A Smarter Contact Center for Employee and Customer Experience


3 min read

The Landscape

How AI Can Deliver Powerful New Ways for You to Engage Customers

For years, customer service has prioritized cost containment and contact deflection. But today, rising customer expectations require a more strategic and responsive contact center environment that can also foster brand identity and customer loyalty.

In an era where one bad interaction can lead a customer to abandon a company, businesses need to find efficiencies that can help modernize their contact centers. They must become support organizations that focus on the customer experience, and shift from sales or product-centric priorities to a service-centric one.

Even in the best of times, customers are ready to abandon a brand after only three unsatisfactory support interactions. 1 Among millennials, 22% said just one bad interaction is sufficient cause to leave. 2

The growth of self-service channels like communities and virtual agents impacts the skills and technologies service agents need. These channels offload routine customer issues and allow agents to solve more complex customer cases, both at their desks and in the field. When companies embrace these efficiencies and incorporate them both on the employee and platform sides, they are able to build better employee and customer experiences.

AI for Business

We live in the era of digital business, where customers demand timely, accurate and personalized experiences. Businesses are looking to change their contact center from a cost center to an engagement center. Using contact centers as a focal point to anticipate, understand and deliver against customer needs is a powerful advantage in earning customer loyalty. 3 AI can uncover powerful new ways for you to engage your customers through your contact center.

This year, AI investment is increasing by 31%

Which AI Solution is Best

Each contact center’s needs vary by industry, complexity, and volume of cases. Before deciding which AI solutions and technology to implement, it’s important to first audit your contact center from a holistic perspective. Understanding where your business falls in this matrix on the next page will help you prioritize different initiatives as you look for a partner to help you on the digital transformation journey to become a smarter contact center.


4 min read

The Contact Center Maturity Curve

Mapping Out the Opportunities Across Your Transformation

One of the biggest challenges of innovating a contact center is mapping the full extent of the transformation. The maturity curve presented below is an example of the timeline and stages to a mature contact center. Timelines and progression for each company will vary depending on size, complexity, and business needs.

The stages of the maturity curve are not a linear progression, but rather an aggregate of common components often found at each stage. You may find that your business aligns more with one stage, while already using components from other stages.

Use the maturity curve as a guide to benchmark the current state of your contact center and identify possible next steps.

Single Contact Management

Companies are at the beginning stages of building their contact center. Most are using legacy or homegrown systems to manage their service teams and customers. Customers are primarily funneled through a single contact channel, leading to multiple service gaps in access, time-to-resolution, and case management prioritization.

Experience Management

Contact centers at this stage are focused on building a positive experience for their customers. Case management and workflows have been implemented and customers are able to reach support through a handful of basic channels and are beginning to look at adding omnichannel capabilities. Companies may also have some knowledge management embedded into their contact center and are able to see some reporting and insights from their activity and improve upon their customer experience. When companies establish this multi process, single function structure, they experience 25-50% improvement in expected outcomes.

Relationship Management

Contact centers in the relationship management stage are doing just that—managing and building a relationship with their customers. They are focused on furthering the relationship with each touch point, wherever that touch point is. Customers are able to effectively self-service and connect with agents through omnichannel digital experiences. Deeper analytics, basic AI, and field service capabilities are available to support agents for a more connected experience. Basic AI typically involves a stand-alone product or service like a chatbot, and not an integrated AI platform with a strategy.

Lifecycle Management

Companies at this stage have a fully mature contact center that’s capable of supporting a customer throughout their entire lifecycle with the company. AI capabilities are embedded to extract data from both inside and outside the company, which informs more comprehensive insights and recommendations for agents to use. A multi-cloud approach allows the company to easily share data between teams and identify opportunities to cross-sell, up-sell, and exceed customer expectations. Companies may also have explored IoT as a possible channel to grow into next. At this level of lifecycle management, companies have a multi-function business platform, and can experience 50-70% improvement to expected outcomes.


4 min read

AI for Employee Experience

Aligning Contact Center Outcomes with the Agent Experience

Your customer service agents are at the heart of your contact center. They are your first interaction customers have with your company and represent your brand at every customer touchpoint. IBM Watson Assistant is a conversational AI platform that helps your agents provide fast, straightforward, and accurate answers to customer questions. It can address common customer inquiries across any device, application, or channel. Implementing AI gives employees time and space to focus on higher-level problems that require a more human approach. This can also improve job satisfaction and reduce turnover among customer service employees.

How your agents interact and resolve inquiries is a direct reflection on your business. The agent experience also directly impacts business outcomes. By focusing on what your contact center is hoping to achieve and aligning your contact center goals with your business strategy from the start, you can make sure your AI use cases will deliver measurable business results.

Example: How Bradesco Pays Personal Attention to Millions of Customers

Bradesco Bank in Brazil partnered with IBM to increase their speed of service, while improving the level of personalization for their 65 million customers across 5,200 branch locations. Watson Assistant was implemented and trained on the nuances of the Portuguese language, as well as the business of banking. Now Watson is trained on 62 products and answers 283,000 questions a month. 4 Watson Assistant is often paired with Watson Discovery, IBM’s enterprise AI search capability, to help agents quickly comb through massive amounts of data to provide customers with the right answers, as quickly as possible.

