables enterprises to understand unstructured data from 15+ digital channels, as well as automatically identify trends/anomalies to act upon
  • Competitive Insights & Benchmarking: Which enables enterprises to benchmark their social performance against competition and monitor influencers across eight social channels
  • Sprinklr Marketing – Focused on planning, executing, and optimizing marketing campaigns, this suite enables enterprises to manage content creation, collaboration, and performance tracking across multiple channels. Key products include:
  • Campaign Planning & Content: Marketing which has capabilities like brand governance, cross-channel publishing/distribution, briefing, copy assistance and localization

Ads Comment Moderation: Which aids enterprises in managing comments on paid posts at scale, brands can moderate testimonials, product feedback, and urgent customer service queries

  • Sprinklr Service – Sprinklr’s Service Suite is a comprehensive Contact Center as a Service (CCaaS) solution for managing customer support across voice and digital channels. It integrates AI-driven automation, self-service, and agent assistance tools, in order to provide customer care at scale through voice, messaging, social media, and other digital platforms. Products within this suite include –
  • Sprinklr Voice: For managing inbound and outbound interactions with capabilities such as Interactive Voice Response (IVR), Automatic Call Distribution (ACD), Agent Assist, AI-driven nudges and predictive dialers, and omnichannel workflows
  • Conversational AI chat and voice bot solution: Which comes with a use case library and industry-specific/intent-based bot workflows, as well as Workforce Management & Quality management for contact center managers

Some of Sprinklr’s strategic differentiators include:

  • Unified architecture: Sprinklr’s single-codebase platform allows enterprises to seamlessly integrate channels, unify customer journeys, and accelerate innovation through a “build once, deploy everywhere” model
  • Advanced listening: The platform captures unstructured data from 450 million daily conversations, providing comprehensive social listening and analytics
  • Purpose-driven AI: While it has its proprietary AI models which are industry-trained, it also allows enterprises to integrate other industry-leading generative AI (gen AI) models, which it calls Sprinklr AI+. Sprinklr AI+ leverages generative AI in all four Sprinklr product suites and is powered by integrations with OpenAI, Google Cloud’s Vertex AI and Microsoft Azure OpenAI Service
  • Scalable enterprise-grade platform: This platform is designed to meet industry security standards, including ISO 27001, HIPAA, PCI-DSS, and SOC compliance, making it a scalable solution for large enterprises

Powered by Sprinklr AI+, it has also recently launched Sprinklr Digital Twin, a new AI technology designed to enable enterprises to build and deploy autonomous and intelligent AI applications, that can mirror and enhance the capabilities of customer-facing teams.

While Sprinklr’s service suite has become an established offering, the company’s broader vision remains becoming the core operating system for all front-office teams supporting all conversations that an enterprise can have with its customers.

If you found this blog interesting, check out our blog focusing on Building Purpose-Driven Generative AI (gen AI) – Why We All Have A Role To Play In The Future Success Of The Gen AI Ecosystem  | Blog – Everest Group (everestgrp.com), which delves deeper into the topic of artificial intelligence.

If you have any questions, have further interest as we continue to investigate best in-class vendors to support your CX transformation journey, or would like to reach out to discuss these topics in more depth, please contact Anubhav Das and Sharang Sharma.

Retail Media Networks Are Making Millions—Here’s How You Can Too! | Blog

Retail media networks (RMNs) are transforming the way retailers and consumer packaged goods (CPG) brands collaborate in the digital advertising space. Retailers are now seizing the opportunity to monetize their digital assets, while brands are eager to invest in retail media networks (RMNs) to engage consumers directly at the point of sale. 

Just this year, Lowe’s rebranded its network with a simplified name—Lowe’s Media Network—and expanded its channels to include email, in-store audio, paid search, and app-based ads. 

Meanwhile, Macy’s integrated artificial intelligence (AI)-powered technologies to its RMN, to improve post-purchase engagement through its partnership with Rokt. Similarly, Albertsons Media Collective is working with commerce media platform Criteo to extend its in-store media offerings for advertisers. 

With so much evolution in the sector, our analysts have looked into what the future holds for a space that is currently incredibly lucrative… 

Reach out to discuss this topic in depth. 

What exactly does all this mean, and how are brands and retailers making money from it? 

A retail media network (RMN) is an advertising platform run by a retailer , allowing brands to purchase ad space on its website, app, and other digital properties. The key appeal is the retailer’s use of first-party customer data, enabling precise targeting, which is often more effective than traditional digital marketing channels. 

For brands, RMNs are a goldmine. They offer a way to target consumers with highly relevant ads while they’re actively shopping, increasing the likelihood of a purchase and boosting return on ad spend (ROAS). This combination of contextual relevance, first-party data, and seamless integration with the shopping experience, gives RMNs a strong edge over traditional marketing platforms. 

Why are RMNs growing while traditional digital marketing still exists? 

There are several reasons behind the rise of retail media networks: 

  • Privacy-First Advertising: With regulations like general data protection regulation (GDPR) and the phase-out of third-party cookies, RMNs provide a privacy-compliant way for brands to connect with their audiences using first-party data 
  • Seamless Shopping Integration: RMN ads appear while consumers are already in buying mode—unlike traditional ads that interrupt browsing or social media activities 
  • Enhanced Measurement and Attribution: RMNs offer closed-loop attribution, enabling brands to see exactly how their ads drive purchases, providing transparent and accurate ad performance data 
  • Retailer Competitive Advantage: Retailers with strong loyalty programs and large online presences control valuable first-party data, giving them an edge in the advertising space 

If it’s so amazing, why isn’t every retailer running their own RMN? 

Despite the many benefits, only top-tier retailers like Amazon, Walmart, Target, and Kroger have been able to successfully manage profitable RMNs. Even for retailers with large customer bases, several challenges arise: 

  • Data Privacy and Security: Handling large volumes of first-party data comes with immense responsibility. Retailers must adhere to regulations like GDPR and the Californian Consumer Privacy Act (CCPA), while avoiding breaches that could harm consumer trust 
  • Ad Fraud: Like any digital advertising channel, RMNs are vulnerable to fraud. Robust fraud detection tools are essential to maintain advertiser trust and campaign performance 
  • Balancing Ads and User Experience: Too many ads can disrupt user experience, so retailers need to strike a careful balance between monetizing traffic and maintaining a smooth shopping journey 
  • Technological Infrastructure: Building a scalable RMN requires significant investment. Not all retailers have the technology stack or resources to develop such platforms without external support 

 Can outsourcing help? Where and how? 

For retailers lacking in-house expertise, outsourcing can be a powerful solution. Case in point, Macy’s partnership with Rokt, which brought in AI capabilities without the need for internal development. 

Key areas where outsourcing can help include: 

  • Technology Development: Building the right tech stack can be time-consuming and expensive. By outsourcing to technology vendors or global system integrators (GSIs), retailers can launch their RMNs more efficiently 
  • Ad Operations: Managing ad inventory, targeting, and performance measurement can be handled by specialists, allowing retailers to focus on their core operations 
  • Data Management: Safeguarding and analyzing first-party data requires expertise in privacy and compliance, which can be outsourced to trusted partners 

Global System Integrators (GSIs) are instrumental in helping retailers scale their RMNs by providing the technical backbone and operational expertise required to do so. 

