Tag Archives: Technology Articles

AnswerNet Acquires Synergy Solutions

AnswerNet acquired Synergy Solutions in an asset transaction. Synergy Solutions specializes in high-touch consultative customer service and sales support programs for many of the nation’s leading brands.

Headquartered in Phoenix, Arizona, Synergy Solutions was established in 1999 and focuses on innovative customer interaction solutions. This allows Synergy Solutions to provide superior results for its clients in fast-growth retail and e-commerce, as well as traditional verticals such as healthcare, insurance, and financial services.

Gary Pudles, president and CEO of AnswerNet stated, “Synergy Solutions furthers AnswerNet’s continued growth in high-touch customer engagement space for well-known companies and brands. AnswerNet’s customer care business has been growing exponentially over the last three years, and adding the incredible Synergy team further deepens our strength in providing solutions that help our clients continually stand out in providing support to their customers.”

Synergy’s president and co-founder Lori Fentem is staying with AnswerNet and will work closely with Pudles on building and executing AnswerNet’s growth strategy. Fentem is a well-regarded leader in the contact center industry. “We are thrilled by the opportunity to become part of the AnswerNet family,” says Fentem. “This acquisition allows Synergy the ability to continue to offer high-touch customer experience solutions. I believe that integrating with AnswerNet will present the ideal environment for Synergy employees and clients.”

Automation Success Requires Human Involvement



By Dan Somers

Automation and artificial intelligence (AI) can help save contact center costs, but primarily it increases customer satisfaction by speeding up responses and reducing customer efforts. Contact center automation falls broadly into three categories:

  1. Speeding up or automating the helpdesk agent (staff who capture and triage queries)
  2. Speeding up or automating the case handler (staff who resolve queries)
  3. Increasing self-service automation (chatbots, searchable FAQs, and self-help tools)

AI Challenges

Certain limitations of AI cannot guarantee the accuracy expected by customers, however. Some of these limitations are temporary, such as the comprehension capabilities of speech recognition, which will continue to improve. But other limitations relate to how machine-learning robots work.

All machine learning relies on studying real-life training data to predict or classify current data. The training data needs to be “labeled”—that is, it must have an outcome or class (tag) assigned to it, as judged by a person. For example, if a query comes in that says, “My server has crashed and is showing a blank screen,” then the chatbot will assign the best label it has in its training set, which might be “server crashed.”

However, in this example, a label of “faulty screen” might be assigned instead. The customer would be annoyed if the bot attempted to address a faulty screen issue instead of a server crash. This is an example of potential ambiguity. Furthermore, new issues will appear from new product launches, changes in quality, and evolution in the market. Lastly, the way people describe or view the same problem is more variable for certain issues than others.

Human-in-the-Loop

The only safe way of deploying bots within a contact center is to have a human-in-the-loop. This person will validate what the bots are doing, preferably with minimal impact to the customer.

So, who and where is the human-in-the-loop? It turns out that there are four general ways for humans to validate some or all of the process:

  1. A helpdesk agent can validate suggested responses before sending.
  2. The customer can validate that the response—or the question they asked—was comprehended.
  3. A third-party solution provider can check the performance of the bots and curate the process; this might be an internal or external data science team.
  4. The knowledge base manager can check the bots for satisfactory performance.Automation of contact centers yields promise, although not without humans-in-the-loop to maintain its performance. Click To Tweet

Considerations of Humans-in-the-Loop

There are pros and cons of different human-in-the-loop approaches. Some of these points are technical in nature but have substantial implications.

Agent: Some solutions on the market have AI recommend the next “best response” for the agent. The agents validate the response, not the categorization. For example, if two queries—“The strawberries I bought were tasteless” and “The strawberries I bought made me sick”—both lead to the same recommended response, “We’re sorry; please accept our voucher,” then the categorization models will degrade as they are not being updated with the accurate root cause.

Also, the insight generated by the models won’t allow executives to monitor product quality, design, and usability to then generate the self-service tools that can reduce contact center traffic. With this solution, other humans-in-the-loop will still be required elsewhere.

Customer Validation: If customers provide the required validation, it is scalable, but customers may not like having to correct their original query or the responses. If the query produces a new category, then there must be a process to deal with it. Fundamentally, the system cannot be relied upon with just these humans-in-the-loop.

Solution Provider: This is the status quo for most machine-learning deployments in real-world environments: a data science team, either internally or a third-party, sets up, curates, and retrains the models on a regular basis to maintain their performance. The pros are that these are the only humans-in-the-loop required. The cons are that these professionals are in short supply.

Knowledge Base Manager: This role has the most hidden potential benefit for having a human-in-the-loop. In a nontechnical environment, they will provide business rules on how to handle queries, as well as the training, trouble-shooting guides, and fault tree analysis to resolve issues.