Watson answers Bradesco questions with a 95% accuracy rate

Insight: Helping the Contact Center

There are multiple ways that virtual agents can assist a contact center:

Workload management

Many queries can be resolved without a human agent, with the assistance of digital labor. For example, businesses can provide automated answers to frequently asked questions, as well as new questions. Have operating hours or return policies changed? Digital agents can easily adapt to new FAQs, which leaves human agents available to assist with the more complex customer inquiries.

Agent assistance

When human agents are unseen by customers, it’s easy for them to use a digital assistant to gather additional information such as suggestions to resolve customer disputes, opportunities to up-sell, and possible technical responses. Virtual assistants with AI-powered search capabilities can help deliver faster answers to complex questions – drawing from a growing and ever evolving set of documents and web content.


Virtual agents have a variety of ways to utilize robotic process automation, allowing them to update and ingest even handwritten documents. With machine learning and optical character recognition, they can help move workloads or even complete certain processing altogether.

Pre-screening and smart routing

Digital agents can compile and gather relevant data so a human agent has it on-hand when a query is escalated, reducing frustration and the time spent handling the query. When multiple queries are incoming at one time, companies can use digital agents to help triage and decide how they should best be routed.5

Surface valuable insights

Traditional search engines do not provide exact answers for employees and customers. But Watson Discovery delivers specific answers to queries and uses conversational AI to find answers, while also providing the entire document and supporting resources to allow your employees and customers to make informed decisions. Watson Discovery is able to understand business documents and is powered by machine learning, both which help to find answers to specific questions.6

Provide context

Previous customer interactions with a company can be traced by virtual agents and applied to new interactions, leading to faster request resolutions and new insights.


5 min read

AI For Customer Experience

Connecting Consumer Insights to Action Using AI

Customers are the focus for every contact center. When designing contact center interactions, it’s essential to focus on what your contact center is ultimately hoping to deliver to your end consumers.

Customer behavior has shown that customers appreciate having multiple engagement channels from which to choose. By having contact center touchpoints across different applications, devices, and channels, customers are empowered to pick the one that best suits their immediate needs and desired level of engagement. A growing number of customers prefer using self-service channels to find their answers, as tools like virtual agents allow customers to interact and receive support when convenient. For example, accessing a chat after-hours can help customers get the help they need without waiting to call a human agent the next morning. For omnichannel support systems to work seamlessly, both virtual and human agents need to be able to access the same customer data and knowledge.

Conversational AI has also advanced to meet customers by using natural human behavior and wording to classify text. Instead of having to fit within a virtual agent’s limited, linear processes, natural language processing can detect multiple languages, understand sentiment in customer reviews, flag comments on social media that are inappropriate, and improve the overall quality of a customer interaction. Conversational AI can help answer complex questions and carry out multifaceted conversations, giving customers more flexibility to use the self-service channel that suits their needs. Additionally, AI powered search speeds training of virtual assistants and dynamically extends and maintains their knowledge as information sources grow and evolve.

Using AI to Understand, Interact, Answer, and Guide

AI impacts what you understand about customers, how you interact with them, how you answer their requests, and how you guide employees with next-best-actions.


AI learns customers’ preferences and habits at an individual level, with scale. The integration of external data, such as social profiles and personality insights, empowers your organization and employees to personalize each and every customer engagement.


AI-powered chatbots, for example, can deflect inbound customer requests or automate repetitive tasks, which allows more time for sales and service to focus on customers and solve more complex problems.


AI can assist with deep knowledge discovery, helping client-facing employees accurately answer questions faster. AI can also monitor internal data to identify and surface patterns or trends, so employees spend less time mining through data and more time engaging and serving your customers for a better customer experience overall.


AI can learn from your data and instruct next-best-actions through predictive and machine learning models. AI can also be used for agent training to surface insights on how customers like to engage with support, route cases based on traffic variation, and employee skill development goals. This helps ensure customers have a more seamless experience when engaging with support, and have the right employee prepared to address their requests.

Example: How Generali is Building Better Experiences Inside and Out

Generali is the third largest insurance company in the world and needed a way to maintain their advantage in a competitive marketplace. Working with IBM Services and IBM Watson, Generali developed a roadmap for the company to better utilize AI in customer-facing processes. Together with IBM, they built two pilots - a virtual assistant called Letizia for clients to communicate with Generali agents, and an internal AI interface called Leo, both using Watson Assistant. 7

Generali saved $1M in the first year of deployment

Leo helped 8000+ Generali agents and increased productivity by 5%

Generali achieved rapid scalability of solutions globally


10 min read

The Strategic Partnership for Business

IBM Watson & Salesforce Einstein

A contact center’s ability to serve both its employees and customers is tied to the platform and technology on which it is built. When integrated into a broader platform, the contact center can leverage data from every customer interaction, ranging from websites and points of sale to previous service calls, to build a comprehensive understanding of each customer. Based on your company’s objectives and business goals, it’s critical to choose a platform that can keep up with the speed and dynamic scale of your organization’s growth, while also adapting to changing demand without disrupting current processes.