Retailers can also outsource day-to-day operational tasks, such as managing advertiser partnerships or designing creative ad formats. This allows them to scale faster without having to build large internal teams. 

The future of retail media networks: 

As RMNs evolve, they represent one of the most exciting opportunities for retailers and CPG brands to enhance customer engagement and drive sales at the point of purchase. Below are key considerations for retailers and brands: 

  • People: 
    • Tech-driven upskilling: Technology vendors and service providers will play a key role in upskilling the teams at retailers and brands, helping them deepen their technical and functional understanding of RMNs and its evolving trends 
    • Need for deeper partnerships: As the number of RMNs grows, brands with stronger connections with retailers will gain a competitive edge by securing better visibility and premium placements within retailers’ advertising properties  
  • Process: 
    • Customer Experience : Retailers will prioritize non-intrusive ads that enhance the customer journey. RMNs will shift from basic product placements to immersive, personalized, data-driven ads 
    • Data management and privacy: As concerns over data privacy grows, transparency in data collection and usage will become crucial. Retailers and brands will need to communicate clearly about how consumer data is handled, building trust, and fostering acceptance of ads in retail environments 
  • Technology: 
    • Closed-loop reporting: Brands will demand closed-loop reporting that is detailed, unambiguous, near real-time, and continuously accessible, providing insights that drive better marketing outcomes 
    • Integration and cybersecurity: Tech solutions must integrate ads seamlessly into retail environments, ensuring consistent delivery across online, in-store, and mobile platforms, while prioritizing cybersecurity and data protection 

In a nutshell, the future of RMNs will see brands and retailers working together more strategically, making every touchpoint a moment to connect and convert. 

Technology and service providers will act as key partners, connecting advanced RMN technologies with retailers and brands. They will help teams understand and utilize these tools effectively, enabling optimized targeting and seamless integration. 

We are actively tracking the evolution of retail media networks and their impact on the future of the Retail And CPG sector. To discuss the latest trends and their implications for CPG brands, retailers, technology vendors, and service providers, feel free to reach out to Manu Aggarwal, Abhilasha Sharma, or Aakash Verma. 

If you found this blog interesting, check out our blog focusing on Composable Commerce: For Composing The Best-of-Breed Customer Experience, which delves deeper into another topic worked on by our HLS service line. 

Join us at NRF ’25 to connect with our retail and CPG leaders. We look forward to exploring the insights and strategies shaping the industry. 

For more information regarding NRF ‘25, visit website and their LinkedIn page

Addressing the Doom Loops in Customer Service: An Opportunity of Market Differentiation for Financial Institutions | Blog

On August 12th, 2024, the Biden administration launched a new initiative – Time is Money – to crack down on all the ways that enterprises try to avoid customer queries and issue resolution by trapping them in arduous cycles of automated communication (doom loops), as well as not connecting them directly to a human agent.

Fast forward a few months and the administration has taken an unfavorable view of the situation and since stated that companies have established these cumbersome processes by design, to deter consumers from getting their monetary due (in the form of refunds or subscription cancelation), along with adding to their daily frustration, as inevitably they then profit from customers ultimately giving up.

This blog explores the concept of doom loops and analyses customer pain points and their impact on brand loyalty and regulatory compliance. Additionally, it provides strategic recommendations for enterprises on how to address these issues, particularly in their outsourcing contracts.

Reach out to us to discuss this topic further with our expert analysts.

Introduction: from interactive voice response (IVR) to chatbots

Doom loops refer to the frustrating and often endless cycles customers experience when trying to resolve issues through automated systems. The concept of doom loops in customer service has its roots in the early days of IVR systems, which were widely adopted by companies in the 1980s and 1990s.

IVR systems allowed businesses to handle a large volume of customer calls by automating the initial stages of interaction. However, these systems often became a source of frustration for customers who found themselves trapped in an endless cycle of menu options, unable to reach a human representative or resolve their issues.

As technology advanced, chatbots emerged as a new solution, promising to enhance customer service by providing instant, 24/7 support. However, these chatbots have inherited many of the same issues that plagued IVR systems. Customers often find themselves in a similar doom loop, where the chatbot fails to understand their query, provides inaccurate information, or directs them through a series of irrelevant responses before they can reach a human agent. This problem is particularly pronounced in industry verticals such as banking and financial services where customer inquiries often involve sensitive and intricate issues.

The evolution from IVR to chatbots was intended to improve efficiency and customer satisfaction, but in many cases, it has simply shifted the medium of the doom loop from telephones to digital interfaces. While chatbots offer the potential for greater scalability and personalization, they also present new challenges in ensuring that customer interactions are meaningful and effective.

Consumer pain points and the impact on brand loyalty

Customers’ experiences with chatbots and IVR systems can be frustrating, particularly when they encounter a doom loop. Common pain points include:

Consumer pain points and

Focus on banking and financial services

While doom loops exist across verticals, in the financial services industry, these pain points can have particularly severe consequences. Financial institutions handle sensitive information and transactions, and customers expect a high level of accuracy, security, and responsiveness.

When these expectations are not met, it can lead to a significant decline in customer trust and loyalty. Banks and financial institutions have attempted to address these issues by creating specialized flows for critical areas such as fraud detection, financial crime, and compliance. These flows are designed to quickly escalate issues to human agents, ensuring that high-priority concerns are handled efficiently. However, despite these efforts, many customers still experience frustration, particularly when the automated system fails to recognize the urgency of their issue or mistakenly routes them through a generic flow.

This situation is particularly concerning in the context of fraud detection. Customers who suspect fraudulent activity on their accounts expect immediate and effective assistance. If they are caught in a doom loop, the delay in resolving the issue can lead to significant financial losses and a complete breakdown of trust in the institution.

A prime example of this is the Wells Fargo unauthorized accounts scandal, where sales employees opened millions of unauthorized accounts to meet their targets. Irate customers faced difficulties in account closure and resolving related issues quickly because of long wait times and unhelpful responses, which saw a loss of customer trust, widespread media coverage, frustrated customers and employees, penalties for the organization, and eventually significant customer attrition.

Regulatory scrutiny and potential liabilities

The growing reliance on chatbots and automated systems in customer service has not gone unnoticed by regulators. In recent years, there has been increasing scrutiny from regulatory bodies such as the Consumer Financial Protection Bureau (CFPB) in the United States. These regulators are concerned about the potential for these systems to create barriers to effective customer service, particularly in critical areas such as fraud detection and compliance.

The CFPB, for example, has initiated actions targeting financial institutions that rely heavily on automated systems without providing adequate human support. The agency’s primary concern is that these systems can lead to consumer harm, by delaying the resolution of critical issues or providing inaccurate information. Therefore, it has proposed new rules that would require financial institutions to ensure that customers have easy access to human representatives, possibly by clicking a single button. It is also planning to issue rules or guidance to crack down on ineffective and time-wasting artificial intelligence (AI) or chatbots used by banking and financial services (BFS) enterprises for customer service and identify use cases in which usage of voice recordings (IVR) is illegal.

