Category Archives: Contact Center Optimization

How To Organize Support For Your Contact Center Applications

As contact centers become more complex and expand to support more channels like web chat and social, it’s important to organize support for contact center applications in a way that allows teams to design consistent customer experiences.

Most contact centers organize support around siloed applications, having one team that supports the voice channel and a separate team that supports social channels, like Facebook. But when support is organized this way and spread across multiple application-specific teams, gaps in support are created and must be fixed as they can affect both the efficiency and effectiveness of the contact center.

Organizing support by functional skills not by application silos

Instead of organizing support by contact center application silos and having multiple application specific teams, contact centers should try the approach of organizing support around functional skill sets.

Seen in Figure 2 below from the Forrester report “Mind the Gap When Organizing to Support Contact Center Applications”, by looking at functional skill sets like agent desktop that can span a group of applications, contact centers can gain leverage.

contact-center-applications

One team to support queuing-and-routing

Companies that don’t have one complete solution for their contact center, are supporting queuing and routing for digital channels like web chat and social through their website teams and ACD, IVR, and CTI support for the voice channel usually has its own team. Having this legacy telecom silo, creates a gap in support and makes it difficult for both teams to design consistent customer experiences.

Merging these teams to support queuing and routing contact center applications, means they will be working on the same customer experience design goals and requirements, which results in more consistent experiences across all channels.

Another reason why it’s important to do this now is there are emerging trends like AI matched routing that will likely force this organizational shift eventually (Future-Proof Your Customer Service: Build An AI-Infused Cognitive Contact Center, Forrester Research, February 2018). This new way of routing is different from skills-based routing in that through AI, agent matching is done in real-time and based more on attributes such as:

  • Agent performance histories
  • Skill development priorities
  • Customer histories

AI matched routing needs to look at the experience customers have on all channels so to implement this and other emerging trends, it’s essential for queuing and routing to be one team.

One team to support the agent desktop

[easy-tweet tweet=”Agents can have 10 to 30 applications open simultaneously.” template=”light”]But to reduce employee and customer frustration, improve handle time, and lower training expenses, agents need the right tools and an agent desktop that shows them a 360˚ view of the customer on one screen, should that be the goal.

In order to not add to the list of agent applications, contact centers should be selective about what ends up on the agent desktop, and they should monitor agent use to further refine the user interface (Design Your Contact Center To Be Customer-Centric, Forrester Research, August 2017). The best way to do this is to have one team that supports the agent desktop, instead of a bunch of separate teams supporting different contact center applications agents use.

Organizing support for the agent desktop in this way will focus efforts on usability and developing a more in-depth knowledge of all applications appearing on the agent desktop. Making it easier for agents to engage with customers has many benefits for the contact center, including:

  • Reducing agent turnover and increase efficiency
  • Increase customer satisfaction scores
  • Increase revenue

[easy-tweet tweet=”Companies with agent desktop optimization programs enjoy 44% greater customer retention rates. ” template=”light”]The first step to driving these results is to have one team that supports the agent desktop to optimize the user interface and help improve customer engagement (Design Your Contact Center To Be Customer-Centric, Forrester Research, August 2017).

Contact center operations to support CC data analysis

Business analysts in contact centers are faced with the challenge of navigating through many reporting systems. Having data stored in disparate systems is a major pain point for contact center managers too – as they need manually consolidate reports to be able to forecast and schedule.

Since expertise of data structures and databases frequently resides within business technology rather than in the contact center itself, this causes a gap in the effectiveness that analytics can bring to the contact center. To remedy this, organizations should move contact center data analysis from the business technology to the contact center business unit itself.

Contact centers are awash with data, but there is still a struggle to integrate it and drive process management (Design Your Contact Center To Be Customer-Centric, Forrester Research, August 2017). Having contact center operations support data analysis for the contact center can help the organization understand the data analysis needs of the contact center, resolve any data visibility pain points that contact center operations managers experience, and help run the contact center more effectively and efficiently.