In terms of their day-to-day role, they will be aware of product launches and modifications, but they also can use the rich insight of the labels coming from the contact center (both triage and resolution) to make improvements to both the knowledge base and the process. This includes updating the FAQs so customers can better use self-service. Also, this insight can inform other functions, such as product quality, product design, and customer experience, to help guide improvements.

Optimized Learning

A new approach that only requires a few humans-in-the-loop can exist because of a new technology called optimized learning. This is a form of machine learning that builds models but invites training from a human in such a way to minimize human input and still provide maximum performance. It is ideal for spotting new signals and improving existing ones.

Optimized learning doesn’t need to be in-line and suffers from none of the downsides of other approaches. Instead, it requires a fraction of the labeling otherwise required, even in a changing environment. The implications of this are profound. It means that a call center would only need to retain a few agents after the automation implementation, and they would handle the training that the optimized learning invited them to do in an offline capacity. This would maintain the models for labeling queries to generate both automation and insight, thus speeding up and reducing issues.

The rest of the automation would come from the rules originating from the knowledge base manager, as informed by the bots. This paves the way for improving chatbots and self-serve, searchable FAQs to free up contact center staff.

Conclusion

Automation of contact centers yields promise, although not without humans-in-the-loop to maintain its performance. There are many different flavors for human-in-the-loop AI automation. With new technology appearing, an optimized system is possible with a minimum number of humans who don’t need any data science skills. There is now no reason why the contact center of the future needs to look like those of the present. The same applies for the customer experience too.

Dan Somers is the CEO of Warwick Analytics, which provides call center automation solutions to address voice of customer (VoC) data, chatbots, service desks, and complaint handling.

Artificial Intelligence and the Call Center



Predict Who Is Calling and Why

By Nancy Lee

Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. In computer science, AI research is defined as the study of intelligent agents: any device that perceives its environment and takes actions that maximize its chance of successfully achieving goals. The term artificial intelligence is applied when a machine mimics cognitive functions generally associated with the human mind, such as learning and problem solving. Artificial intelligence algorithms improve their performance automatically through experience by finding patterns in a stream of input, such as telephone automatic number identification (ANI) information.

AI in the Call Center

Artificial intelligence is nothing new to Amtelco, which started developing a unique dataset for predictive call handling in 2005—the Intelligent Series (IS) Clairvoyant Agent feature. The latest iteration of this development is the innovative IS predictive intelligence feature. Predictive intelligence uses the ANI for a call to recognize the caller, eliminating the need for operators to reenter information. Predictive intelligence determines who is calling and the most likely reason why.

Predictive intelligence enables the call center system to learn with each call it receives and progressively improves the performance of subsequent tasks.

Time-Saving Features

Predictive intelligence saves a tremendous amount of time for both operators and callers. Operators simply select the reason for the call from the list, helping ensure error-free information.

For multiple callers from the same phone number, predictive intelligence sorts the list of callers by the number of times each person has called and displays the list in a pop-up box. The most frequent caller from a number appears at the top of the list. The operator can quickly choose the current caller from the list, and predictive intelligence retrieves that caller’s information from previous calls. For each caller, the list of reasons for previous calls displays with the most frequent reason for calling.

The textbook for teaching the call center system about predictive intelligence is comprised of a script template, an SQL server database separate from the IS system database, and an administration script for managing the database. The script template is the starting point for creating new predictive intelligence functions within existing scripts and using it to direct the disposition of the call. The separate database makes it possible to track callers and their reasons for calling and provides information about past calls to the script. The administration script is a user interface that enables supervisors to easily create a customized list of reasons for calling without having to access the database.Artificial intelligence gives the adage 'live and learn' new meaning for call center systems and their human operators. Click To Tweet

Looking to the Future

Although advanced AI could replace or reduce the need for human interaction, reducing the workload on call centers by answering simple or commonly asked questions, it could also enhance human interaction to improve and streamline the customer experience. This would retain the personalized aspect of calls that human interaction provides while augmenting it with AI technology to provide higher-quality service.

Voice recognition technology can be coupled with artificial intelligence capabilities to offer adaptive response suggestions to operators based on key words and phrases. This would reduce wait times and enable agents to instantly respond to a wide variety of caller needs with appropriate solutions.

Tone and voice analytics can gauge customer satisfaction and agent friendliness and enthusiasm to help provide individualized performance assessments. This form of AI also could monitor agent and customer call temperaments in real time, alerting managers when a situation escalates and allowing them to listen or step in if necessary.

Artificial intelligence gives the adage “live and learn” new meaning for call center systems and their human operators. And there seems to be no limit to what call center systems can learn to make life easier for call center agents.