The implications for financial institutions are significant. Failure to comply with these regulatory expectations can result in substantial fines and legal penalties, not to mention potential damage to the institution’s reputation. In an environment where evolving regulatory compliance is already a significant challenge, the additional burden of ensuring that automated systems do not create doom loops adds another layer of complexity.

Strategic recommendations for brands

Given the risks associated with doom loops in customer service, enterprises must take proactive steps to address these issues. Here are some strategic recommendations:

Strategic recommendations for brands

By taking these steps, enterprises can mitigate the risks associated with doom loops and ensure that their customers receive the level of service they expect and deserve.

Exceptional customer experience = sustained customer trust

The issue of doom loops in customer service is not new, but it has taken on new dimensions in the digital age as brands increasingly rely on automated systems. Ultimately, the success of enterprises in today’s competitive environment depends not only on their ability to manage costs but also on their commitment to providing exceptional customer service.

By focusing on the needs of their customers and avoiding the pitfalls of doom loops, enterprises can build and maintain the customer trust and brand reputation that is essential to their long-term success.

If you found this blog interesting, you can read our Decoding The EU AI Act: What It Means For Financial Services Firms | Blog – Everest Group (everestgrp.com) blog, which delves deeper into the topic of regulatory compliance for financial services firms.

If you’d like to discuss the impacts of doom loops on customer experience in financial institutions in more detail, please reach out to Dheeraj Maken or Aishwarya Barjatya.

How has Generative AI Evolved and is its Evolution Now Supporting CX Leaders More on the CXM Journey? | Blog

The landscape of Customer Experience Management (CXM) has witnessed a remarkable transformation within the advent of Generative AI (generative artificial intelligence). Based on periodic comprehensive studies conducted by Everest Group with customer experience (CX) leaders from over 300 enterprises globally, we present comparative insights that highlight the progress made in the past year (2023 to 2024).

Using two different primary studies, research has been conducted regarding gen AI in CXM operations, in the process providing our perspective on future developments.

Reach out to us to discuss this topic further with our expert analysts.

Adoption of digital CX solutions – 2023 vs 2024

Propelled by gen AI, a significant shift has been observed in the adoption of digital CX solutions such as automation, self-service, conversational artificial intelligence (AI), data and analytics, and migration to cloud contact centers.

There was a 15-30% increase in the number of enterprises having deployed these solutions from 2023 to 2024.

Blog The Evolution of Generative AI Exhibit 1

 

Generative AI awareness and its potential

Noteworthy changes in the awareness and potential of various gen AI use cases were also observed during this analysis. In 2023, while most enterprises had a good understanding of applications such as text, image, and code generation, few had robust knowledge of other application areas.

However, this scenario changed significantly in 2024. The majority of enterprises across industries now report having a solid working knowledge of various gen AI applications. Many are even considering synthetic data generation and audio and video generation as high-potential applications for gen AI in CXM.

Blog The Evolution of Generative AI Exhibit 2

The role of third-party providers

The role of third-party providers has become pivotal for enterprises, as they look to navigate complexities. Their importance is increasingly becoming more significant as enterprises realize the various nuances required in developing these solutions.

Blog The Evolution of Generative AI Exhibit 3In 2024, there is a significant uplift in enterprises opting for tech-heritage or specialized AI companies, to use for implementation of gen AI, to be able to leverage their expertise in this technology and achieve faster time to market.

Additionally, more enterprises are outsourcing to contact center providers for gen AI integrations, capitalizing on their CXM domain expertise to better customize customer journeys and improve productivity and CX metrics.

Conversely, there has been a notable decline in the hybrid approach to gen AI development which combines both in-house and outsourced development. From a whopping 70% in 2023, the percentage of enterprises preferring this mode has reduced to only around 30%. This decline, accompanied by a decline in internal development, can be attributed to the change in business priorities for organizations and their need to have eagle-eyed focus on improving their core competencies and achieving their business objectives of revenue improvement, cost reduction, and adapting to new business challenges.

Enterprises choosing to invest wisely in their long- and short-term approach to Gen AI

From a financial perspective, enterprises exhibited a more optimistic stance toward generative AI adoption in 2023, with nearly two-thirds planning to invest over US$1 million in the next 12-18 months on gen AI solutions in CXM.

However, as the technology has matured, enterprises now have a clearer understanding of the returns these investments can generate. Over the past year, many enterprises observed that a significant number of gen AI pilots failed to progress to the deployment phase.

Consequently, in 2024, enterprises have taken a more cautious approach toward gen AI adoption. They now prefer to evaluate each application on a use-case basis before committing to full-scale investments. This shift is reflected in the investment budgets for gen AI, with only half of the enterprises (down from two-thirds) now planning to spend more than US$1 million on these initiatives. This decrease in investments on gen AI is propelled further by the current difficulties in the macroeconomic and business environments, where organizations are placing cost reduction and revenue enhancement as their top priority.

Blog The Evolution of Generative AI Exhibit 4

This cautious stance, however, does not mean that there is a decrease in the perceived potential of gen AI. 2025 continues to hold promise of a booming gen AI adoption. In fact, more than 80% of the enterprises plan to invest more than US$1 million in 2025. As gen AI continues to demonstrate its potential and deliver its promised outcomes, enterprises are likely to embrace it with increased enthusiasm.

If you found this blog interesting, registrations are now open for our Gen AI Unhyped: How It Is Evolving And How To Plan For Success | LinkedIn Live – Everest Group event LinkedIn Live event on September 11, 2024!

If you have questions or want to discuss CX strategies and solutions, please contact Mohit Kumar at [email protected] or Aishwarya Barjatya at [email protected].

Are Human-centric Experiences Possible with Gen AI? We Think So! | Blog

In this blog, we explore how generative AI (Gen AI) is not only enhancing our personal and professional interactions but also ensuring that the essence of human connection remains central in our increasingly digital world. Reach out to us to explore further.

In a world where digital transformation is the norm, maintaining genuine human connections becomes our greatest challenge and opportunity. Gen AI isn’t just a futuristic concept – it’s a present-day reality reshaping how we interact on both personal and professional levels. Amidst the whirlwind of technological innovation, the essence of human connection remains a priority. Let’s delve into how gen AI is revolutionizing customer and employee experiences, ensuring that humanity stays at the forefront of our digital journey.

Gen AI: the game changer

Gen AI is a technology that doesn’t just respond to your commands but anticipates your needs, understands your emotions, and adapts to your preferences. It’s a revolutionary leap beyond traditional AI, enhancing our interactions and deepening our connections. This isn’t about robots taking over; it’s about AI becoming a true partner, understanding us on a more profound level than ever before.