A few things organizations need to do is:

  • Understand how subtle changes in historical data can affect WFM

WFM teams depend on historical data but they also need to know of any anomalies or shifts in that data over time. Business Intelligence (BI) teams should assist WFM teams in analyzing these shifts and helping them determine if system upgrades or database changes in a certain timeframe caused any anomalies.

  • Understand that queuing and routing changes affect reports

Changing real-time business rules can affect how data flows into analytics systems so the team that supports queuing and routing must work with the BI team so both teams understand what reports will be affected from routing changes.

  • Map and manage the many sources of truth

BI professionals should work with contact center business analysts to map existing systems and determine which reports should come from which system. For example, in scenarios were customer feedback is captured in an IVR then integrated with quality monitoring data, which system is best suited to show customer satisfaction trends? This needs to be determined for the contact center to get the right insights and make better decisions.

Configuring contact center applications drives not only the customer experience but the agent and management experience as well. How contact centers organize support results in the overall efficiency and effectiveness of the contact center.

To learn more about how to optimize operational performance of the contact center by picking the right contact center organizational model and developing a “living” RACI model, download this complimentary Forrester report https://aria2019.wpengine.com/forrester-report-support-contact-center/ 

 

Top 3 Reasons Why You Need Customer Interaction Analytics

Businesses are losing $62 billion per year through poor customer service (Serial switchers strikes again, NewVoiceMedia, Jan. 2016). This means the new goal must be getting every interaction right.

Forrester Research predicts that by 2020, insights-driven businesses, like Baidu and Netflix will quadruple their revenue from $333 billion to $1.2 trillion, growing eight times faster than global GDP (Top Five Imperatives To Win In The Age Of The Customer, May 23, 2017).

Customer-centric companies like these are a real threat to a lot of businesses who choose to prioritize areas like manufacturing and distribution, instead of better understanding their customer needs and wants and delivering personalized experiences.

To deliver such experiences, you need insights; but to get insights, you need to start using all your data the right way. Once you get to a phase when you no longer have data silos across business systems, it is important to start looking for a good operational, employee, and customer interaction analytics application. And here are the top three reasons why:

1. Customer retention

No one would argue that customer retention is critical for survival. Your brand and company Net Promoter Score (NPS) is constantly being reevaluated with every interaction handled and socially-shared commentary by your customer base.

Back in the day, a negative customer experience would simply make interesting conversation over coffee. But with the advent of social media, customers that are not able to resolve issues, can blast their complaints to a global audience that will hear about any shortcomings your business may have.

A lot of companies out there focus more on customer acquisition than on customer retention. But did you know that it costs five times as much to attract a new customer than to keep the existing one, and if you only increased your customer retention rates by 5% your profits could increase by 25% to 90% (Customer Acquisition Vs. Retention Costs, Invesp, Dec. 2015).

The best way to increase your customer retention rate is to improve customer experience.

2. Agent behaviors

Your front-line agents are also a crucial element to your customer experience. By gaining visibility into your agent interactions you can make better decisions.

But do you really know what is going on? Are you able to easily see the whole picture when it comes to your agent performance?

Traditionally, agent behavior analysis has been based on a set of standardized aggregated metrics that were supposed to summarize good agent performance. But to provide good customer service, aggregated metrics just don’t cut it and so you need to look at customer interaction analytics.

Granularity and automation are needed to look for negative behavioral patterns (placing customers immediately on hold, flashing Not Ready while Ready, etc.) in your agent performance and flag them immediately.

The ROI in this case can be simple. As an example, let’s assume a fully loaded agent cost of $65K. That translates to $280/day/agent. If we manage to identify 15 mins of lost time for every agent day and assume a 300-agent contact center. It translates to $2700/day which over the course of 220 work days in a year is just under $600K!

And that is not even considering the impact a negative behavior may have on the customer experience or revenue opportunities.

3. The “hidden” costs of support

Most firms are swimming in data, but they’re only using about a third of it. Worse, only 29% say they are good at translating the result of data and analytics into measurable business outcomes (Top Five Imperatives To Win In The Age Of The Customer, May 23, 2017).