AmtelcoNancy Lee is in marketing and advertising at Amtelco, a developer and supplier of call center and communications solutions located in McFarland, Wisconsin. Contact her at nlee@amtelco.com

How to Ensure That Your VoIP-Based Call Center Is Always Online



By Steve Walker

The industry trend towards Voice over IP (VoIP)-based PBXs is causing a shift in the technology underpinning the call center business. VoIP PBXs bring with them tremendous features and flexibility, but they also create some unique technical challenges. Since a VoIP PBX is essentially software running on a computer, how will you keep your agents active and phone lines up when your VoIP telephony environment goes down?

Computer problems are not a question of if, but when. And VoIP PBXs are no exception. VoIP PBXs may encounter problems on their own (for example, a hard disk failure), network problems may block them, or they may go idle in the event of a local VoIP carrier problem. (VoIP call centers on the East Coast of the United States will remember an extended outage of a particular carrier in November 2017). Any one of these events (and more) can bring your VoIP telephony environment to a halt and idle your agents.

If you’re planning to deploy a VoIP-based PBX, you need to ensure that you implement high availability (HA). In simplest terms, HA means that if one PBX fails for any reason, another will rapidly take its place and restore telephony services. This is normally achieved through “clustering,” which means having a standby PBX ready to take over for the primary PBX if things go wrong.

If you ask your IT person about HA or clustering, you might get an answer well-suited to an office computer but not appropriate to a telephony environment. To design a HA solution suitable to a mission-critical telephony environment, you need to consider the following six criteria:

1. Autonomy

This criteria is the most important requirement when designing a HA telephony environment. It means that damage or failure of one PBX in the cluster cannot negatively affect the others; they must be autonomous (share nothing). Simple or cheap solutions share hardware, software, and disk drives between primary and standby PBXs. But enterprise-caliber solutions, including those serving public service answer points (PSAPs), must have fully autonomous cluster members. Make sure your clustered PBXs are fully autonomous.

2. Synchronization

The information held in the PBX must be kept consistent between the primary and standby PBXs in the cluster, so that either can take over for the other on a moment’s notice. Solutions that share data break the first rule of autonomy, but solutions which synchronize data are ideal. Look for a solution that synchronizes data, not one that shares a data storage device. Just as important, ensure that the PBXs will automatically turn off synchronization if one of them is in poor health. Sharing data that may be corrupted by a failing PBX can destroy the other one, resulting in the call center going off-line.

3. Failure Detection

Simplistic HA solutions define failure as a black-or-white scenario (for example, a power outage affecting the building shuts down everything). But VoIP PBXs fail in their own unique ways. A software bug might prevent the PBX from connecting calls, or a memory error may prevent calls from reaching agents. Enterprise-caliber solutions require sophisticated health sensing and failure detection. This ensures that the PBX is running and telephony services are fully functional. Avoid solutions with simplistic failure detection.

4. PBX Separation

While putting the primary and secondary PBXs side by side is convenient, it minimizes the magnitude of failures the cluster can withstand. Instead you will want to place one PBX in your primary call center and the other far away, perhaps in a different state. That way, if you suffer a local or regional power or carrier outage, the backup PBX running far away can take over. Then agents can connect with mobile phones or work from home. Note as well that simplistic synchronization solutions break down whether the two PBXs are placed far away or one is placed in the cloud. Therefore, make sure your synchronization solution can handle any degree of physical separation of the two PBXs.

5. Rapid Detection and Failover

Your call center will suffer immensely if it takes fifteen minutes for your PBX to detect that something went wrong, and it will suffer again if it takes twenty minutes longer to switch to the backup. And a lengthy outage may put your call center SLAs (service level agreements) or contracts at risk. Ensure that your HA solution can rapidly failover from one PBX to the other and that failure detection (health monitoring) can trigger a failover in under one second if things go wrong.

6. Encryption

If your call center handles personal health information (i.e., for a medical facility), then information contained in the PBX (such as voicemails) may be protected health information (PHI). Voicemails synchronized between the two PBXs may be deemed “ePHI in transit,” which could violate rules pertaining to the protection of this information. Regulations like HIPAA in the USA, PHIPA in Canada, PDPA in Singapore, and so forth may impact your HA solution. You must ensure that communications between the two PBXs are encrypted to secure that information; this will also help protect the PBXs from internet hackers.

Conclusion

These six criteria define a minimum set of capabilities your HA environment must meet to ensure you maximize PBX uptime and maintain the productivity of your call center. Since VoIP PBXs are fundamentally software running on a computer, you will find a range of HA solutions from free and open-source (generic computer HA) to commercial products specifically for PBXs.

As you select your HA solution, evaluate your options using this criteria to find the solution that’s right for you. Don’t wait until your first VoIP PBX outage to start implementing a high-availability solution.

Steve Walker is the CTO at Telium, a manufacturer of telephony and telematics solutions specializing in VoIP.

