Tag: CX / customer experience

Unlocking the Power of Data-driven Insights in Subscription Management Through Digital CXM | Blog

Cutting-edge digital technology is revolutionizing subscription management by providing organizations with real-time data-driven insights to enhance personalization, increase sales opportunities, optimize revenue, expand offerings, and retain customers. Explore the transformative impact of the latest advancements on customer experience management (CXM) for subscription services and gain valuable insights into the future outlook in this blog.

Subscription-based services have experienced exponential growth in recent years across various industry sectors, including streaming, gaming, media and entertainment, as well as retail and Consumer Packaged Goods (CPG). The rise of subscription box services has further fueled this trend by offering customers a convenient and personalized way to access products/services on a recurring basis.

Organizations offering subscription-based services have access to vast customer data, encompassing demographic information, purchase history, browsing behavior, engagement metrics, and feedback. In the digital customer experience (CX) era, organizations can better grasp their customers’ preferences, behaviors, and pain points by thoroughly analyzing this extensive consumer repository data. The use of AI to support this analysis has accelerated the pace at which organizations can respond to trends and changes in customer behavior or CX needs. This understanding can help these enterprises deliver superior CX, foster long-term loyalty, and achieve sustainable growth in today’s competitive marketplace.

Let’s delve into how technological advancements have transformed the approach to subscription management and the advantages it brings to organizations.

Traditional approach to subscription management

Historically, subscription management has been characterized by a reactive, post-facto approach to data analysis with data stored across multiple disparate systems and departments. In this traditional model, organizations or their outsourcing partners would collect customer data throughout the subscription lifecycle in an isolated approach. Analysis and decision-making would occur afterward to form future strategies, product development, and customer engagement initiatives. While this approach has its benefits, it is constrained by the following issues:

  • Lack of a unified customer view: In many organizations, different departments handle various aspects of subscription management, such as sales, marketing, customer support, customer retention, and finance, with each department storing data independently. Without a unified view of customer data, organizations may struggle to analyze the entire customer journey to identify patterns or trends that could inform strategic decisions or improve customer engagement efforts
  • Delayed decision-making and inability to implement real-time interventions: The reactive nature of post-facto data analysis often leads to delays in decision-making, as insights are generated after the fact. Without real-time data analysis capabilities, organizations may miss opportunities to intervene proactively during the subscription lifecycle, resulting in a less agile response to customer needs and market dynamics. Additionally, while certain analytics tools can identify customer concerns, the process still entails hours of listening and data collection, further delaying responses and increasing agent workload
  • High dependency on the IT group: In the traditional subscription management approach, organizations were heavily dependent on their internal (or outsourced) IT group to respond to requests for change, build requirements, prioritize the work, and finally implement

 Advancement in technology redefining CXM for subscription-based offerings

The rapid progression of digital CX tools, including advanced analytics, automation solutions, Contact Center as a Service (CCaaS), conversational AI, and the emergence of generative AI (gen AI), have significantly transformed CXM for subscription-based models. This has eliminated data silos and provided real-time data-driven insights. As a result, these technological advances have ushered in a new era of data-driven CXM management, revolutionizing the following aspects:

  • Personalized subscription offerings and recommendations: Advanced digital CX tools can analyze customer data to deliver highly personalized subscription plans and recommendations tailored to individual needs. Leveraging Natural Language Processing (NLP) capabilities, gen AI can engage in conversational interactions, guiding customers through subscription options and providing tailored advice
  • Identification of upsell/cross-sell opportunities: Real-time analytics enable organizations to identify product or service enhancement opportunities based on customer needs. This includes determining the optimal time to introduce premium products or services and suggesting relevant upgrades or add-ons. Furthermore, organizations can create personalized product bundles, discounts, or rewards tailored to individual preferences
  • Dynamic pricing and revenue optimization: Gen AI models can analyze market trends, competitor data, and customer behavior to recommend dynamic pricing strategies and optimize revenue streams from subscriptions. By dynamically adjusting prices based on demand, seasonality, and customer preferences, organizations can maximize revenue potential while remaining competitive by facilitating discount strategies for new customer acquisition, as well as for customers who are at churn risk
  • Augmentation of product/service offerings: Organizations can use advanced analytics tools, such as speech analytics, sentiment analytics, or tone analytics, to identify the areas of concern for end-customers and address them by augmenting their offerings. Digital-first service providers have leveraged gen AI’s analysis and conversational capabilities to develop solutions that can identify the root cause of consumer concern without requiring extensive call listening or data collection time
  • Increased customer retention: Organizations can identify patterns indicating potential customer churn risks for subscriptions. By leveraging advanced analytics and machine learning algorithms, they can proactively intervene to mitigate these risks, offering personalized incentives, targeted communication, or proactive customer support. Additionally, organizations can continuously monitor customer engagement metrics and feedback to iteratively improve subscription offerings and enhance overall customer satisfaction, fostering long-term loyalty and retention. As businesses mature, effective churn management emerges as a paramount concern, rendering these tools indispensable for support