As a matter of fact, the top two challenges preventing organizations from making use of analytics are “ensuring data quality from a variety of sources” and “accessing data from a variety of sources” (Pick A Powerful Pilot To Propagate Customer Analytics, July 19, 2017).

Speed of issue resolution carries a significant impact. The quicker issues can be resolved, the less chance there would be of repeating poor customer experiences, thus minimizing the impacts to your brand. Outages that critically impact service delivery are a ticking money bomb. Financial impacts increase exponentially the longer you are unable to service customers. One of the largest banks in Canada implemented Aria’s Visualizer (business and support analytics) and improved support response times by 75%. Such customer interaction analytics applications cannot be underestimated.

Systems that deliver customer interaction analytics in an efficient and accessible manner empower lower tiered or less senior support staff to extract necessary system information required for issue resolution. This can help focus the energy of senior technical staff on critical and future facing initiatives.

Business analytics resources can also leverage data on agent and system behaviors to make better operating decisions.

Lack of proper visibility into these three areas: customer experience and retention, employee behavior, and support issues – translates into a significant financial impact. Analytics applications like Aria’s Visualizer allow for an improved unified approach to visualizing interactions level data, strategic support approach and behavioral performance analysis which can help you provide top rated customer service.

To sign up for a demo of Aria’s Visualizer visit the Genesys AppFoundry or the Aria’s Visualizer product page.

Turning Customer Interaction Data into a Competitive Advantage

Most contact centers use interaction data to justify or support contact center metrics, such as average call handle time, speed of answer, abandonment and even first call resolution.

But when you think about it, doesn’t it make more sense to capture data at the event and interaction level? This would allow for much more powerful analysis, as well as the ability to think outside the standard box of metrics every legacy system provides.

It’s actually very difficult to turn even excellent performance in most standard contact center metric categories into a sustainable competitive advantage.

In this blog, we will look at how one well-known company’s use of customer interaction data has become a key part of their success.

A Modern-Day Romance: Big Data and Customer Journey

It’s hard to escape noticing the trend categorically described as Big Data. Gartner predicts that by 2020, there will be 26 billion common household devices with the capability to being connected and sharing data. If you really think about it, it kind of starts to get a little unnerving. So, our advice is … don’t think about it!

Not only is data being tracked in aggregate, but it’s being tracked by businesses in the context of trying to understand your journey or your customer experience.

In the past, companies primarily focused on delivering their customers a tangible good or service. But why wasn’t this sustainable? If your market was attractive, then someone somewhere was working on delivering it better and cheaper.

Companies then began focusing on our “relationship”. Today, most organizations are focused on customer experience or the customer journey. But it’s different than the relationship and loyalty concept. It’s based on the concept of the “experience economy”, which started in the early 2000’s, but really has emerged as the guiding principle for customer service organizations. If you want some background, read this Harvard Business Review article “Welcome to the Experience Economy” by B. Joseph Pine and James H Gilmore.

The reality is – most organizations have more information than they know what to do with.

Now Playing: Netflix

Let’s look at Netflix and how they leverage their customer information to enhance the customer experience. The upstart was one of the main factors that drove Blockbuster to bankruptcy; even though, Blockbuster seemed to have all the advantages. Blockbuster at its peak was a $5B company; Netflix was started with $2.5M in startup cash. And today, according to some, it is worth in the neighborhood of $68B!

What made Blockbuster disposable was the fact they were focused on the rental transaction and were not focused on customer experience. Blockbuster had the opportunity to collect our interaction data – but they didn’t.

On the other hand, Netflix did something with each customer interaction. They tracked what customers liked and made suggestions. And they got better and better. Blockbuster only had a loyalty program, something like a free rental every 10 times.

It wasn’t just about the streaming technology. Yes, it was a threat, but Blockbuster had the financial resources to build it or buy it. They failed by allowing Netflix to create a competitive advantage of customer interaction intelligence. Netflix leveraged this intelligence to delight customers, by personalizing each and every customer experience.

So, Where Do We Go from Here?