With its ability to sift through vast datasets and interpret the subtleties of human emotions, gen AI is transforming customer experiences into something remarkably intuitive and personalized. Picture your favorite brands offering customized solutions for your needs, with customer service that feels less like a transaction and more like a genuine interaction. Gen AI can improve operational efficiency in contact centers by 15-25% and create experiences that resonate on a deeply personal level, making every interaction feel uniquely tailored to you.

Enhancing employee experience with AI

The impact of gen AI goes beyond revolutionizing customer interactions; it’s also redefining the workplace. Gen AI is transforming how we work, learn, and grow. Imagine walking into your office and having an AI-powered system that understands your work habits, suggests ways to enhance your productivity, and even recommends personalized professional development opportunities. This isn’t merely about efficiency – it’s about creating a fulfilling and engaging work environment.

By leveraging gen AI, companies can significantly reduce agent training time by 20-30%, enabling employees to reach proficiency more quickly. AI tools can help managers give personalized and timely feedback, making employees feel more connected and appreciated. AI-driven training platforms tailor learning experiences to each person, ensuring everyone gets the most relevant and useful training. This makes learning exciting, and employees more engaged with their roles. Additionally, AI can analyze how engaged employees are and suggest ways to boost morale and productivity. By understanding how we work and what we need, AI creates a supportive environment where everyone feels valued and empowered.

Cracking the code: keeping it human

While diving into the digital deep end, we never lose sight of keeping it human. Gen AI might be smart, but it’s no substitute for real connection. So, how do we strike the balance? Simple: by putting empathy first and foremost in every interaction.

Designing for empathy

Think of AI as your trusty sidekick, not the hero of the story. By designing AI systems with empathy in mind, we ensure that technology enhances, not replaces, human interaction. For instance, customer service bots are programmed to recognize when a customer is frustrated or upset and respond with appropriate empathy and understanding and when to pass on the conversation to an agent. This isn’t about mimicking human emotions; it’s about creating a supportive and responsive environment.

Similarly, in the workplace, AI tools are designed to support employee well-being. For example, if an AI system notices a drop in an employee’s engagement scores or an increase in negative feedback, it can proactively suggest wellness resources or flag the issue to HR for a more personalized follow-up. These small, empathetic touches can make a big difference in creating a supportive and nurturing work environment.

Humans + AI: the dream team

Forget the man vs. machine showdown. It’s time to embrace collaboration. Gen AI isn’t here to steal our jobs; it’s here to supercharge them. By teaming up with gen AI, we can unlock new levels of creativity, productivity, and innovation. According to research by Everest Group, 65% of enterprises believe that gen AI will improve or transform their workflow, underscoring its potential to revolutionize the workplace.

AI can handle the repetitive, mundane tasks that often bog us down, freeing us up to focus on what we do best: creative problem-solving, strategic thinking, and building meaningful relationships. This collaboration between humans and AI can lead to more innovative solutions and a more dynamic and engaging work environment.

For example, in customer service, while gen AI can handle routine queries, human agents can step in for more complex issues, providing the empathy and nuanced understanding that only humans can offer. This not only improves efficiency but also enhances the overall customer experience, creating a win-win situation for both businesses and their customers.

Looking ahead

As we gaze into the future, one thing’s for sure: gen AI is here to stay. But let’s not forget our roots. Let’s keep the human touch alive and kicking, even as we ride the digital wave into tomorrow.

The future of gen AI is bright, with endless possibilities for enhancing both customer and employee experiences. However, it’s crucial that we approach this future with a balanced perspective. While embracing the technological advancements that gen AI brings, we must also prioritize the human element, ensuring that empathy, connection, and understanding remain at the forefront.

In conclusion, maintaining human connections in the digital age isn’t just a matter of convenience – it’s a fundamental aspect of our humanity. As we continue to embrace the possibilities of gen AI, let us do so with a deep appreciation for the power of human connection. By harnessing the transformative potential of technology while preserving the essence of what makes us human, we can build a future where empathy, understanding, and compassion flourish in the digital realm.

Watch the webinar, Gen AI Unhyped: How It Is Evolving and How to Plan for Success, to gain insight into how to stay ahead using this emerging tech as a lever, and how to harness the full potential of gen AI.

Enhancing CX with Integrated Tech Solutions: A Spotlight on Salesforce | Blog

In today’s competitive landscape, enhancing customer experience (CX) is crucial for brands to achieve superior growth and loyalty. This blog is the first in a series that will highlight tech providers and how integrated tech solutions can empower enterprises to meet CX challenges and seamlessly connect various tools for improved productivity and data flow. Reach out to us to discuss further or for questions.

Enterprises love talking about customer experience, or CX, and for good reason. Brands that prioritize CX (think Apple, Amazon, Disney, or JP Morgan) consistently outperform their peers in terms of topline growth and customer loyalty.

However, to get to this place of superior CX, enterprises need to invest in a strong backbone of integrated tech solutions that can meet the challenges of an increasingly interconnected operational environment that transcends channels and places. With generative AI-led innovation, digital CX solutions are becoming more sophisticated and impactful.

Enterprises require multiple technologies within the CX tech ecosystem, such as data platforms, including customer relationship management (CRM) and Customer Data Platforms (CDP), contact center solutions, including cloud, AI bots, and agent support, as well as analytics tools for customer and sales insights. Additionally, marketing solutions like content management systems and social media tools are crucial.

The whole ecosystem has had time to become mature and rich with multiple compelling offerings in the market. However, enterprises seeking to simplify their transformation journeys and reduce the burden on IT and procurement are increasingly looking at ecosystems or platforms that can act as a one-stop shop for their technology needs. This approach also helps create a CX ecosystem where different tools can seamlessly integrate and connect with each other for better efficiencies and information flow.

Sensing this opportunity, numerous tech providers are working to address this emerging need in the market. Players such as NICE, Sprinklr, Salesforce, and even tech giants such as Amazon, Google, and Microsoft are moving in this direction. We plan to cover some of them in our series of blogs, starting with Salesforce, which is in the spotlight today.

Salesforce offers a range of CX solutions to enterprises for their customer experience initiatives. The company has developed a suite of CX solutions designed to support enterprises in their customer experience initiatives. Let’s have a look at some of these integrated tech solutions and what they’re capable of across the processes they cater to below.

Salesforce Einstein 1 Platform: The Salesforce platform’s AI capabilities bolster sales, marketing, and support strategies by unifying organizational data. The Einstein 1 platform enables enterprises to offer connected customer experiences, develop targeted strategies, and track their effectiveness. It also includes Einstein Copilot, a customizable AI assistant.

Einstein 1 is a modular platform that can be tweaked as per the enterprise needs and comes with core solutions for sales, marketing, service, commerce, and data that are natively integrated into the platform, along with other solutions that can significantly enhance these capabilities, such as analytics and AI. Let’s look at the core offerings under the Einstein banner in detail below:

Picture1

(Image source: Salesforce)

Service Cloud:  Service Cloud integrates customer service and field service needs onto the Einstein 1 Platform, connecting business data and apps to provide a complete view of every customer. Service Cloud helps businesses across industries deliver service from first contact to final delivery on multiple channels.