Outlook for subscription-based services

The CXM landscape for subscription-based services is rapidly evolving, driven by technological advancements and the imperative for organizations to deliver superior customer experiences. Moving forward, organizations must recognize the importance of partnering with CXM providers that offer comprehensive capabilities to address the evolving needs of subscription-based models. Some leading CXM providers have already begun to leverage AI and gen AI to support analysis of high-volume clients, leading not only to deeper insights on the interaction but also allowing them to create models for churn and NPS prediction based on the interactions that their clients are using to make business decisions.

By leveraging these capabilities, organizations can not only enhance customer satisfaction and loyalty but also drive revenue growth and market competitiveness in today’s dynamic landscape. Therefore, organizations must prioritize investments in digital CXM and strategic partnerships with digital CXM providers. This can empower them to navigate the evolving subscription economy effectively. As the subscription-based service model continues to gain traction, organizations that embrace data-driven CXM strategies will be well-positioned to thrive in this ever-changing market. Furthermore, organizations relying on outsourced CXM providers must be ready to utilize their outsourcing partners’ technology and provide the necessary data to fully capitalize on the emerging benefits these companies offer.

To discuss CXM strategies and subscription management further please contact David Rickard, [email protected], or Divya Baweja, [email protected].

Watch our LinkedIn Live session, Leveraging AI for CX, to learn about how to utilize AI and gen AI for anticipating CX needs and creating adaptive strategies.

Are Investors Right to Be Nervous about CXM Providers? Well, It Depends! | Blog

Generative AI (gen AI) is transforming the customer experience management (CXM) landscape, challenging traditional contact centers. While concerns about declining revenues and increased costs are valid, many traditional methods, like human interaction, are still needed for complex customer issues. Read on to discover strategies to improve CXM provider success in a technology-driven market. Reach out to discuss this topic in depth.

Over the last 12+ months, we have seen a massive drop in the stock performance of nearly every publicly traded customer experience management (CXM) service provider. This has mainly been driven by nervousness in the market about how generative AI will impact the need for contact centers, especially in the way they are operated today, which is very reliant on vast numbers of people.

In this blog, I will explain why, in answer to the question, “Are investors right to be nervous?” I give the very vague answer of “It depends.”

The possible impact of generative AI on traditional contact centers and CXM providers

Firstly, we need to understand what could be causing some of the angst among investors, and full disclaimer: I am not positioning myself as an expert investor. There may be very technical reasons why investors are right to be nervous, but I am looking at it as someone who has bought contact center services for some of the world’s leading brands and has a good understanding of how this environment works.

Let’s explore the ways gen AI or next-gen technology could impact traditional contact centers and CXM providers:

  • Traditional contact center businesses have been successful in building large workforces and real estate portfolios, and there is an expectation that the use of technology, brought to large-scale attention by the hype around gen AI, will dramatically reduce the need for humans and, in turn, the need for large real estate portfolios. This assumption means that service providers will have dramatically increased exposure to their real estate costs and will see their main source of revenue, i.e., humans, reduced or removed completely
  • Therefore, the revenues of the impacted service providers will decline over the coming years as more customer interactions are handled by technology, making the companies operating in this space less attractive, if judged on revenue performance alone
  • There is constant talk about new entrants to the CXM market and how a pure technology play, for example, Conversational AI, much improved by the use of gen AI, could replace the need for human interaction, therefore giving birth to a whole new set of CXM providers who only bring technology. This, if true, would have a dramatic impact on traditional players

Any sensible person looking at the factors I have outlined above would be right to be nervous about the future of traditional contact center players. However, this would be missing a few key factors often overlooked or at least given less priority than the concerns. Some of these factors include:

  • People still want to talk to people at times of high stress or when they perceive the problem as complex or emotive. Despite the rapid rise of technology aimed to reduce the amount of human interaction in the contact center, such as robotic process automation (RPA) or Conversational AI (CAI), which has been around for many years, over 70% of service provider revenues are still coming from the voice channel. This proves customers still want to talk to people, and even with the inclusion of gen AI, the shift to non-voice channels is not going to happen overnight
  • When having a negative outlook for traditional contact center players, it assumes that they are standing still and doing nothing to embrace the new technologies, which is totally incorrect. Most of the leading CXM service providers we assess as part of our CXM PEAK Matrix © Assessment are investing heavily in a wide range of technologies that will improve the customer experience and reduce the need for human-assisted contacts, but also, and equally as vital, allow support agents to be more effective and efficient, therefore reducing total cost to serve for customers
  • Many providers, mainly since the pandemic, have already been working hard to reduce their real estate exposure driven by the increased use of work-at-home models (which have reduced since the pandemic abated but are still very prevalent in certain markets)
  • Additionally, we know from recent research that enterprises are increasingly looking to service providers to support them in deploying technologies such as gen AI. These providers bring a high degree of domain expertise and understand customer’s problems, and therefore, are best placed to deploy solutions using the latest technologies. This will present additional opportunities for providers who can demonstrate capabilities in this area

So why did I say it depends? I strongly believe that CXM service providers can thrive in this new market but need to embrace a new reality, which includes working hard in a number of areas.

Strategies for enhancing CXM provider success in a technology-driven market

  • Build solutions that address business problems – This entails not just the generic “reduce cost” or “improve CSAT” but real business challenges where CX can drive significant change in the business metrics
  • Demonstrate differentiation – With a large percentage of the market trying to move away from the traditional moniker of a “call center provider” and trying to demonstrate a shift toward digital solutions; it is important that they demonstrate, not just tell, the story of how they are solving real business problems for their customers by bringing together the power of their people with the available technologies to offer the best solution for the customer
  • Build strong technology partner ecosystems – Partnerships allow providers to deliver technology solutions across the customers’ journey – this includes, of course, the use of LLMs and gen AI, but can be as simple as having solutions in place to improve the employee experience or to provide timely insights through analytics. Most buyers want their providers to be able to bring an end-to-end solution and are no longer just looking for a provider that can only provide people. Humans, supported by and, where possible, improved by technology, are the type of solutions customers are demanding. Those that are pivoting in this direction can continue to grow their customer base
  • Develop flexible delivery models – Providers should leverage work at home as well as other sources of talent (GIG and Impact Sourcing, to name just two) to meet the changing demand both in terms of when support is needed and the type of skills that are required
  • Build commercial models that allow both parties to benefit from efficiencies – Commercial models should go beyond the traditional per FTE, per transaction, or per minute models and allow buyers to visualize and, more importantly, realize the value that a more efficient operating model can deliver
  • Use technology to solve operational challenges – This helps operations run smoother and more efficiently. While using all the technology available to resolve a customer’s issue is an obvious application, those providers that will thrive in the future will also be investing in technologies and skills within their organization that address operational challenges most effectively
  • Develop a culture that recognizes that revenue is not the only metric – While important, it is more impactful to focus on the margin of the work because as a business deploys more technology-led solutions, the revenue may decline, but the business that replaces it should be more profitable
    • This will also require a total evaluation of how people are rewarded within the business to recognize the value of deploying solutions that may bring lower revenue but provide a better and longer-lasting business benefit
  • Be forward-looking when it comes to skills that will be required in the future – Build location and talent strategies that will provide the talent required for the future in order to maximize the benefits available from a human and technology model
  • Develop strong account management disciplines – We know from recent studies that when there is limited differentiation in the market, as there is in the CXM space, the one deciding factor that tips a decision in the service provider’s favor is the strength of their account management
  • Use the technology to improve the employee experience (EX) as well as CX – Leverage the available technologies to remove mundane and frustrating tasks from employees, allowing them to focus on value-adding work. We all know that happy agents deliver a better experience

In summary, I am not pessimistic about the future of the CX arena. We know that the markets tend to overreact in the short term to new stimuli, gen AI in this instance, and underreact in the longer term, and this could be the same.

