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Transforming the Enterprise and Call Center with Intelligent Automation (IA)

5 Capabilities Intelligent Automation (IA) Solutions Must Deliver to Align with Customer Demands

We live in a world that is connected, mobile and demanding. Enterprises must use Intelligent Automation to gain a better understanding of their customers’ demands, behavior and sentiment. This is essential to successfully manage the customer experience. Especially when today’s customers have other options, high expectations, and access to multiple channels of engagement.

Intelligent Automation Solutions

Managing big data resulting from everyday business with customers, employees and internal activities is another major challenge. It is almost impossible to analyze big data and produce actionable knowledge using manual methods. Other challenges include the lack of unification among enterprise systems and the absence of business process automation.  Deficiencies in producing real-time and holistic views of the overall enterprise operation pose a final challenge.

Conventional workforce optimization (WFO) solutions are not adequate since they do not make use of intelligence-based automation. They use an “inside-out” approach that focuses on aligning customer service with internal business processes.  IA-driven solutions use an “outside-in” approach that aligns business processes with customer demands.

CXM Driven by Intelligent Automation

To cost-effectively deploy IA solutions to most functions of an enterprise, solutions should offer 5 major, generic capabilities:

Capture

Access, capture and record data, media and KPIs from every entity engaged in enterprise functions. This includes data and media from telecom platforms, service request routing, customer engagement, multichannel interactions, transactions, IoT devices, CRMs, and ERPs.

Unify

Manage, normalize, convert, categorize, and prepare the captured data for the next steps of processing and analysis.

Analyze

Multichannel and cross-channel analytics use the unified datato produce actionable knowledge and insightful trends.

Decide & Learn

Rule-based or AI-driven decision-making and learning machines use the actionable knowledge and trends to automatically determine next best steps and actions.

Act

Automatically launch the best actions, reports and notifications determined by the decision-making machines.

The advantage of such capabilities is that they can intelligently automate enterprise and contact center functions related to both customer experience management (CXM) and business process automation.

Empowering enterprises to cost effectively and intelligently automate and unify customer experience management and business processes.

Organizations can intelligently automate the entire CXM process and customer journey before, during and after service. This includes customer service routing, engagement, processing and feedback management. During engagement, IA drives other applications such as automated QA and compliance management. IA also impacts voice and text-based Intelligent Virtual Agent as well as intelligence-based voice applications such as fraud protection and discovery of sentiment. Business process automation is enabled through intelligent robotic process automation, unification and process automation among dispersed enterprise systems engaged in delivering certain enterprise functions.

Deployment of and transition to Intelligent Automation solutions requires customer assistance programs to assure success and a rapid return on investment. Suppliers of Intelligent Automation solutions should offer customer-centric programs like consultations and proofs of concept.  Intuitive tools that help customers map their business processes to IA solution configurations should also be made available. Solutions offered as both on-premise software or SaaS make acquisition easier and help organizations meet their business and financial requirements.

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Customer Experience Management Powered by Intelligent Automation

Customer Experience Management Powered by Intelligent Automation

Customer Loyalty vs. Customer Satisfaction

All enterprises should strive to create positive customer experiences that lead to customer loyalty. Customer loyalty is different from customer satisfaction.  It establishes a long-lasting relationship with customers. It is an ongoing process, not a single set of actions. Therefore, enterprises should develop a strategy for customer experience management.

Companies first focused on customer interactions by capturing and analyzing customer calls, emails and chat. Agent training soon followed to better serve customers during interactions. This approach helped to achieve customer loyalty, but it ignored other steps of the customer journey critical to Customer Experience Management (CXM).

4 Segments of Customer Experience Management

Customer experience management demands a view of the entire customer journey, consisting of the following four segments:

  1. Routing customer service requests to the right organization and agent rapidly with no need for the customer to repeat information
  2. Managing interactions for the best outcome for the customer
  3. Processing customer service requests quickly and accurately
  4. Capturing and analyzing customer feedback from all customer touch points during and after the completion of service, making changes and taking action toward improvement.

intelligent automation

Intelligent Automation Technologies Greatly Power Customer Experience Management

Enterprises can face major challenges in establishing these four critical segments effectively. This is where advanced Intelligent Automation (IA) technologies greatly enhance CXM programs.

The core components of IA is commonly used the same way in all four segments.

  1. Data and media capturing, unification, and big data management performed on all areas critical to the customer journey. This includes telecom platforms (network routers, IVR, PBX, ACD, etc.) and key performance indicators from workforce optimization, workforce management, customer relationship management and enterprise resource planning.
  2. Multichannel analysis (speech, desktop and text) of unified data and the creation of actionable knowledge
  3. Learning Decision Making Engines (LDME) driven by Artificial Intelligence (AI) further analyze actionable knowledge, make best decisions, and learn from historical data and analysis
  4. Automated actions driven by LDME launch actions and automate functions

 

Artificial Intelligence and Learning Machines are Key to Making IA a Practical Solution

customer journey

In customer service routing, IA automatically captures, monitors and analyzes the status and performance of all entities engaged in the customer journey. Routing makes the best decision and launches the action to intelligently route the service request in real time. It also captures customer information from each touch point and deposits it in a single place accessible to all agents and systems. This prevents customers from having to repeat information.