It offers features such as omni-channel routing, case management, analytics and dashboard, telephony integration, knowledge management, AI integration, service console for agents, community collaboration, social media integration, and field service among others.

Sales Cloud: Sales Cloud is a comprehensive platform designed to support sales organizations of all sizes, industries, and regions. It offers a wide range of tools and capabilities tailored for different roles within a sales team, including sales leaders, representatives, and operations. These tools cover various aspects of the sales process, such as prospecting, engagement, team collaboration, analytics, sales programs, performance management, partner management, CPQ (Configure, Price, Quote), and billing. Built on the Einstein 1 platform, Sales Cloud integrates harmonized data and connects to the broader Customer 360 ecosystem through Data Cloud, utilizing reliable AI to enhance its functionality.

Marketing Cloud: As the name suggests, Marketing Cloud is a digital marketing platform aimed at helping organizations manage customer journeys. Marketing Cloud comprises five main core capabilities, each focusing on specific aspects of digital marketing. The key products within Marketing Cloud are Data Cloud for Marketing (customer data platform), Personalization (real-time next best actions), Engagement (email, mobile, advertising, journeys, and loyalty management), Account Engagement (marketing and sales alignment, lead generation, and ABM), and Intelligence (performance insights, analytics, and reporting). The platform is aimed at B2C customers. The product architecture sits on its own platform apart from the core Salesforce infrastructure, using connectors for integration.

Formerly called Pardot, the Marketing Cloud Account Engagement is aimed at B2B customers. It can automate and streamline marketing processes and multifunctional campaigns across channels. It includes functionalities to manage and nurture leads, run targeted campaigns, align with sales to close deals, and track the effectiveness of marketing efforts.

Commerce Cloud: Designed for brands to create and manage online stores and scale personalized ecommerce experiences from acquisition to conversion to loyalty, Commerce Cloud offers digital storefronts for business-to-consumer (B2C) and business-to-business (B2B) customers, along with full-scale order management and payments solutions that can be connected to the rest of the business. Commerce Cloud converts insights into actions, driving revenue and loyalty throughout the entire customer journey by leveraging unified data and trusted AI on the leading AI CRM.

Besides these, Einstein 1 also features other solutions inside and outside the core platform. These include solutions such as:

  • Data Cloud that captures customer data in real time from different sources (internal to Salesforce and external, and both structured and unstructured data)
  • Analytics (including Tableau) for analytics and BI
  • Mulesoft, which connects software as a service (SaaS), on-premises software, legacy systems, and other platforms to Salesforce
  • Slack for internal and external messaging, collaboration, and automation of work processes
  • AppExchange, a marketplace to add pre-built apps and capabilities to Salesforce solutions
  • Net Zero Cloud, a sustainability management platform to track and analyze your carbon emissions and environmental footprint in a single location

Salesforce Einstein’s integrated and holistic operations support enterprises in designing their customer experience. Features such as low-code development, integrated AI, and unified data management along with a platform-based approach to CX transformation are some of its key features. With recent investments, especially in AI-focused organizations, Salesforce has shown an intent to focus on upcoming AI solutions and add those to its core offerings.

Of course, it is one of the several compelling options out there. Stay tuned to this space as we explore other integrated tech solutions that can help you on your CX transformation journey. For questions or to discuss this topic further, reach out to Sharang Sharma at [email protected].

Watch the webinar, Elevating CX: Trends and Insights for a Unified CX Tech Strategy, to learn how integrating service, sales, and marketing capabilities through a platform approach can streamline operations, centralize customer data for better insights, improve collaboration across departments, and enhance the overall customer experience.

Revolutionizing Customer Journeys: Creating a Unified Customer Experience through AI | Blog

A top-notch customer experience (CX) can transform skeptical shoppers into loyal brand advocates. However, achieving this level of service can be challenging. With an ever-expanding stream of customer interaction channels available, AI can help enterprises manage these diverse touchpoints more consistently and coherently.

Modern customers, including GenZ and millennials, expect seamless experiences, whether voice, chat, or social media. However, many enterprises manage these channels separately, leading to disjointed customer experiences, fragmented data, and service inefficiencies.

For example, let’s say John adds a laptop to his cart on a retailer’s website but decides to buy it later. When he visits the store the next day, the sales associate has no information about his online cart. Frustrated, John calls customer service, but they also can’t access his cart details. Each channel – online, in-store, and phone – operates in silos, causing John frustration and ultimately leading him to abandon the purchase.

This fragmentation leads to delays and diminishes the customer’s trust and satisfaction. Additionally, valuable data gathered from these interactions remains isolated within each channel, limiting the ability to gain insights into customer needs and preferences. Such a fragmented approach can negatively impact CX, as seen below.

Revolutionizing Customer Journey Creating a Unified Customer Experience through AI Images on the doc

Source: Based on an Everest Group survey of over 600 consumers in Q3 2023

AI has emerged as a transformative force in integrating various customer interaction channels, breaking down organizational silos, and addressing the issues consumers are facing on both spoken and written channels. But how can AI in CX be the answer to solving customer issues?

The role of AI in bridging interaction channels and breaking down silos

AI revolutionizing data aggregation and analysis

Robust data integration and management practices are crucial for digital technologies to address the challenges of heterogeneity, volume, and velocity in customer data. AI in CX can revolutionize data aggregation, integration, and management in several ways. Automated data collection and aggregation through schema mapping, data normalization, deduplication, and automated Extract, Transform, and Load (ETL) tools ensure consistency across data sources. AI also modernizes data quality processes, enabling large-scale, accurate data annotation and labeling.

Further, generative AI (gen AI) creates bias-free, cost-effective synthetic data, enhancing AI adoption in sectors like retail, manufacturing, and autonomous vehicles. Traditional AI models also enhance data security and privacy by detecting threats in real time and automating data cleansing to improve reliability. AI-powered techniques revolutionize data analysis with descriptive, diagnostic, predictive, and prescriptive analytics, helping organizations interpret customer data and predict customer experiences.

However, challenges such as bias in AI models, the interpretability of black-box algorithms, and the need for robust data privacy safeguards must be addressed to fully leverage AI’s potential.

Reconciling customer lifecycle touchpoints through AI

Extending these traditional and gen AI tools to enhance the integration of data across customer lifecycle journey touchpoints – encompassing sales, support, and marketing – builds a comprehensive understanding of customers.

Traditional AI and ML algorithms unify disparate databases, integrating them into a central system, which allows seamless access to data from various departments. This provides customer service representatives with a 360-degree view of each customer. It enables organizations to monitor every interaction with their brand, integrating key information such as contact details, survey responses, purchase histories, and more.

On the other hand, gen AI leverages natural language processing (NLP) and deep learning models to personalize customer interactions. By analyzing vast amounts of data from various channels, such as social media, emails, and chat logs, gen AI creates detailed customer profiles. By integrating AI with customer relationship management (CRM) systems and customer data platforms (CDPs), organizations can deliver highly personalized and contextually relevant responses. This not only enhances customer satisfaction but also ensures a consistent and unified experience across all touchpoints.