The key is creating a company culture that does not focus solely on tasks. And the first step is to see if you have any system or data silos to be able to know your customer’s interactions.

The key to overcoming all barriers is to focus on the fact that the contact center is the front line of the customer experience. Typically, it is a key nexus to capturing the interaction data that can be leveraged strategically.

Contact centers should push the organization to view the contact center as strategic. Setting the stage that customer experience has to be viewed with an eye toward making the customer’s life better is every bit as important as making the contact center’s life better.

The key lies in making the connection between the customer interaction data, transforming that into valuable information and leveraging that to improve every customer interaction.

In today’s world, simply satisfying customers will not retain them. By turning data into insights, contact centers can personalize each interaction to deliver a little extra to delight them. And this what creates a real competitive advantage.

Measuring Agent Productivity in an Omnichannel World

As customer call centers have evolved into customer care centers, managers have had to adapt with new strategies for going beyond solving customers’ problems to finding ways to delight them at every touch point. The rewards can be great — customer loyalty and brand advocates — but only if customer care is done right.

Making sure that happens involves a complex melding of best practices in technology, process, and agent performance. One element that brings all three of these factors together is an omnichannel approach.

Ensuring a smooth and consistent experience between channels — phone, email, text, and chat — is the key to success in omnichannel customer care delivery. But to ensure that success, you need to know what’s working, especially in terms of agent efficiency.

In the old voice world you measured the length of phone calls, how many calls per hour, and the percentage of issues resolved during the first call, pretty straightforward, but with agents using multiple channels in a given shift, those measurements no longer tell the whole story. Let’s look at the challenges of measuring agent activity and productivity in an omnichannel world and how you can overcome them:

Challenge #1 – Blending

Within the omnichannel world you might have each agent assigned to just one channel, which keeps measuring their performance simple. However, another approach is having any given agent assigned to multiple channels simultaneously. For example, an agent might take calls, but respond to emails or chats when call volume is slow.

While this approach serves to increase overall efficiency for the care center, a single agent may not be as productive as they would be using just one channel at a time, especially when asked to handle too many channels.

The first step to optimal performance is appropriate performance measurement. For example, let’s say you have two pools of agents handling inbound phone calls:

  • Pool #1 handling only calls[su_spacer size=”10″]
  • Pool #2 responding to emails in between calls[su_spacer size=”10″]
  • Expectations for Pool #2 handle times should be adjusted accordingly, given that these agents need time to shift between channels and tools.[su_spacer]

This scenario becomes increasingly complex as you add more channel types and combinations, and you must determine the level of granularity needed to be effective at managing your workforce according to contact load. The best approach is to be as granular as possible on initial setup, and then aggregate metrics as you choose to ignore certain levels of differentiation to simplify ongoing management.

Challenge #2 – Simultaneous Interactions

Simultaneous interaction handling is not recommended. Agents juggling more than one customer at a time are more likely to exhibit lapsed concentration, mistakes in execution, and accidental sharing of private information.

However, there are care centers out there pushing those boundaries, so some agents will be handling multiple channels simultaneously. These agents may be engaged, for example, on a phone call and a chat at the same time.

So, in a five-minute window, if a given agent is talking on the phone to one customer and chatting with another, the appropriate measurement of time spent might be five minutes for each interaction, for a total of ten minutes.

This means that an agent could potentially have more interaction time (say six hours) than their actual shift time (four hours). Managers may need to adjust the processes and tools they use to accurately measure results.

Challenge #3 – Virtual Queuing

When no agents are available, virtual queuing allows customers to schedule a call back when call volume is low or hold their place in the queue and call back when it’s their turn. This method is more convenient for customers, but — to ensure it works most efficiently — care centers must properly attribute the queue time of the interaction even when there is no call physically waiting in the telephony environment.

With falsely short queue times, measurement systems may offer lower numbers than expected as there appear to be more calls handled within acceptable queuing thresholds. It’s also important to note that virtual queuing strategies (and the metrics used to measure their effectiveness) only work if there are down times during which agents can make return calls.

