DEV Community: Priya Kumari

Why Will Credit Unions Embracing Technology Have a Competitive Edge in 2023?

Priya Kumari — Wed, 07 Dec 2022 06:01:49 +0000

Introduction

Credit Unions are financial cooperatives that provide various financial services to members. Credit unions have traditionally been located in the U.S. but have recently expanded overseas.
Credit unions are different from banks in many ways. They are owned by their members and do not make a profit for shareholders. They also serve their communities through various charitable activities.

Credit unions can be found in most localities across the country, but they generally offer fewer services than banks. Most credit unions do not provide checking or savings accounts, but they may offer other kinds of accounts, such as CDs or money market accounts. Some credit unions also offer certificates of deposit (CDs) that allow investors to lock up funds for a set period of time without paying interest on those funds until the maturity date, at which time investors can redeem their CDs for cash.

Credit unions are starting to embrace technology, and for a good reason. As the financial world becomes increasingly digital and as young people seek more flexible banking experiences, credit unions have an opportunity to attract new members and customers. But not all banks are embracing tech in the same way—and they shouldn't be left behind. Let’s examine how credit unions embracing technology will have a competitive edge in 2023.

The one-size-fits-all Model for the Credit Union is Gone

The one-size-fits-all model for the credit union is gone. It's time to adapt, evolve and change with the times.

The credit union must be able to adapt to the changing needs of its members and provide a digital experience that meets the needs of younger generations. In addition, they must be able to do this while still remaining financially sound enough to serve their members well in other areas, such as investments and lending services.

Younger Generations Have Higher Expectations for Their Financial Institution (FI)

You may wonder what the younger generations look for in their credit union. The answer is simple: they want to be engaged with their financial institution.

Millennials and Gen Z want their FI to have a mobile app to access accounts on their own terms. Millennials also value convenience and accessibility when making payments or transferring funds from one account to another.

A Credit Union Experience Must Be Digital and Human

The credit union experience must be digital, but it also has to be human. A digital experience should be tailored to the member's needs, and a human one should be personalized. The two experiences need to work together in order for them to create a unique experience for each member.

Engage with Members on Their Terms to Drive Loyalty

Meet members where they are. Credit unions have a unique opportunity to engage with members on their terms because most of them still use traditional technology. But by embracing modern technologies like chatbots and social media channels, credit unions can connect with their customers in ways that are more relevant to them than traditional banks or financial services providers.

Use technology to build trust. Trust is one of the most important factors when it comes to customer loyalty—and if you want your members to trust you enough to open a new account or otherwise engage with your brand, then building an online presence will help establish credibility while also providing valuable information about what makes your company different from others in its industry space (or category).

Start Thinking Differently about Lending

If you're a credit union, it's important to think about how technology can help improve your overall customer experience. We've already seen that technology has been used to improve the member experience by making it easier for them to use their accounts and make payments online. In 2023, we'll see more banks using technology to improve employee experiences as well.
A great example of this is how Wells Fargo recently launched an app called "Wells Fargo on Your Way," which allows customers who are driving through certain states (like Texas) access information about where they need gas or if there are any service stations open nearby while on the road! This app helps customers avoid wasting money while they're away from home and makes sure they don't forget anything important such as food items needed at home, after stopping at one stop along their way.

Conclusion

We're seeing a shift in the way credit unions are looking at technology. We're not just talking about financial applications and apps but also human-centric experiences that make members feel welcome, valued, and connected. These are the kinds of things that will help credit unions compete with larger institutions that have more resources at their disposal and can attract top talent from other organizations. It's also important to remember that these trends aren't going away any time soon—they carry over into future years as well! As we move forward to 2023 and beyond, keep an eye out for things like this happening again at your local credit union or community bank (if not already).

3 Simple Tips That Companies Must Employ to Make 2022 the Year of AI Success

Priya Kumari — Fri, 21 Jan 2022 12:26:58 +0000

Despite the proliferation of artificial intelligence, particularly in the post-pandemic era, the harsh reality is that AI deployments still have a considerably high failure rate. Modern industrial organizations are looking to redefine their complex processes with greater resiliency, flexibility, and agility to better adapt and respond to the changing market conditions. Artificial Intelligence (AI) has emerged as a key enabler of the industrial digital transformation and allows marketers to leverage the shifting market conditions. AI makes for a compelling business case as AI-powered automation not only promises to help marketers enhance productivity and operational efficiency but also helps them accelerate their journeys to net-zero targets.