AI-driven predictive analytics models analyze historical data to identify patterns and predict future customer behaviors. For instance, machine learning algorithms can detect early signs of customer dissatisfaction, allowing businesses to address them proactively. AI in CX can monitor network performance and automatically notify customers about outages, providing estimated resolution times and minimizing customer frustration.

Furthermore, AI-powered marketing platforms utilize automated data mining, real-time data processing, and advanced segmentation algorithms to target campaigns effectively. By analyzing past interactions, browsing history, and behavioral data, AI creates precise customer personas and segments. This enables businesses to deliver personalized marketing messages and offers at the optimal time.

Delivering personalized experiences at every stage

AI in CX not only streamlines data flow but also enables the delivery of personalized experiences at every stage of the customer lifecycle. Personalization is crucial. A 360-degree view of customers, enabled by AI, offers several benefits, including:

1

What does this mean to the customers?

  • Enhanced convenience: Customers can switch between channels (website, app, in-store) without repeating information, streamlining tasks like browsing, purchasing, and customer service interactions
  • Consistent information: Uniform responses and information across all channels reduce confusion and frustration, while consistent branding and messaging enhance trust and reliability
  • Personalization: Integrated customer data across channels allows for personalized recommendations and offers, with previous interactions and purchase history informing tailored customer support
  • Efficient issue resolution: Intelligent routing directs customers to the most appropriate support channels or agents, and real-time data access enables quick and effective problem-solving
  • Proactive engagement: AI-driven notifications and reminders help customers complete their journeys smoothly, while follow-up communications, like feedback requests and product suggestions, improve engagement
  • Customer satisfaction: Reduced friction and streamlined processes enhance the overall customer experience, fostering loyalty and encouraging repeat business

Embracing AI in CXM is essential for businesses aiming to maintain a competitive edge. The ability to unify customer interactions across channels and deliver personalized experiences will be a differentiating factor.

By breaking down silos and integrating customer interaction channels, businesses can revolutionize their customer journeys and achieve long-term success.

AI is not just a tool but a strategic imperative for modern CXM. The future of customer experience is unified, personalized, and powered by AI—let’s embrace it.

If you have questions or would like to further discuss gen AI’s evolution, please reach out to Sharang Sharma or Joshua Victor.

Watch our webinar, Elevating CX: Trends and Insights for a Unified CX Tech Strategy, to discover how leveraging unified platforms and innovative technologies can help businesses scale, increase agility, and create seamless, personalized customer journeys.

How to Prepare your Customer Experience (CX) Support for CrowdStrike-like Outages | Blog

When unexpected disaster hits, how should enterprises handle the impact on customer experience? Read on for expert suggestions on best practice for CX crisis mitigation, or get in touch if you’d like to speak with our analysts on this topic.

It was a business-as-usual day on July 18th, until several users started seeing the “blue screen of death” issue on their systems. Soon, it became clear that the problem was more widespread than initially thought. Airline, hospital, banking operation, auto company systems and more were crippled across the globe.

While it was soon identified that the issue was caused by an update pushed by CrowdStrike that took down worldwide Microsoft systems, there was no ready fix to undo the damage immediately. This resulted in many cancelled flights, the 911 emergency line going down across several US states, and major stock exchanges suffering outages across the globe. While the technical issue has now been resolved, it might take several days in some situations to go back to normal.

As customers bore the brunt of the havoc, there are lessons for enterprises on how they can best manage customer experience (CX) in times of such crisis. It’s highly unlikely that this is going to be the last outage impacting the globe. Enterprises are increasingly coming under threat from such disruptions, often driven by nefarious elements.

Some measures that enterprises can consider for minimizing the inconvenience for customers during such outcomes include:

Proactive communication – in real-time and with transparency

Given the potentially massive scale of disruption, it becomes crucial for enterprises to set up a communication channel with their customers and proactively inform them of issues undergoing resolution. This can be done through use of technology where information can be pushed out across multiple channels, such as text, messaging, and emails. Informing customers of the issue as early as possible allows them to plan more effectively.

It is also vital to be transparent. Often, it is not clear when the issue will be resolved, but communicating what has happened and what is being done to fix it can help alleviate customer concerns.

For example, during the 2021 Facebook outage, the company used Twitter to keep users informed about the issue and posted updates on restoration efforts, ensuring continuous communication despite their primary platform being down.

 Managing volume surge – support team readiness

Any major disruption is going to create a significant surge in the volume of enquiries coming in. Equipping support teams with the right information and setting up self-serve channels can help manage some of that influx. Using agent assist solutions can help them be more readily equipped to provide real-time updates.

Business continuity plan (BCP) measures – redundancy, flexibility, and crisis management

Having BCP measures in place can be crucial, as outages such as these can often result in entire teams in a particular region being cut off. Having redundancies built into the system through use of cloud-based flexible solutions, as well as using edge computing to ensure reduced loads on central servers, can help reduce any potential technology challenges.

Similarly, having diversified teams across regions, if possible, as well as providing crisis management training to agents, can help them to better manage customer complaints during a crisis. Additionally, having global and regional crisis management teams that can take independent actions in dire situations can often result in saving precious time when deploying countermeasures.

For instance, after the 2018 Marriott data breach, the company implemented extensive crisis management training for their customer support teams to better handle the increased volume of calls and concerns from affected customers.

 Vendor management – disaster recovery plans and effective communication channels

Ensuring service partners have disaster recovery plans can be differentiator between good CX and chaos. Additionally, it is important to have clear communication channels with vendors for rapid and effective response to outages.

 Planning – risk assessment

Conducting regular risk assessments to identify potential outage scenarios and their impact on customer experience is crucial for effectively managing difficult situations.

Prevention – regulatory compliance

There is a good reason that the proverb “Prevention is better than cure” exists, and it applies to this scenario as well. While it might not be possible to plan for every outage, by ensuring compliance with regulations, enterprises can protect themselves and be in compliance with local laws. For example, legislation such as the recent Digital Operational Resilience Act (DORA) in the European Union has been designed to comprehensively address information and communication technology (ICT) risk management in the financial services sector.

Continuous improvement – post incident evaluation

It is possible that enterprises may not get all the things right despite preparations. It becomes important to evaluate performance after such incidents and learn from failures. Collecting feedback from customers and understanding where the biggest challenges were can help enterprises prepare more effectively in the future.

While enterprises can’t control every aspect of an outage and its fallout, they can plan for unexpected outcomes. Ensuring that customers feel supported and informed throughout the disruption can often be the differentiator between good and bad experiences. It is important to plan for disruptions holistically and leverage all readily available measures to minimize inconvenience for the customers in such times.

For questions about the CX crisis best practices, contact [email protected]. For more on customer experience management, read our State of the Market report, Strategic Keys: Unlocking the Potential of Customer Experience Management.

Is Japan on the Cusp of CX Outsourcing Disruption? | Blog

Japan is on the verge of a significant transformation in the customer experience (CX) outsourcing industry. This blog explores how generative AI and other cutting-edge technologies are revolutionizing Japan’s CX market, creating unique opportunities and challenges in a country where tradition and innovation coexist harmoniously. Reach out to us to discuss this topic further.