Machine Learning Puts the “Intelligence” in Contact Center AI



By Bob Kasten

With the advent of computers, thoughts quickly turned to speculation that a computer could someday match human intelligence. In 1950 Alan Turing devised the Turing Test that became a threshold for when a machine is said to become intelligent. The test uses a human evaluator that watches a conversation between two parties. The evaluator knows that one of the parties is a machine, and if the evaluator cannot distinguish between the human and the machine, the machine is said to be intelligent.

While the notion of artificial intelligence (AI) can bring thoughts of computers someday becoming self-aware, we do not have to worry about this just yet. In our era, AI has become an important tool that can be used in contact centers to become a performance differentiator.

Machine learning is a branch of AI. It uses data to feed algorithms that automatically learn and improve. Machine learning falls into two broad categories: supervised and unsupervised. In supervised learning, the output datasets are provided and used to train the machine and get the desired outputs for future datasets. Unsupervised learning does not use output data, but instead the data is clustered into different classes and then analyzed.Having a conversation in a text format gives the ability to mine agent and customer interaction. Click To Tweet

Many industry verticals have become commoditized to the point where offerings are similar or the same across the competitive market. This applies to BPOs (business process outsourcers) as well as the companies that use their contact center services. In order to gain and keep market share, it is essential to give a best-in-class customer experience. Machine learning can help with this process.

Contact centers generate a multitude of data. Data sources include systems for CRM (customer relationship management), billing, collection, agent QA (quality assurance), call recording, chat, email, CSAT (customer satisfaction), social media, and so on. All this data tells a story about the customer and the contact center’s interaction with them.

The recent progress made in AI parallels similar progress with voice recognition and natural language-processing technology. It is now possible to convert real-time conversations or voice recordings to text with a high degree of accuracy. Having a conversation in a text format gives the ability to mine agent and customer interaction.

The easiest way to understand how data and machine learning can work together in concert is to describe a common scenario. The process uses an archetype that can be applied generally to supervised machine learning.

Here is a list of generic process steps, followed by a specific example that uses a voice recording as the data source. Note that the data could come from any of the above sources.

  • Identify data source: Locate a voice recording.
  • Generate learning data: Convert the voice into text.
  • Machine learning analysis: Process text data.
  • Machine learning correlation: Connect success and failure outcomes with patterns in the agent and customer conversation. Find out how the best agents generate success. Identify the criteria of the call that causes the interaction to be successful. The output of this step will produce actionable insights.
  • Make improvement suggestions: Use the insights from the previous step to make enhancement recommendations. Improvements can come in many forms, including agent training as well as agent and customer matching. This provides real-time customer data the agent can use during future sales opportunities or script changes.
  • Implement recommendations: Take action by improving the script or training the agent.
  • Predict success: The insights gained from machine learning can be used to predict the likelihood of success. A benefit of predictability is that an action can be taken based on the predicted behavior.
  • Feedback: Verify that agents are using the training recommendations by running the process iteratively to confirm that the feedback is contributing to attaining key success metrics. Feedback is also used in the success prediction.

Determine what successful agents say is the basis for building on that foundation and give it to agents who are not as successful. Once you know the why of success, you have taken the first step in answering how to improve it. Positive customer experience plays directly into understanding the success equation. A customer who makes a purchase or gives a positive customer satisfaction rating for the service they received will be identified by using the machine-learning process.

Other data sources can be added into the model to improve the predictability quotient. CSAT could be used to help further identify success patterns. Another possibility is using customer attributes that can be obtained commercially. Commercial data includes purchase habits, household income, age, gender, home market value, and occupation.

These data marts are a good way to give agents more direct information about customers. In addition, they are used to improve the accuracy of the predictive modeling. Customer attributes are used to enhance the customer experience and increase the likelihood of success. Many attributes about the customer that are found using their phone number or email address can give further insights.

Using a computer-generated call that speaks as if it were a human being brings this model full circle. This application has been deployed in the past couple of years. It still has a long way to go, because customers can tell the caller is a computer rather than a person. In 1950 Alan Turing probably never envisioned that his Turing Test would be used with automated dialing systems.

Using machine learning in conjunction with learning from the mined voice text, with the advances in natural language constructs, brings new opportunities, as seen with assembly-line automation in the early twentieth century. Calling and speaking using a computer reduces staff and leads to labor cost savings. It should be noted there are TCPA requirements, as well as state and federal laws, that should be thoroughly understood and followed before using this type of technology.

When we get to the point that a customer cannot tell that a machine called and is speaking to them, the Turing Test will pass, and the machine will be considered intelligent. Once that happens, we may be closer than we would like to the day when computational awareness becomes a reality.