While there's absolutely no doubt that AI is the future, before taking a plunge marketers must know some other things as well. As AI deployments have an extremely high failure rate, and a staggering 80% of AI projects fail (source: Gartner), the blog highlights some of the steps that marketers can follow to make 2022, a year of AI success.

Addressing the following three challenges can lay the foundations for successful AI implementation and can help industrials achieve real business value from AI as quickly as possible:

a) Finding the Right Use Case

Ensuring that your AI use case aligns with your business objectives and data availability is critical for successful AI deployment. However, equally critical is to demonstrate the viability and get buy-in from all stakeholders. However, demonstrating the viability and getting buy-in is also critical for all stakeholders. The million-dollar proposition though is selecting the right use case.

Marketers must choose a use case that demonstrates a clear value or achieves a key benefit. A good example is one that sustainably cuts down operational expenditure and helps in the optimization of productivity. Secondly, the marketers must see whether the use case already has data that can be worked with. AI thrives on data and must identify trends, correlate behavior, and must ultimately deliver predictions that can help one control processes and manage their assets. Therefore, the marketers must pick a use case where they are already collecting the relevant data.

Additionally, marketers must check whether their use case has a quantifiable Return on Investment (ROI). Whether your project may be successful on a small scale, the value may come to a standstill if one cannot lead an enterprise-wide deployment. One must therefore select a use case where they can measure ROI and can demonstrate value to the upper management in a language that appeals to them. Taking this point further one needs a use case that is easily scalable to other processes. This way, the learnings of the project can be applied to other functions to fast-track your AI deployment.

b) Extracting Deeper Insights From Data

Typically industries collect a massive amount of data but struggle to derive actionable insights for them. This problem can be addressed by leveraging digital tools that have been designed specifically for industries. Generic AI tools that fit all enterprise sectors such as financial, retail, etc. are geared to address general issues and need to be built to take into consideration the nature of problems to be tackled in an industrial option. Consequently, this also means that the gains from AI deployment using generic AI tools will be minimal. Simply, industrial companies need data analytical tools and AI platforms to handle the volume, variety, velocity, and veracity of industrial data and the dynamic environments that manufacturers operate in.

One must lean on the right digital tools that can provide you with critical insights into your business needs. The tools also offer solutions to improve your operational efficiencies. One must also learn how to improve plant operations, enhance quality, reduce waste, optimize energy consumption, decrease asset failure, accelerate net-zero ambitions, and more.

c) Accelerate the time to impact

Typically industries work with data scientists and external consultants to make sense of data. However, since they are not domain experts, this approach ends up complicating the delaying the deployment. Using a digital tool that empowers your workforce is critical to accelerating the time to impact your business. Instead of empowering the data science specialists, the marketers must put the power of AI in the hands of the industrial workforce viz. their ML engineers.

If your engineers are not trained in AI, they might struggle with it. However, many of the AI solutions available today can be entirely automated. These solutions don’t need data science or coding expertise. These solutions are designed to make AI accessible to industrial engineers, so that they can define and develop real-world use cases, quickly extract value from data, and can drive impact across their operations. Your ML engineers better understand your business and hence can lead your AI initiative.

Wrap Up

Amidst a business landscape where digital transformation has been augmented, marketers must stay relevant to their business requirements and must get a competitive edge. Addressing the above-mentioned three key challenges helps businesses leverage the power of AI to drive a greater level of profitability and sustainability while empowering their workforce.

How Conversational AI Will be the Cornerstone of Technology and Innovation in 2022

Priya Kumari — Wed, 15 Dec 2021 16:12:44 +0000

All of us have heard of the modern superhuman agents. These are gifts of the technological advancements in the field of artificial intelligence (AI) and machine learning (ML). The use of these tools will be crucial for the technological advancement of the companies in 2022 and in order to provide them with a competitive advantage. These latest tools have the potential to transform the potential of contact center agents. However, understanding how to apply these technologies before, during, and after customer contact is the first crucial step.

What is Conversational AI

Conversational AI is the set of technologies behind automated messaging and speech-enabled applications that offer human-like interactions between computers and humans. Most of the conversational AI agents are based on Voice Tech: Siri, Alexa, and Google Home.

Even modern chatbots fall under this category.