Will every provider in this space today be successful in three years? Probably not, but the size of the CXM environment (we estimate it to be well over US$330 billion, including insourced and outsourced activity) represents an excellent opportunity for those businesses that can evolve and meet the fast-changing needs of customers.

Navigating the Shift to Next-Gen Customer Engagement Technology Products in the Life Sciences Sector | Blog

Life sciences enterprises are undergoing a generational shift, transitioning from outdated legacy customer relationship management (CRM) systems to modern Customer Experience Platforms (CXP). Discover the three emerging customer engagement layers in these platforms, the readiness of enterprises to adopt the latest solutions, and the factors to consider when selecting customer engagement technology in this blog. Reach out to us to discuss this topic further.

In the rapidly evolving life sciences landscape, a significant and crucial transformation is underway as companies move from traditional CRM systems to cutting-edge CXP. Let’s explore this further.

As illustrated below, the life sciences CXP technology architecture has two distinctive foundational structures: CRM and next-gen customer engagement management.

Picture1 6

In the widespread realm of next-gen customer engagement management, the following three main customer engagement layers are emerging:

  • End-to-end content management: These tools provide features to enable intelligent content management across the entire content lifecycle, including automated and modular content creation, cognitive-capabilities-powered digital asset management (DAM), content distribution recommendations, real-time content analytics, dynamic libraries, and third-party integrations
  • Engagement channel optimization: Tools that manage all channel types (digital and non-digital) with CX-focused capabilities, including dynamic recommendations based on customer behavior analysis (personas), ideal content-channel combinations, third-party messenger integrations (including regional requirements), and channel analytics
  • Commercial learning and training: Embedded platform features to enable complete learning experience management (preferably covering the entire commercial function), including smart assistant-led training navigation, multi-format training modules, and personalized learning journeys

Enterprise adoption priority

The pandemic has reshaped customer engagement channels, resulting in a diverse blend of traditional communication methods (face-to-face, phone, text, conferences) and digital channels (video calls, webinars, Healthcare Professional Portals).

Picture2 7

This shift has made it essential for enterprises to adopt an efficient channel management system. As a result, engagement channel optimization has become the most demanded module in next-gen customer engagement management, followed closely by content management and learning and training.

While the life sciences commercial segment is synonymous with sales and marketing, it also includes other vital functions such as medical affairs, market access, and patient services. However, not all functions within the commercial segment are equally equipped to adopt these tools.

The overall maturity of the necessary technology, data architecture availability, and optimal processes vary significantly by function. These factors will influence platform and tool selection decisions as illustrated below:

Picture3 2

Customer engagement technology platform sourcing factors 

Enterprises looking to make sourcing decisions for next-gen customer engagement platforms and tools have moved beyond considering pricing as the sole or major driving factor. They are looking at platforms and tools that offer a better user experience and a flexible technology stack that seamlessly integrates into existing systems.

Picture4 1

“We prioritize how the platform fits with the existing enterprise tools and how well they work with current enterprise CRM and incorporate enhancements that come from them. Additionally, geographic infrastructure to provide support in global adoption, ease of working with the provider, and the price are the key criteria for selecting the provider.”

 – Director, Content Strategy and Operations, Large Pharmaceutical Company

“Our top sourcing considerations include ease of use for all stakeholders, user friendly and intuitive design, how well it integrates with other platforms, cost for implementation and the licensing fees, and product enhancements included in the fee or for small service fees.”

– Global CRM Lead, Global Life Sciences Enterprise

Outlook for the life sciences landscape

With enterprise objectives constantly shifting and generative AI technology continuously evolving, the innovation pace on the supply side is equally frenetic. Commercial technology players are swiftly rolling out highly tailored solutions in the life sciences industry. This rapid progress also gives rise to a new wave of specialized providers catering to niche needs. Consequently, enterprises must continuously assess the evolving landscape of commercial technology offerings and enhance their tech infrastructure accordingly.

To discuss customer engagement technology trends in life sciences or other developments in this space (especially after the Veeva-Salesforce announced split), contact [email protected], [email protected], or [email protected].

Watch our LinkedIn Live session, Key Insights: The Evolving Commercial Technology Landscape in Life Sciences, to learn more about the critical shift from CRM ecosystems to CX platforms and the next-gen technologies poised to deliver personalized CX.

Implementing Gen AI for CXM: The Data Challenge | LinkedIn Live


Implementing Gen AI for CXM: The Data Challenge

View the event on LinkedIn, which was delivered live on Wednesday, April 17, 2024.