 Bob Kasten is the founder of contactcentertools.com. His tools provide a holistic suite of agent performance management modules that includes KPI performance tracking dashboards, voice analytics, QA scoring, knowledge testing, goals, coaching, and secure clean desk agent communication. He spends his time consulting on contact center information technology projects and enhancing his agent performance management tools. He can be reached at bob.kasten@contactcentertools.com or www.linkedin.com/in/bob-kasten/

Add Resilience to Your Call Center

By Wayne Scaggs

Do I get up after a knockout event? My first, second, and third answer is “yes.” Why? It’s because it is in me to find a way over, around, under, or through the issue.

For the purpose of this article, issue refers to your call center system, the beating heart of your business. The processors in your system clock millions of cycles per second, and the software sends the data you need through wires to the screen or printer to provide the information needed.

I do not know who discovered the following proven method of troubleshooting, but I will say that I have used it and it often works. One of the first places to start to look for issues in your system is to verify what is happening between the keyboard and the monitor. This should be approached delicately, because you do not want to disrupt the balance that exists. It can be a tremendous time-saver when this intricate part of your system is at its peak form.

Here are some of the mitigating approaches to data loss you may want to consider to protect and preserve your company’s most valued resource: the data on your servers. This information is based on our experience and research in creating both the hosted and cloud systems that protect and preserve our clients’ data. We are required to protect and preserve that data. Click To Tweet

Procedures you may want to have in place and verify their readiness include Windows updates, snapshots, planned failover, checkpoints, server replication, virtual servers, SQL transaction log shipping, backups, and spares. All procedures may not be applicable to all systems; use the procedures that work best for your business.

  • Windows updates can be an issue. Sometimes they won’t let you shut off your computer or allow you go to work until the update is completely installed. Updates break things, and updates rearrange your comfortable setup that you worked so long to get the way you wanted. Something to remember about Windows updates is that they help keep your computers secure, and the longer the time between updates, the longer it takes to update your computer. More importantly, you cannot operate your business without computers and computers must be updated; it’s mandatory.
  • Snapshots of your server are taken at an instance in time, which you can go back to in order to restore your computer to the time the snapshot was taken. You should use snapshots before a major update or component change-out. Snapshots are performed automatically, and there is a limit to the number of snapshots before they are overwritten.
  • Planned failover is used when you want to use a different server for operations and replicate back to a server. This method keeps the operating server and the replicating server in sync.
  • Checkpoint is a manually created mirror of your server used to retreat to a known working point of your server.
  • Server replication is a scheduled event that replicates your server—both the operating system and all the programs.
  • Virtual servers can operate multiple servers in one physical computer. The physical computer has enough resources (disk drive space, processing power, and memory) to accommodate servers that require fewer resources. A virtual server can be used to house your replicated server. If a failure occurs on your operating server and you have that operating server replicating to a virtual server, you can now bring your virtual server online and continue to operate your business while the failed server is being attended to.
  • Transaction log shipping is a SQL server tool to reestablish your SQL database back to a point, determined by the frequency of the transaction log shipment. To make the transaction log work, you must have a separate and complete SQL server where you can ship the transaction logs.
  • Backup options include online storage, flash drives, physical hard drives, and cloud storage. Performing multiple routine backups and maintaining off-site storage is mandatory.
  • Spares could include virtual servers, disk drive raid arrays, network switches, backup Internet access, and backup online servers.

We live in a software-driven world, with software controlling the data of our businesses; we are required to protect and preserve that data. This article provides a view of a variety of systems from a higher level. Know what you have in place, and then choose to incorporate other options that add resilience to your call center.

Wayne Scaggs is the president of Alston Tascom, provider of call center database information and network telephony systems.

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How to Use CRM and Live Chat in Your Call Center

Transform Your Call Center Agents into Customer Experience Ambassadors

By Chris Frascella

In the last decade there has been a vast change in the approach to customer service. Millennials (officially the largest living generation) may be to blame for starting the revolution, but the desire for a more centralized and omnipotent form of customer service is now a universal expectation.

Shrewd industry leaders have recognized the trend and have been transforming what were once simple call centers handling incoming customer complaints into teams of brand ambassadors. Consequently, call center teams are being reorganized, reenvisioned, and tasked with delivering consistent, centralized, and exceptional service to customers no matter what channel they use. Today, live chat is often a key component of call center service offerings.

Innovative Creation or Frankenstein’s Monster? Unfortunately, many agents have to rely on legacy processes from the old call center model: tools that aren’t suited to meet today’s customers’ more demanding expectations. Even centers that have the appropriate tools have often purchased and deployed them over time, leading to a confusing patchwork of log-ins, dashboards, and permissions.