The CX outsourcing industry is undergoing significant disruption due to generative AI (gen AI) and other advanced technologies. Gen AI is transforming contact center operations by automating interactions, enhancing agent performance, and improving operational efficiency. Meanwhile, other technologies, such as accent neutralization and AI translation, are eliminating language barriers, improving service quality, and boosting workforce productivity. As enterprises look at outsourcing to meet some of the changing dynamics in the market, vendor management strategies are being re-evaluated, with a focus on providers with robust technology capabilities. These trends collectively indicate that the global CX industry is on course to get disrupted.

This blog illuminates how Japan – the Land of Cherry Blossoms – is also on the cusp of CX disruption. In this vibrant country where tradition meets innovation, the CX market presents unique opportunities and challenges, much like navigating the bustling streets of Tokyo.

Before we deep dive, the following image sets the stage some of the unique attributes of Japan’s business landscape.

Distinctive qualities of Japan

Infographic on Japan blog

Although Japan is known for its innovation, historically, it has been cautious in adopting cutting-edge technologies in the CX space. Factors such as cultural conservatism, hierarchical structures, and a preference for traditional methods of working have contributed to this lag. However, with the advent of gen AI, this scenario is poised to change.

How is the Japanese CX market changing? ­

The Japanese concept of Monozukuri (ものづくり) which encompasses meticulous attention to detail, dedication, and pride in creating high-quality products in-house, makes CX outsourcing less appealing in the world’s third-largest economy. However, AI has found a way to make outsourcing attractive even to the most discerning clients. It further presents an opportunity for Japanese enterprises to save on increasing operational costs onshore, develop capabilities to serve customers through non-voice channels, and leverage technologies such as automation and analytics to deliver superior quality CX.

Tasked with adapting to this evolving market, the country’s outsourced CXM market has witnessed a significant evolution in recent years.

Picture2

A land of growing opportunities for outsourcing amid some long-standing risks

With a market size of US$4-5 billion and a market share of 26% in the Asia Pacific (APAC) outsourced CXM market, Japan commands attention as a prominent region in the outsourced CXM services industry.

The outsourcing market in Japan stands out due to its traditional emphasis on quality over cost, process control, and unique cultural challenges, favoring in-house over outsourced operations. However, since the early 2000s, a declining workforce and the rise of global outsourcing companies have changed this tendency. Japan, which is still behind some of the other APAC geographies in terms of CX innovation and CX tech, combined with an aging and shrinking workforce, is now starting to grapple with issues of high operational costs and labor shortages in the CX service delivery landscape.

However, Japan’s government is placing a strong emphasis on gen AI; for instance, Japan’s industry ministry invested over US$55 million in AI initiatives in 2023. Furthermore, both central and local governments have introduced tax breaks, grants, and loan assistance to attract foreign investments.

This has made Japan an attractive market for CX outsourcing as various businesses across sectors look to expand their outsourced operations.

Nonetheless, these opportunities come with some risks:

  • Economic risk: Despite being the 3rd third largest economy in the world, Japan has been in and out of short-term economic recessions, and is currently facing an economic slow-down with a growth rate of only 0.6% in the last decade
  • Demographic risk: The aging population is another concern, as the majority workforce is between the ages of 45 and 54, making it challenging to find and retain qualified CX professionals
  • Geological risk: Japan, situated within the Ring of Fire, makes it one of the most tectonically active places on Earth and heightens the risks of natural disasters such as frequent earthquakes and floods due to its geographical location

Recently, the Bank of Japan (BOJ) ended its negative interest rate policy in March 2024, signaling a stronger economy. Japan’s economy is forecasted to grow by 1-2 % in the second half of 2024, driven by wage growth, consumer spending, and a weak yen. Recent economic trends indicate a potential upswing in spending, further enhancing Japan’s appeal as a destination for CX outsourcing operations. However, companies must navigate through the nuances of these opportunities and risks to gain from Japan’s outsourced CXM market.

Current service provider landscape in Japan

In Japan’s contact center outsourcing sector, there are two distinct categories of service providers: regional firms such as Transcosmos, Bellsystem24, TMJ, and Altius Link (formerly Relia Inc.) and global companies such as Concentrix, Teleperformance, TDCX, and Foundever. While regional providers hold the largest market share in the Japanese outsourced CXM market, global players also have a notable presence, leveraging their established positions in the Asia-Pacific region.

 

Service Provider Description
Picture3 ·       Headquartered: Tokyo, Japan

·       FTEs and delivery centers: 43,000 FTEs across 71 locations

·       Industries served: Manufacturing, BFSI, telecom & media, government, and retail sectors.

·       Transcosmos stands out for its comprehensive suite of digital and traditional CX solutions and delivers cost-effective, results-oriented services. The company provides a comprehensive suite of customer experience (CX) solutions, including chatbots and multilingual speech recognition tools (supporting 25 languages)

·       Their blended delivery model leverages a mix of onshore and other low-cost locations for CX delivery. Furthermore, they demonstrate a commitment to client success through flexible pricing models. These models include outcome-based, output-based, and hybrid options, allowing for risk- sharing and cost-efficiency tailored to each client’s needs

Picture4 ·       Headquartered: Tokyo, Japan

·       FTEs and delivery centers: 11,000 FTEs across 37 locations

·       Industries served: Manufacturing, BFSI, telecom & media, retail, healthcare, and public sectors.

·       It provides services such as customer service, technical support, CRM, and sales services. Its consulting offerings include CX strategy formulation, contact center operational consulting, VoC analysis, process benchmarking, and end-to-end crisis management solutions

Picture5 ·       Headquartered: Tokyo, Japan

·       FTEs and delivery centers: 19,000 FTEs across 23 locations

·       Industries served: Manufacturing, BFSI, technology, and public sectors

·       TMJ offers a wide variety of CX solutions, including contact center outsourcing, sales and technical customer support services, and back-office services. TMJ caters to a diverse range of industries in Japan to improve its presence in the APAC region and establish a hub and spoke model with its base in Tokyo

Picture6 ·       Headquartered: Tokyo, Japan

·       FTEs and delivery centers: 33,000 FTEs across 100 locations

·       Industries served: Manufacturing, BFSI, telecom & media, energy and utilities, government, and public sectors

·       It delivers customer support, order fulfillment, technical support, inbound and outbound sales, and helpdesk services to clients in Japan, China, Vietnam, and the Philippines offering support in 12 languages including Japanese, English, Chinese, Spanish, Portuguese, Korean, and other Asian languages

Japan beckons businesses with its unique blend of tradition and innovation. With a skilled workforce, competitive resource costs, and regulatory stability, Japan offers fertile ground for driving business success and nurturing long-term partnerships.