🚀 Generative AI (gen AI) has the potential to revolutionize customer support, as well as reduce operational costs. However, to leverage gen AI for its maximum capabilities, it will be vital to base AI learnings on excellent quality data that is well managed and controlled.

📣 Watch this LinkedIn Live session with Everest Group’s David Rickard, Partner, and guest David Ilett, Consulting Director from Davies, to explore practical examples of implementing gen AI for customer experience (CX). Learn about the main challenges organizations face with data provision for AI and understand how to plan adequately to avoid the common pitfalls. 📊

During this engaging LinkedIn Live, we discussed:

⭐ The main challenges facing enterprises when deploying gen AI 🌐
⭐ The scale of the data provision challenge 📈
⭐The practical steps that organizations can take to leverage gen AI


Meet the Presenters

Rickard David
Everest Group

Breakdown: CX Leaders Spooked by Gen AI Data and Compliance Snafus | In the News

Decision makers in the CX space are almost entirely sold on generative AI (gen AI). Nevertheless, many can’t shake off the nightmare scenarios that the technology could bring in matters of data security and compliance.

Data security and compliance are the issues of most concern for CX leaders seeking to deploy gen AI in their organizations, according to a recent survey by Everest Group and TELUS International.

Read more in Nearshore Americas.

Leveraging Gen AI to Enhance CXM: From Innovation to Implementation | LinkedIn Live


Leveraging Gen AI to Enhance CXM: From Innovation to Implementation

View the event on LinkedIn, which was delivered live on Thursday, February 29, 2024.

🌐 While we recognize the huge potential of generative AI (gen AI) in enhancing Customer Experience Management (CXM), the questions on everyone’s mind are: How do we make it work in real-world scenarios, and where do we start?

Watch this interactive LinkedIn Live session to hear from Arte Merritt, Founder of Reconify, and Everest Group analysts, Shirley Hung and Sharang Sharma. We explored the roadmap for gen AI implementation, discuss what global businesses are considering in terms of deployment, address challenges, and examine whether companies should take on this journey independently or collaboratively.🚀

During this event, we dove into questions such as:

  • 💡 Where do you start with your gen AI journey for CXM?
  • 💡 What areas should you be looking at immediately for implementation?
  • 💡 How do you co-innovate to minimize risks?

Meet the Presenters

Hung Shirley
Everest Group

Nearly 75% of Enterprises Pivoted to Text-based Generative AI to Improve Operational Efficiency | In the News

Over 45% of enterprises identify the lack of internal technical expertise as a major barrier to generative AI implementation.

According to the recent Generative AI in CXM Survey Report by Everest Group and WNS, 75% of enterprises are elevating their business strategies by piloting, deploying, or scaling up text-based generative AI solutions, followed by 62% for code generation and 52% for image generation.

Read more in Analytics India.

Call Center Technology Needs a Platform Approach | Blog

It feels like the more technology a company deploys in its call center, the more it results in the worst customer experience possible. What used to be a personal conversation with a specific person is now a proliferation of technology channels that create more complexity for the customer and the company. Whether companies recognize it or not, in making these investments, they have assembled a digital platform operations model where the technology and the people in call center operations have become more intertwined. The problem is they did not adopt platform thinking.

Read more in my blog on Forbes

The Generative AI Advantage in Enterprise CXM Operations | Webinar

on-demand webinar

The Generative AI Advantage in Enterprise CXM Operations

Enterprises are embracing generative AI’s transformative potential in today’s rapidly evolving CXM landscape. As businesses strive to stay competitive and adapt to changing market dynamics, they are increasingly exploring its power to deliver personalized customer experiences.

In this webinar, our analysts discussed how enterprises are looking at generative AI-based solutions adoption to improve CX and contact center operations, the business impact of generative AI, and what we’ve learned about this revolutionary technology that can drive future growth.

What questions has this webinar answered for the participants?

  • What are the key areas in which generative AI is being deployed for CX services?
  • How positive are enterprises about generative AI implementation, and how are they going about it?
  • How do we expect generative AI-based solutions in CX to mature?

Who should attend?

  • CXM strategy/global heads
  • CXM outsourcing heads
  • CXM strategy heads
  • Customer service heads
  • CXM service delivery heads
  • Supplier and vendor managers
Practice Director
Rickard David

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