Customers expect agents to know their preferences and history as soon as an interaction begins. They don’t want to wait while agents look up their records, and they won’t tolerate having to give the same information over again. It is impossible to deliver on a promise of centralized customer service when you have siloed information stuck in disparate systems. Agents will struggle, key performance indicators (KPIs) will fall, and customers will end up leaving even more frustrated than when they arrived with their problem or question.

Knowledge Plus Performance Equals Power: Implementing a customer relationship management (CRM) system and an enterprise-wide live chat platform can make a significant difference in the quality of customer service you deliver. Exceptional CRMs contain an incredible amount of valuable information that can inform agent-customer interactions throughout the organization, but if the information is locked in a system that is difficult or time-consuming for agents to access, its impact on actual service quality is limited.

Deploying a system with integrated CRM and live chat within the call center gives agents the tools they need to truly engage users and accurately measure and analyze results. Here are a few examples of how an integrated CRM/live chat system can transform both the agent and customer experience:

Provide Agents with a Single, 360-degree View of Customers: Customer experience agents should never have to log in and out of different dashboards and navigate through various screens to get the information they need. At the simplest level, a CRM/live chat integration allows support staff to instantly view extensive customer data without ever leaving the chat window. This includes purchase history, service records, past interactions, location, and contact information. One-click access to a 360-degree view of the individual with whom they’re chatting lets agents focus fully on their current interaction with the customer rather than on finding and accessing records.

Capture Sales Leads Immediately: If a call or live chat event uncovers a potential lead, a truly integrated system allows agents to easily capture the critical information the sales team will need right away and within the live chat window. This kind of digitally facilitated handoff creates a culture of collaboration and continuous improvement between dispersed call centers, sales teams, and marketing departments.

Build a More Robust Cache of Customer Record with Ease: Customer records locked in other call center or live chat systems lead to siloed knowledge and information gaps, so getting your staff to actually use your CRM is not always easy. Agents should be engaging your customers, not transferring data from one system to another.

Integrating enterprise live chat and a CRM platform allows agents to work in one place. This will minimize the administrative burden, increase CRM adoption rates, and lead to more knowledgeable service and sales teams – as well as happier customers.

Chris Frascella is the director of partner marketing at Velaro.

Fight Social Engineering of Call Center Agents

Make Your Priceless Data Completely Worthless to Combat Fraudsters

By Ben Rafferty

When a new wall goes up, criminals will always search for a door in or a way around. It’s in their nature, and it’s ultimately what fuels them. We are witnessing this transition in the cybersecurity space today.

Companies are investing more in defending their security perimeters and are using daily penetration testing to identify and remedy holes a hacker could potentially exploit. According to the SANS Institute, about 9 percent of IT budgets have been allocated to security in 2016, up from 4 percent in 2014. So-called next-generation endpoint products will surge to a predicted level of nearly $4 billion by 2020. Cyber criminals are watching a substantial wall being built between them and their targets. The skill set required to obtain the same valuable information is increasing and ever-changing. Or is it? Just because some direct methods criminals used in the past will no longer be available to them, unfortunately there’s always another way.

Security involves people and processes in addition to technology. The most logical weakness is the human component – you and me. Hackers caught on to this years ago, and we’ve become incredibly familiar with weak spots that result in “social engineering” attacks that often involving tricking people into breaking normal security procedures. Phishing emails hit our inboxes daily, trying to convince us to approve wire transfers from our “boss,” or click a link to “save” our sick Aunt Nancy, potentially installing malware, or more recently, ransomware.

What to Watch Out For: Digital disruption in the financial industry has led to a rise in third-party payment systems. The Amazon Store Card, Apple Pay, and Google Wallet are just a few examples. And with them, we’re far less likely to actually use our credit and debit cards at the point-of-sale. In fact, our physical use of cards is arguably becoming obsolete.

This trend isn’t going anywhere, and because of it we will continue to deliver more of our personal and account information over the phone, email, and Internet to banks and retailers without thinking twice. But when this information reaches the contact centers that facilitate these interactions, it can be a goldmine for fraudsters and criminals – especially with the rise of massive data breaches exposing huge amounts of personally identifiable information (PII).

Most organizations don’t have the time to carefully vet every phone and digital interaction in order to ensure they are not being socially engineered. If a caller provides accurate information, it’s often all he or she needs to pass through the gates. And we’re not just talking about one crafty individual pretending to be someone else; criminal groups have systematized these intelligent attacks.

One year ago this seemingly simple tactic wounded one of the tech industry’s biggest players, Apple. A flurry of fraudsters took advantage of the Apple Pay authentication process by convincing contact center employees to activate Apple Pay accounts with stolen credit card information. The actual Apple Pay activation was then initiated between Apple and the bank, and Apple gave the bank stolen credit card information to open the account, including the details relating to their iCloud.