IBM and Salesforce have a strategic partnership committed to delivering on the AI promise of faster and smarter decision-making. With IBM Services, clients can rapidly deploy the combined IBM Watson and Salesforce capabilities. Together, they deliver unprecedented intelligence across industries, to help service teams connect to their customers in new and valuable ways.

IBM’s commitment to the Salesforce ecosystem helps contact centers of any size and industry create positive experiences on Salesforce Service Cloud that customers won’t forget, and agents won’t want to work without. For organizations with a mobile workforce, Field Service Lightning gives service organizations real-time visibility into how and where service technicians are assigned and gives these field technicians access to a 360-degree customer view and case context to quickly resolve service issues on the go. Community Cloud enables businesses to provide more personalized service to their customers. By empowering customers to solve their own routine issues via self-service, businesses are experiencing faster case resolution, reduced case volume, and higher customer satisfaction.

AI enables you to support your customers wherever they are, identify knowledge gaps, and automatically route cases to an available agent who can help resolve an issue.

Watson uses advanced AI capabilities with embedded machine learning to understand, analyze, and contextualize documents, files, cases, and more from diverse sources outside of Salesforce.

Einstein helps you discover insights and patterns in your data, predict business outcomes, get recommendations in context, and automate tasks.

Watson knows your business:

Unique company policies
How to surface insights from previous customer cases
The application of industry-specific information
How to connect data in multi-org environments
Information in multiple languages
Nuanced tone and sentiment of customers and their reviews
How to extract relevant insights from thousands of news articles

Einstein knows your customer:

The best product to sell, up-sell, and cross-sell
Service case predictions
How well a marketing email will perform
The lifetime value of every customer
Which customers are most likely to churn
Which leads and opportunities are most likely to convert
The sentiment and intent in text

Examples of the Watson & Einstein AI Partnership at Work

Here are a few examples of how Watson and Einstein can translate insight into action for your business.

IBM Watson:

Case Prioritization

Watson prioritizes cases based on topic and sentiment, so agents know which ones need attention first.

Question Assistance

Watson provides faster responses to customers’ questions.

Chatbots and Omnichannel Support

Utilize self-service and multiple touchpoints through chatbots, live chat, social channels, and more to lend support anywhere, anytime.

Cognitive Routing and Assignment

Watson classifies by issue and level of difficulty. Cases are automatically routed to an appropriate and available employee.

Support Search with Watson

Watson Discovery enables agents to search first to solve an issue before even opening a case.

Salesforce Einstein:

Einstein Discovery

Boost productivity and discover relevant patterns in all your data, whether it lives in Salesforce or outside.

Einstein Bots

Easily build, train, and deploy custom bots on digital channels that are connected to CRM data.

Einstein Case Management

Route and escalate cases automatically.

Einstein Next Best Action

Define recommendations, create action strategies, integrate predictive models, and more.

Einstein Mobile Service

Optimize Field Service scheduling with advanced mobile app.

How IBM Resolves Customer Cases 35% Faster with IBM Watson

IBM is using Salesforce Service Cloud with IBM Watson Services to scale personalized customer service across 170 countries and over 22,000 agents with a single view of the customer. Watson instantly surfaces answers to complex questions for live agents to solve customer problems faster than ever before and assists with case routing and prioritization.

11% cases deflected with IBM Watson in 2018

2M+ support cases assisted by IBM Watson each year

Up to 45 min saved daily


3 min read

Your AI-For-Business Partner

Becoming a More Strategic and Responsive Business with IBM

Re-evaluating and building your contact center with AI-powered technologies is not a project that should be taken lightly. Organizations that focus on customer experience and building intelligent workflows will find themselves delivering high-touch, seamless experiences, while those who miss the mark on employee or customer experience may see diminished returns for their efforts - particularly in an environment where business resiliency and continuity are more important than ever before. Here are a few steps to consider when reinventing your contact center:

Refer back to the maturity curve to guide you on where your contact center needs to evolve first.
Identify what your organization can do to support your employees first, whether that’s building more robust remote collaboration or cleaning up knowledge management.
Find gaps where AI can add immediate value. Start small, such as setting up a virtual agent to help deflect frequently asked requests.
Add on additional AI tools based on a time-to-value approach, such as exploring discovery or "next best action" technology to support your live agents.
Build feedback into your iterations. It's important to learn quickly and pivot if something is not working, and this will turn your agents into stakeholders of the transformation project.

AI is transforming how businesses operate and deliver value, while improving efficiencies across organizations. When we partner with businesses to create workflows that are more intelligent, communication and interactions can be more personalized, future outcomes can be shaped and influenced, and the businesses can adapt at the speed of change needed to meet their customer expectations. IBM can help your organization determine where you are in your AI journey, decide what next steps are needed, and help turn your aspirations and expertise into results.

Next steps

AI for Customer Service

AI for Customer Service

How to provide complete customer service with market-leading AI

Conversational AI

Conversational AI

Enable collaboration and robust conversational solutions with Watson Assistant

Salesforce Consulting Services

Salesforce Consulting Services

Transform your CRM organization and make better decisions by deploying Salesforce globally