How Conversational AI Is Indispensable to Your Customer Engagement

Customer care has achieved new benchmarks in modern times as researchers, academics, and innovative organizations all have come together to produce a seemingly never-ending wave of tech-based breakthroughs. The use cases for artificial intelligence, automation, and analytics have proven to be increasingly expanding and are making these technologies fixtures in virtually every executive boardroom discussion.

Many companies are implementing targeted digital technologies in their contact centers. At the very core of this approach is embedding the right tools in the contact center to create impact. This involves routing calls to the agents best equipped to handle them and ensuring that agents on focus on optimizing the human interactions and on empathy. The proliferation of digital transformation, the recent transition to cutting-edge technologies, and the use of conversational agents to investigate customer issues and solve queries effectively are the trends that are only going to multiply in the year 2022. This will allow technologists to investigate customer issues and solve queries efficiently while capturing lessons to continuously improve.

Weaving all these technologies together to drive and optimize customer engagement is tremendously complex and a wide array of available tolls further cloud the way forward. Most pioneer organizations are setting up the trend by taking a holistic view on how to improve user experience and then setting the tone up with the technology that can deliver specific capabilities. Collectively, these applications and use cases reflect a future state, wherein technology is intertwined with operations to support and drive the human agents at every step of the process.

Chatbot Use Cases

The Contact Center Agent of the Future

Technological advancement is the key to enabling personalized assistance for each customer – the 'care of one.' The concept is based on data collected before, during, and after an interaction and requires the aggregation and use of data across channels, journey flows, and systems. Both humans and technology are needed to provide personalized customer care. In the coming year, technology won't completely replace humans but rather facilitate and support intense human-machine interaction and collaboration.

For example, each contact center agent could be supported by a virtual agent assistant, a behind-the-scenes bot that actively supports the conversation. This intelligent bot powered by natural language processing (NLP) and next-generation machine learning techniques will be quietly monitoring every call or chat and equipping the agent with personalized advice: What are the customers' intent and past actions? What are the customers' feelings? What is the best next action? What are the most relevant insights and guidance from our knowledge management system? These conversational agents fully free-up agents to fully focus on applying judgment by supplying information from different systems and handling administrative tasks. Thus, the conversational agents enable solving problems with creativity and creating a connection with the customers.

The Road to Enablement

The sheer size and complexity of incorporating these technologies into contact centers mean that it will take time to achieve this future state despite the daily advances in computing power, algorithms, and data volume. Quite quickly, organizations can start capturing value by harnessing the full functionality of existing technology and redirecting resources to focus attention on the care of one. The recent proliferation of digital customer care capabilities – for example, digital self-service tools such as apps and chatbots, interactive voice response (IVR) systems, NLP, real-time coaching, and augmented reality – makes it possible for companies and agents to adopt the care-of-one mindset without sacrificing cost and revenue targets. To highlight how specific technologies can be applied before, during, and after the call to improve agent performance.

Intent Recognition

Entity Recognition & Slot Filling

Named Entity Recognition

Dialogue Management

Conversational Design Choices

The following are the design choices in the conversational AI platform:
a) Automation bots – These bots employ frameworks like Rasa or Google Dialogflow to get information from the end-users, fill slots and send them to the backend.
b) FAQ/Questioning Answering Bots: With these bots slot filling is minimal and marketers need to use an information extraction system from a Knowledge Base (KB).
c) Chat agents like Replika are employed for generating the generative models

How to Get Started

The marketers must first define their problem and must narrow the domain when designing a conversational bot via automation. A huge focus of the end-users is on the conversational experiences and therefore and therefore designing bots who are more like a friend should be a priority for the marketers.

If the bot is like a friend, the marketers must automate the bot and see if there's enough data available. Such robots make conversational datasets available. One, however, needs to define the intents, entities, and slots (for the information that one would like to highlight), scenarios (intent-action sequences)

How to Create the Training Dataset

When it comes to defining the TF-IDF one needs to split the intent and merge on entities

Using Language Models

If you have a little amount of data, use language models like T5 to augment your data in a natural way. The markdown tools must be sparingly used:

Using Language Models

Marketers must use language models if they don’t have a narrow domain chatbot.

Embedding Choices

• SpaCy has currently languages in more than 17 languages
• BytePair Embeddings supports 277 languages & is a lightweight language
• firstText supports 157 languages and is heavy
• Huggingface models support 251 languages

Handling Fallbacks

• One can determine an NLU Fallback Threshold
• One can even go over the misclassified intents during cross-validation
• Marketers can even analyze the confidences and determine a fallback threshold
This is how UX assists in handling fallback scenarios.