Vishing or “voice phishing” calls involve a series of phone calls to a contact center, each one taking minor actions to slowly gain incremental access to an account or turn off alerts by warning of an impending “trip out of town.” Essentially, in two or three phone calls, criminals are able to escalate privileges into user accounts and commit fraud. In this particular instance, fraudsters loaded iPhones with stolen, card-not-present card information and turned that data into physical cards via Apple Pay. This type of attack is very difficult to identify and defend against because one contact center might have thousands of agents, and it’s highly unlikely an attacker would reach the same agent twice.

How to Stop It: Social engineering in the contact center environment is something US organizations have to address, and fast. But unfortunately things are likely to get harder before they get easier.

A US-wide move to chip-card technology has the potential to grow the threat of these attacks. While the transition is intended to help reduce overall fraud rates – its introduction in the UK reduced card-present fraud by 32.5 percent in seven years – in reality it is more likely to simply shift the ways fraud occurs. Fraud that leverages a contact center environment is likely to be exactly where most new fraud attempts will occur, a trend already seen in the UK, according the UK Payments Administration.

Humans have always been, and always will be, the weakest link in the security chain. As more and more cyber criminals target contact centers, contact centers must do everything they can to make sure criminals are not able to socially engineer their employees.

The most effective means of stopping this – and many other types of fraud – is to ensure that even if the human element is misled, other measures are in place to prevent the looting of payment cards and personal information. Many would agree that an effective means of protecting against social engineering is to simply leave the data in some format unusable by the criminals.

For example, tokenization can be used to replace sensitive data with a unique and meaningless equivalent (known as a token) that has no exploitable value. This token is then stored by a tokenization system and acts as an empty stand-in and director for the sensitive information. Many organizations use this to increase the security of critical data and keep it out of the reach of cyber criminals.

Technologies will improve, but humans will always be duped. Acknowledging and preparing for that eventuality is the only true way we can combat social engineering.

Ben Rafferty is the global solutions director at Semafone.

The Call Center Meets Cyberterrorism

By William Lane

Like it, or not, your call center is connected to the Internet. Whether you utilize a premise or cloud-based model, PRIs or VoIP, are located in Bar Harbor, Maine, or Los Angeles, California, or have four agents or 1,004, you are dependent on the Internet in some way. The bad news is that every person, business, organization, and government connected to the Internet is vulnerable.

Vulnerable to What? A few of the threats facing all of us every day include distributed denial of service (DDoS) attacks, malware, toll fraud (international calls being made from your switch), phishing, crypto-lock attacks, and unfriendly probes. Having antivirus software from a leading company is not enough.

Not only is there an explosion of malware (some estimates are as high as 200,000 new malware samples released every single day), but research shows that only 5 percent of threats are actually identified by existing security software, and in the majority of cases the average time-to-detection rate takes two months (Marc Goodman, Future Crimes).

Our networks, computers, switches, and every other device connected to the Internet are vulnerable to attack. Some of the bad actors are out for the lulz (the fun of it), but an increasing number are out for money. If you don’t believe me, try searching for ransomware.

Your Network, System, or Switch Is at Risk: Some attacks are direct, some are indirect, some (as mentioned above) are just for the fun of it, and some are malicious, purposeful targeting. Often victims of cyberterrorism are merely collateral damage. For example someone releases a malware to Windows, and every Windows user gets the sickness. Or a bad actor releases a web crawler, and it identifies an open public port on your switch, notifies the perpetrator, and your telephone bill goes up thousands of dollars until you notice the charges on your invoice. Experts estimate that some form of cyberterrorism will affect one in eight businesses each year, and the threat is only growing.

So, after painting this bleak picture of the vulnerabilities of contact centers (and everyone else, by the way) being connected to the Internet, what can be done to protect critical systems from cyberterrorism?

  • Be Aware: Understand that every system is vulnerable; so prepare for how to deal with the various challenges before an attack occurs. Don’t be blind to the very real threats that are growing daily; plan contingencies on how to keep your business running should such an attack occur.
  • Practice Safe Software Management: Ensure that all available updates are installed quickly. This will mitigate exposure to known threats. For instance, Microsoft does not even issue security updates for Windows XP anymore. Yet millions of computers with this software are still running, making them vulnerable to attack. Make certain your call center stays up-to-date with software versions and security updates, and avoid open source software not shepherded by your vendor and its partners.
  • Implement Resiliency: Install software and hardware that ensures constant monitoring of your system, such as robust firewalls, routers, and network management tools. Proper resiliency may not prevent every attack, but it will ensure that your system continues to operate (even if in a degraded state) and alert you to issues in a timely manner so you can repair the damage and stay in business.
  • Execute Redundancy: Implement a business continuity disaster recovery plan and test it frequently, ensuring that your system is completely backed up and accessible in a crisis.
  • Choose Trusted and Experienced Partners: No one can do it all on their own. Ensure that your chosen vendors and partners are at the forefront of technology implementation. Make sure they have the ability to enable you to practice safe software management in a cost-effective and timely manner and have key partnerships in place to assist you.
  • Utilize Encryption Technology: Use encryption technology wherever possible, such as secure messaging, databases, routers, and firewalls.
  • Perform Security Audits: Contract with a competent third-party auditor to ensure compliance with best practices for security, including PCI and HIPAA. Use vendors and partners whose products and environment are annually audited.