IA captures and analyzes customer interactions (calls, emails, chat, desktop transactions) to automatically conduct quality assurance, compliance management and customer sentiment analysis. Real-time coaching, workflow automation, reminders and notifications help automate agent interactions. Recent developments in AI-based chatbots and Intelligent Virtual Agent (IVA) technologies automate customer interactions while reducing enterprise expenses.

When it comes to processing customer service transactions, IA utilizes Robotic Process Automation to process repetitive tasks in various processes without errors. IA utilizes Business Process Automation to perform data collection, unification and analysis of transactions to automate business processes.

Finally, IA captures customer sentiment from every customer touch point during and after service. This can include social media content and customer surveys. IA analyzes the data and provides actionable knowledge to LDME that can offer conclusions, trends and actions.

Each of these four steps is designed to improve systems, processes and the interactions engaged in the customer journey.

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What is a Call Center? A Modern Primer

Call centers are offices staffed with representatives who either make or receive phone calls.

Call centers employ many staff in customer service, sales and support functions.

Call Center Introduction

A call center is an office where a company’s inbound calls are received, or outbound calls are made. Call centers are increasingly popular in today’s society, where many companies have centralized customer service and support functions. Call centers employ many staff in customer service, sales and support functions.

Call centers are often large offices staffed with representatives who either make or receive phone calls. Depending on the size of the call center, a single office could have anywhere from a few dozen to hundreds of telephone staff. Depending on the needs of the company, call centers can make either incoming or outgoing calls, or both.

Some call centers focus on answering inbound calls, such as a bank that gives out a toll-free number for customers needing assistance. In that case, call center representatives can give account balances and take loan applications over the phone. Other call centers focus on outbound calls, such as a survey company. In that case, survey representatives make outbound calls to ask people to answer survey questions over the phone.

Almost every company or enterprise has a need for call center. Call centers provide a number of advantages to companies. By centralizing telephone-based service and support in one location, companies can easily adjust staffing to match call volume. Call centers can be located almost anywhere, allowing companies to take advantage of time zones and cheaper labor rates in different states and countries. Call centers also centralize the technology needs of companies, allowing major telecommunications setups to be installed in a small handful of call centers instead of a number of smaller offices, making upgrades and training easier to complete.

Inbound and Outbound Call Management

Many call centers use a number of different technologies to help improve performance and customer experience. Inbound call centers often use automatic call distribution (ACD), in which incoming calls are assigned to representatives on the order they are received, or assigned based on their skills.

Inbound call centers also use a technology called Interactive Voice Response (IVR), in which an automated recorded voice presents a menu to the caller to choose from by dialing numbers or speaking the choice.

Outbound call centers may use Dialer technologies. Dialers can automate the outbound dialing for representatives in which a list of telephone numbers are entered into the Dialer, and Dialer will dial those numbers automatically either after the agent has completed the previous call, or continue dialing the numbers on the list until a number answers and while the representative is waiting, in which case the Dialer automatically connects the answered call to the representative.

Workforce Optimization (WFO) and Workforce Management (WFM)

Call centers usually utilize call recording and monitoring (WFO), in which customer calls are recorded and monitored by quality assurance staff to ensure that phone representatives meet customer needs. Quality assurance and agent performance scoring are critical functions in improving the performance of call center representatives. There are software technologies and applications, called workforce management (WFM), used to effectively schedule call center agents based on the volume of calls during the day, week or month. This schedule management will prevent over- or under-staffing the call center.

Other technologies, such as Performance Management (CCPM), are available to call center managers to define their Key Performance Indicators (KPIs), measure, report and manage the performance of their agents and call centers. In recent years industry vendors have provided to call center software technologies that can perform speech and/or text analytics. Analytics technologies can assist in automating and optimizing work required to monitor, measure and qualify call center transactions and/or agent interactions with customers.

The collection of all of the above technologies, called Workforce Optimization (WFO) and Workforce Management (WFM), can be used to automate and optimize the call center transactions, functions, customer interactions and quality-compliance management. Call center technology evolves constantly, helping call center staff assist customers more efficiently and effectively.

Hierarchy of Call Center and Enterprise Technologies

Multiple categories make up today's complex call center environment.

From connecting to the outside world, to customer support programs, call centers are a vital part of modern business.

Call Center Outsourcing

Call centers have been increasingly popular as outsourcing increases. With outsourcing, companies contract out some functions to other companies. As it can be expensive to maintain call center equipment and staff, some companies choose to outsource their telephone functions to an external call center. In this case, external call center staff can be trained to answer phone calls from a number of different companies.

 

Evolution of the phone: Why the phone lies at the heart of business

 

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