As these changes take place in the Japanese market, enterprises need to adopt new digital technologies to embrace the growing uncertainty in the market. Service providers and technology partners have a critical role in facilitating this transformation. By integrating advanced solutions and offering robust operational support and a skilled talent pool, they can help businesses navigate the evolving business landscape. Collaboration between enterprises and service providers can prove beneficial for driving innovation and ensuring technological advancement in the Japanese market, which is ripe for CX disruption.

If you have questions or would like to further discuss Japan’s CXM evolution, please reach out to Sharang Sharma at [email protected], Aishwarya Barjatya at [email protected], or Joshua Victor at [email protected].

Watch our Mid-market Digital Transformation: Insights and Outlook for 2025 webinar to learn best-practice recommendations for adopting newer technologies, based on our analysts’ recent experiences.

Enhancing Customer Experience through AI-driven CX: Bringing Innovation and Human Connection Together | Blog

Read on to explore how AI is revolutionizing customer experience (CX) in today’s fast-paced digital landscape. In this expert analysis, you will learn how AI-driven solutions enhance customer journeys, personalize interactions, and streamline operations. Discover the pivotal role of human talent in ensuring the success of AI-driven CX and how businesses can harness these innovations to create seamless, customer-centric experiences. Reach out to us directly to discuss this topic further.

In today’s fast-paced digital landscape, customer experience (CX) stands at the forefront of business success. Companies are increasingly turning to AI to revolutionize their customer interactions, streamline operations, and provide a seamless journey from start to finish. AI-driven CX is not just a buzzword; it’s a game-changer, offering a host of benefits to both businesses and their customers alike. In this blog, we’ll delve into how customers stand to benefit from AI in their journey and highlight the pivotal role of human talent in ensuring the success of AI-driven CX.

Enhancing the customer journey with AI

Imagine a seamless, personalized experience tailored precisely to your preferences and needs, available at your fingertips. That’s the promise of AI-driven CX. From personalized product recommendations to proactive customer support, AI empowers businesses to anticipate and meet customer expectations like never before.

AI triage

Elevated experiences: hyper-personalization for unparalleled connections

One of AI’s biggest benefits for CX is using data to achieve true personalization at scale. AI can analyze a company’s vast pools of customer data – from transactions to browsing behaviors to communication histories – to build rich customer profiles. It can then surface insights to deliver experiences tailored to each individual’s preferences, needs, and contexts.

For customers, this enables a new level of relevance from the brand interactions they receive. AI-powered recommendation engines, such as those from Netflix, Spotify, and Amazon, ensure customers always see the most fitting content or product suggestions.

For businesses, envisioning how AI-powered recommendation engines could work in their own context unlocks a new level of relevance in brand interactions. AI algorithms can ensure that customers receive personalized recommendations for support resources or solutions tailored to their specific needs and preferences. Moreover, AI can personalize messaging tones, channels, and cadences for outreach, creating smoother, more engaging experiences for customers. By leveraging AI in this way, customer service teams can deliver proactive and tailored support that addresses customer needs efficiently and enhances satisfaction.

Anticipating needs: proactive care redefining customer support

AI opens up powerful new possibilities for proactive customer care. With machine learning models analyzing data patterns, businesses can anticipate customers’ likely future needs or issues and be proactive about resolving them. This benefits customers by allowing problems to be addressed before any major disruption or frustration occurs.

For instance, a telecom company notices an increase in calls related to a network outage in a specific area. Instead of waiting for frustrated customers to flood the lines with complaints, the contact center proactively sends out automated notifications to affected customers, informing them of the issue and providing estimated resolution times. Additionally, the system identifies high-priority customers, such as those with critical business needs or medical emergencies, and prioritizes their inquiries for immediate resolution. Another example is when an insurance provider utilizes proactive outreach strategies, such as sending notifications when insurance coverage is expiring or subscriptions are ending, along with discounts or offers for renewals.

Efficiency amplified: faster, smoother, better resolution times

When customers do need to directly engage a brand for support, AI can accelerate resolution times and reduce frustration. Conversational AI assistants are becoming smarter at understanding complex language to quickly identify the true intent behind customers’ requests. From there, AI can directly handle simpler queries, tasks, or transactions through self-service.

For instance, an AI assistant could autonomously resolve a customer asking to return a parcel by walking through the process and initiating a refund. For more complex cases, AI can automatically route the conversation to the right human agent or department for seamless escalation.

This AI-powered triage and assistance cuts down tedious back-and-forth, reducing resolution times and customer effort. When human employees are looped in, they have full context to focus on providing a tailored, speedy resolution.

The human touch: why human talent matters in AI-driven CX

While AI brings transformative capabilities, human agents remain vital for delivering empathetic, personalized customer experiences – especially for complex, emotional situations. AI can augment and empower human workers, rather than replace them. Here’s why human talent is crucial in AI-driven CX:

Empathy and emotional intelligence

AI may excel at analyzing data and predicting behavior, but it lacks human empathy and emotional intelligence. Empathetic human interactions are essential, especially in sensitive situations or complex inquiries where understanding and compassion are paramount. Human agents can empathize with customers, actively listen to their concerns, and provide personalized solutions that resonate on an emotional level.

Complex problem solving

While AI can handle routine queries and tasks with efficiency, complex issues often require human intervention. Human agents possess critical thinking skills and domain expertise to navigate intricate problems, adapting to unique situations and finding creative solutions. By combining AI’s automation capabilities with human problem-solving skills, businesses can deliver comprehensive support that addresses the full spectrum of customer needs.

Building trust and loyalty

Trust is the foundation of customer relationships, and human interactions play a vital role in fostering trust and loyalty. Customers value authentic connections with human representatives who demonstrate understanding, sincerity, and integrity. While AI can streamline processes and deliver personalized experiences, it’s the human touch that cultivates meaningful connections and builds long-term loyalty.

Continuous improvement

Human feedback is irreplicable for refining AI algorithms and enhancing the customer experience. Human agents act as the last checkpoint before messages reach customers, ensuring authenticity and relevance. Moreover, with AI’s potential to hallucinate, skilled agents play a crucial role in validating AI-generated insights and enhancing the overall customer experience. By fostering collaboration between humans and AI, businesses can achieve continuous improvement in their customer operations and stay ahead in a competitive market.

Conclusion: the future of customer experience (CX)

In the dynamic realm of CX, the fusion of AI innovation and human expertise emerges as a cornerstone for success. As businesses embrace AI-driven solutions to streamline operations and personalize interactions, they can unlock unprecedented levels of efficiency and customer satisfaction. However, amidst these technological advancements, the pivotal role of human agents cannot be overlooked. With their empathy, creativity, critical thinking, and problem-solving abilities, human agents add an indispensable touch to customer interactions, fostering trust and loyalty in an increasingly digital landscape. By striking the right balance between AI-driven innovation and human connection, businesses can navigate the complexities of CX, delivering seamless experiences that resonate with customers and propel their brands to new heights of success.

For more details on customer experience and AI reach out to Rishav Kumar, [email protected], or Aishwarya Barjatya, [email protected].

Learn more about how to utilize AI and its latest iteration, generative AI, for anticipating CX needs in the LinkedIn Live session, Leveraging AI for CX.

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