Recognizing that we live in a dangerous world and seeking solid partners who understand technology and know how to mitigate the risk of cyberterrorism is not only prudent – it is an essential element in today’s world for ensuring that your business not only continues, but thrives. A little self-reflection and thoughtful examination of system and software vulnerabilities may not make it possible to avoid every cyberterrorist attack, but it will certainly create an environment of awareness and minimize the impact on your business.

William Lane has been involved in software development for nearly thirty years and has worked at such companies as Oracle, Microsoft, and ARIS. He is the president and CEO of Startel and Professional Teledata.

[From Connection MagazineMay/June 2016]

Why You Should Care about Your IVR

By Donna Fluss

Contact centers are finally becoming omni-channel organizations where customers can interact using their channel of choice. Technology such as WebRTC is altering the service experience by allowing customers to change modes – moving from a chat session to a phone call, for example – without changing medium. Outbound environments can chase customers using many channels, as long as they comply with regulations. Despite all of this welcome innovation, the traditional, dependable interactive voice response (IVR) systems continue to handle a large percentage of both inbound and outbound calls cost-effectively.

Back to the Future: While the Millennial generation has a strong preference for using non-voice channels that are accessible from their smartphones, they are not opposed to using an IVR, as they often prefer any form of self-service over talking to a live agent. Of course, the IVR experience has to be a good one, which we all know is much less common than it should be. Enterprises need to invest in enhancing their Web and voice self-service channels.

The service experience delivered by these channels needs to be consistent, as should the information available to customers. The self-service channels should be optimized to allow users to easily access the information or transact their business. Web and voice self-service channels should mirror as many activities as possible, as there will be times when customers are unable to call or cannot get online.

Millennials are giving voice self-service a fresh beginning, even if voice is not their preferred channel. But Millennials will not put up with the many poorly designed IVR implementations in the market today. This means that if companies are willing to invest in enhancing the scripts, voice user interfaces (VUIs), and integrations between the system and agents, then they have a great opportunity to use their IVRs, which remain one of the most inexpensive forms of service.

Tips for Using IVRs with Millennials: Here are a few ideas for using an IVR to deliver service to the Millennial generation:

  • Make it speech-enabled, and be sure it works: Millennials don’t have a lot of patience. They may try it once, but if something doesn’t work, you’ve lost them, and even worse, there is a good chance they’ll share their grievances on social media.
  • Make it easy, and give callers the options they want: In the “old days” companies put up the options they wanted callers to use on an IVR. This didn’t work then, and it doesn’t work now. If you want callers to use an IVR, automate the tasks they want to do on this channel.
  • Do not torture callers who do you the favor of using your IVR: Make sure it’s painless for a caller to transfer from the IVR to a live agent. Transfer the customer’s account number, and tell the agent what the customer already did in the IVR. Forcing callers to input and validate their identity in the IVR and then asking them to do it again when they get to a live agent is a waste of time and money for your company – and a total turnoff for any customer, particularly a Millennial.
  • Optimize your IVR scripts and options: Continuously look for ways to improve the performance of your IVR. Callers are open to changing scripts, especially if it improves the service.
  • Personalize the IVR: Use analytics to personalize the IVR experience. If callers always do the same thing on the system, either give them this information after they authenticate, or present it as their first option when reading them the script.
  • Tap technology: Use visual IVR tools to build consistency in your self-service channels.
  • Invest in voice biometrics to reduce fraud risk: Once customers pass the initial verification screening, give them what they want, and if they need to transfer to an agent, make sure they are not asked to re-verify.

Final Thoughts: When scripts and VUIs are well-designed and optimized, customers welcome IVRs as a useful form of self-service. This means that the old days of building an IVR application and leaving it alone for months, if not years, is no longer an option.

There has been innovation in the IVR market, and there is good technology available from on-premise and cloud-based vendors. But companies that want to succeed with voice self-service today must continuously invest in their application to ensure that it’s meeting customers’ ever-changing needs.

Donna Fluss is the founder of DMG, a vendor-independent research and consulting firm that analyzes contact center and back-office technology and best practices. Contact her at donna.fluss@dmgconsult.com with any questions you may have or to learn how to make today’s innovative and powerful technologies and best practices work for your organization.

[From Connection MagazineMay/June 2016]