Why One Shouldn’t Use Generative Models

The Dawn of Intense Human-Machine Interaction and Collaboration Begins

In the coming year, technology will be an ultimate enabler; however, it wouldn't replace humans and would support intense human-machine interaction and collaboration. Technological advancement is the key to enabling personalized assistance for each customer – the 'care of one.' The concept is based on data collected during, before, and after an interaction and requires the aggregation and use of data across channels, the journey follows, and systems. Both humans, as well as technology, are needed to enable personalized customer care.

For example, each contact center agent can be supported by a virtual agent assistant, a behind-the-scenes bot that actively supports the conversation. This intelligent bot, powered by natural language processing (NLP) and next-generation machine learning techniques will be quality monitoring every call or chat and equipping the agent with personalized advice: What are the customers’ intent and past actions? What is the customers’ feeling? What is the best next action? What are the most relevant insights and guidance from our knowledge management system? By supplying information from different systems and handling administrative tasks, these technologies free-up agents to fully focus on applying judgment, solving problems with creativity, and creating a connection with the customers.

Enabling Your Conversational Network

Despite daily advances in computing power, algorithms, and data volume, the sheer size, and complexity of incorporating these technologies into contact centers mean that I will take time to achieve this future state. Organizations can start capturing value by leveraging the power of existing technologies and redirecting resources to focus attention on another one. The recent proliferation of digital customer care capabilities – for example, digital self-service tools such as apps and chatbots, interactive voice response (IVR) systems, NLP, real-time coaching, and augmented reality – makes it possible for companies and agents to adopt the care-of-one mindset without sacrificing cost and revenue targets. The users must ask themselves how specific technologies can be applied before, during, and after the call to improve agent performance.

How to Use Virtual Workforce as Effective Solutions to Improve Productivity

The customer care organizations across the globe were forced by the COVID-19 pandemic to rapidly move their agents to remote work. The disruption possesses the potential to rapidly lower costs, improve innovation, reduce processing times, and optimize the employee satisfaction indexes. To unleash this potential, customer care leaders across the globe must discover ways to create a supportive environment for agents while facilitating processing, engagement, and collaboration. In order to foster virtual collaboration, the organizations can leverage a variety of tools that mostly fall under the following categories:
a) Tools for Communication
These tools support synchronous and asynchronous communication activities such as real-time remote discussions and presentations, desktop sharing, mobile screen mirroring, virtual team meetings, channel-and-group-based instant messaging, whiteboard use, and the use of email.
b) Team Collaboration
Companies can organize teams and their work product by leveraging tools that support activities such as file sharing, especially for large documents and version control; project planning and management; task management; single-source documents; tracking of issues and bottlenecks; real-time project updates; group calendars and event schedule.
c) Writing & Editing
This set of tools helps teams to create, publish and manage documents. These include the wikis and the online document-processing tools such as joint whiteboarding and central knowledge spaces.
d) Engaging & Networking
This set of tools is primarily meant for social media, networking, and fun activities, including offer pools, designing surveys, forums, ideation platforms, retrospective tools, and ones with features such as upvoting, designing interactive team quizzes, and interactive Q&As.

Benefits of Employing Virtual Workforce

a) Innovation and Virtual Teams
Collaboration tools can boost productivity and unlock innovation by enabling virtual teams to work together across geographies, functions, and organizations.
b) Human-to-Human (H-2-H) Collaboration
Video conferencing has been amongst the most important enablers of collaboration when it comes to handling virtual teams. However, interoperability across video systems has been a headache for some organizations. To solve this issue, organizations are increasingly moving towards solutions that do not rely on propriety systems such as Zoom.
c) Getting the Right Answers at the Right Time
AI-enabled search tools for the search features of collaboration are critical in large organizations. Without a search, the organizations can find it difficult to provide the right data to the right people to enable productive working sessions.
d) Speed, convenience, and flexibility
Tools, for speed, convenience and flexibility include the ones for instant messaging to increase efficiency by eliminating the need to travel for in-person meetings. These tools also offer added convenience for employees who have flexible hours and work remotely.

Risks Associated With Virtual Workforce

There is a potential decrease in productivity by increasing multitasking and context switching. Frequent notifications and flashing or beeping lights can interrupt productive working sessions.

Employees might also feel overwhelmed when information comes through too many channels.

a) Difficulty Managing & Protecting Information
Collaboration tools especially instant-messaging tools such as SMS and WhatsApp have been designed to make tasks easier for the employees. However, issues can arise when confidential data is generated in these channels but no clear owner has been designed to archive, store or delete information.
b)The lines between Work & Personal Time are being blurred
Employees working from home and staying constantly connected through virtual communications channels can find it challenging to keep work from infringing on their home lives.
Effective collaboration continues to be an important factor for optimizing workforce productivity and inspiring innovation. Consequently, discovering better tools for collaboration will always be the priority for customer care leaders.

How Live Touchpoints Will Make an Impact

Live touchpoints with customers – such as call, chat, or messaging will always be important for marketers. However, these conversations will be most effective when agents can focus on complex interactions. In order to ensure that agents concentrate on the highest-value voice interactions, customer care leaders must first implement the auto-response and self-service options to handle the most frequent transactional interactions.

How to Quickly Address the Root Causes

When one tries to address an issue, 66% of customers begin with self-service before reaching out to an agent or virtual agent. Organizations should equip their customers with technology to solve their problems via continuous updates of self-service channels such as the web knowledge base, FAQs, community forums, apps, and websites. Advanced analytics, machine learning, alongside speed and text analytics can be dynamically used to analyze large volumes of contacts and generate insights about contact drivers, self-service leakage, repeated intersection bursts, and channel switching. Companies can use these insights to efficiently update self-service information and functionality.

Reach Out Before Customer Do

Proactive conversational AI platforms can resolve requests before customers even feel the need to reach out. Modern solutions integrated with various data systems can analyze large quantities of internal and external data and can identify triggers to start proactive and personalized conversations through the channels that customers prefer.

For example, a leading telco was able to eliminate 50% of unnecessary service calls and inbound calls related to repairs by using robotics to proactively contact customers and resolve issues as soon as a malfunction is detected in remote monitoring.

Deflect with cognitive agents

Two-thirds of customers believe through online channels and mobile devices should be faster, more intuitive, and should be better able to serve the needs of their customers.
With improved front-end robotics or "virtual agents" organizations should seize the opportunity with improved front-end robotics or "virtual agents" to handle repetitive transactional requests as well as to guide customers through a logical menu of topics and intensions to address issues. Companies that have incorporated such technologies have witnessed significant returns. In fact, effective deployment of conversational AI can create a twofold improvement in customer experience; reduce the cost to serve by 15 to 20 percent and can optimize churn, helping upsell, and acquisition by 10 to 15 percent; and this results in a fourfold increase in employee productivity.

During the Call

As the industry is rapidly evolving to prioritize digital modes of communication, the majority of customer respondents still prefer to use voice channels to resolve more complex issues. Retaining the human element and striking the right balance between human and digital customer service will lead to more satisfied customers. To optimize the efficiency and overall service quantity, top organizations are enabling agents to focus their entire attention on value-added tasks while optimizing costs.

Match ‘alike’ personalities

Instead of assigning customers to agents automatically or through simple rules, organizations are using advanced analytics and machine learning to route calls. Modern techniques draw on data about individual callers (for example, from external databases and internal CRM data) and agents (such as past performance and call history) to match calls with best-suited agents. This approach results in more successful interactions, improved agent performance, and ultimately, better call outcomes.

Know Your Customers

Knowing the history of a customer is no longer a competitive advantage, but a must for organizations that want to keep their customers satisfied. More than three-quarters of customers expect a service representative to be familiar with them, the product and service history, and information. Next-generation agent desktops and knowledge management systems start by combining multiple communication channels (for example, webchat, email, and SMS) with internal and external customer databases into one simplistic view. Organizations then layer in AI-enabled customer analytics, suggestions for next-best actions, recommendation engines, product and offer analytics, conversational profiling, and risk identification. A single portal provides all the information and context that agents need to provide fast service and ensure smooth cross-channel transitions.

Best Emotional Connection in the Moment

Up-skilling people is more critical for organizations now than ever before. With robotic and cognitive technologies handling simple queries, the agent should focus exclusively on consultative conversations with the customers. Many organizations are leveraging real-time coaching and training tools powered by deep learning and behavioral science. Such tools measure thousands of quantitative and qualitative metrics in real-time – tone of voice, speed, pauses, volume, keywords, compassion, and more. AI analyzes the conversation and nudges the agent on-screen with recommendations if it detects an issue. For instance, when it comes to customer care, modern organizations are applying modern algorithm innovations and overlaying information from a customer's smartphone screen directly to the agent's desktop. The software powers agents by providing additional visual guidance to improve the accuracy of real-time decisions, support, and recommendations.

After the call

Once a call is completed, agents often have a few minutes of downtime that they typically spend on correcting the administrative tasks. However, contact centers could improve efficiency by implementing back-end robotics to handle simple tasks, feeling agents spend more time enhancing their skills through quick, and personalized training sessions.
Monitoring and Optimization of Agent Performance
The biggest cultural and organizational changes of next-generation performance management will be based on personalized, real-time coaching with near-constant feedback for agents. Modern performance management operating systems use AI and NLP to visualize role-based data, identify improvement areas, and continuously monitor performance at the individual and team levels. These insights are used to tailor coaching and training to personality, skills, and motivation. Next-generation systems also include personalized targets for agents, gamification to spur healthy competition, and self-learning recommendation engines. Collectively these tools motivate and train agents while they wait for their next call.

Understand Your Back-End Operations

Several capabilities such as process discovery or process discovery or process mining, offer process insights that can reduce the burden on agents and improve performance and overall customer service by quickly identifying non-intuitive opportunities for digitization and automation within contact centers. For example, managers can use computing vision applications to determine the number of time agents spend on specific activities and to untangle the granular workflow of tasks, activities, and events that agents perform.
Who is responsible for high-priority processes? Are people engaged and productive? What are the sources of lost productivity? These applications can answer all of these questions and others.

The tools for robotic process automation (RPA) can handle all non-value-added back-office tasks. Automation can be used to replicate human work in a cost-efficient way by handling repetitive processes and tasks through virtual rule-based robots.
Data integration, manipulation, and analysis can be facilitated by converting unstructured analog data flow into structured digital flows. This exercise can help optimize customer experience by enhancing the quantity and quality of data inputs, which accelerate analytics, suggestions for next best actions, recommendation engines, product and offer analytics, conversation profiling, and risk identification. A single portal provides all the information and context that agents need to provide fast service and ensure smooth cross-channel transitions.
A major focus of marketers should be on boosting emotional connection at the moment. Managing people skills and upskilling them has never been more critical for organizations than now. Marketers now have robotic and cognitive technologies handling simple queries, the agent should focus exclusively on consultative conversations with the customer. To support these interactions, many organizations are using real-time coaching and training tools powered by deep learning and behavioral science. Such tools measure hundreds of quantitative and qualitative metrics in real-time including tone of voice, speed, pauses, volume, keywords, compassion, and more.

AI analyzes the conversation and nudges the agent on-screen with recommendations if an issue is detected. For instance, an AI coach may suggest that the agent shows more empathy or speaks at a different speed to build a better connection. This support can help agents come across as more confident or speak at a different speed to build a better connection. With this support, agents can come across as more confident and empathetic, which in turn can improve customer experience, sales and can boost the retentions.

According to research, while it’s impossible to control customers’ actions, a fully engaged phone professional is the one who listens and expresses a genuine interest in resolving the situation will foster the type of partnership with customers that is necessary to ensure more engaging and successful conversations.

Selecting the Right Technology to Support Agents

Organizations need to realize that the creation of super-human agents requires a large number of technological solutions. This might be a key challenge for organizations that are intent on achieving this vision. The tools included constitute only a small part of the solution and keeping the human element intact is still paramount.

The customer care organizations should select a few tools as a starting point and prioritize their implementation based on the contribution of each tool to the pre-defined business goals. The following 5-step process has proved effective for a wide array of customer care organizations already:

Define business success in hard numbers
Build a driver tree to highlight the driving factors that influence those KPIs
Stimulate different interventions by applying them to the driver tree and determine which of the changes will have the most lasting impact
Marketers must scan the market to stay abreast with the latest cutting-edge tools and should allow the latest products to shape their marketing strategies
The B2B marketers can also track KPIs before, during, and after the implementation of the prioritized tools which is critical to measure the impact of the investments

Wrapping Things Up

Ushering in the era of superhuman agents wouldn’t be an easy task for the marketers heading to 2022. It’s also not going to be automatic and a comprehensive solution with too many moving parts. The companies that get it right ensure that the benefits they reap are worth the investment. Moving ahead in 2022 as the world will be reeling from the pandemic, the customer care queries and their volumes will spike. Remote working will become a standard practice for contact centers, and organizations will have the unique opportunity to make significant progress.