Invest in the Right Technology

The key to accurate measurement in the omnichannel environment is the right technology. Granularity is important because you must be able to group by agent skill set or interaction type combinations. Those base metrics can later be combined to achieve the desired level of reporting.

Therefore, it’s prudent to seek out tools, such as Aria’s Visualizer, that capture and display data at the distinct interaction level. The key is to get reports of all events (including interactions, routing, and meta data) within an environment, so you can later analyze that data in ways that are meaningful to your care center and your company.

You also need to be able to accurately capture presence data, and precisely attribute handle times to each channel method. The right tool for these tasks is one that seamlessly connects your customer relationship management (CRM) system, such as Salesforce, with your workforce management (WFM) system. This type of application can provide accurate metrics like the average queue wait time, or average interaction handle time (including all channels), which help with forecasting and staffing.

Finally, having all channels operating within one system can assist in measuring critical metrics. Commonly, an agent will be working within two or more channels, using a separate tool for each one. Because the systems are separate, so is the data gathering, meaning there could be inconsistencies in how performance is measured. Unified agent desktop technology helps in connecting all channels to one system in order to gather consistent, complete, and useful data.

Bottom line: the challenges of working within an omnichannel environment don’t have to outweigh the benefits. The investment you make in omnichannel operations may come back to you many times over, but only if you can optimize agent performance. The best way to do that is to recognize the challenges, and make sure you have the right tools to address them.

Agent Desktop Optimization: How Many More Screens Can Your Agent Handle?

Successful contact centers have always relied on speed. It’s about getting more done, in less time. To better manage customer conversations and respond to their inquiries in a timely manner, contact center agents need access to the right information immediately. The trouble is – most contact centers face data silos and believe that expensive, custom integration for agent desktop optimization is their only alternative.

It all comes down to inefficient infrastructure. Agents are forced to work with disparate IT systems that don’t talk to each other, making access slow and labor-intensive.

Over the years, mergers and acquisitions have shoehorned incompatible technology or multiple data sources together, making the infrastructure even more complex.

Wasted time and unnecessary costs

The average agent spends 15% of their time searching for the information across disparate systems to respond to customer inquiries (the Aberdeen Group research). This results in a lost cost of productivity of $1.57 million each year for a 300-seat contact center.

It’s a daily battle, and it gets them down. They’re not as productive as they want to be. They can’t serve customers as well as they need to, and there’s nothing they can do about it.

The extra ongoing costs of managing and maintaining disparate and legacy systems mean your business is bleeding money where it doesn’t have to.

Improving agent efficiency with unified, omnichannel technology

Modern contact centers need to add channels like voice, email, chat, mobile, social media to serve their customers. And the number of channels and tools used by contact center agents is expected to increase. This, coupled with data silos, means organizations need to rethink priorities and find alternative solutions.

According to 2016 Aberdeen Research “Optimize your customer experience strategy, get data right”, delivering consistent omnichannel conversations depends on companies providing all relevant employees with a unified view of their customer journey. So, it’s important that contact centers integrate this omnichannel approach into their agent desktop technology.

By investing in an optimized agent desktop, agents no longer have to switch between several screens to find the information they need. It’s simply there when they need it. To achieve this, agent technology needs to be integrated with multiple data sources, such as CRM solutions like Salesforce, while also providing access to legacy databases, such as billing systems or custom in-house systems.

There are platforms and solutions available that make integration faster and more powerful than ever before. So, improving agent’s access to information through agent desktop optimization may not be nearly as costly as you think.

The faster an agent can access what they need, the happier they’ll be. The same goes for their customers. Optimizing agent technology to speed up customer service should be a priority. For example, Amazon patented its ‘OneClick’ purchase process to retain what it believes is an enormous business advantage in terms of customer service. Amazon achieves extremely high conversion from its existing customers. Since the customer’s payment and shipping information is already stored on Amazon’s servers, it creates a checkout process that is virtually friction-less.

It’s this “friction-less” transaction concept that is needed in your contact center. Whether answering a customer’s question, selling them a product, or providing a service, enabling your agents to perform friction-less transactions should be the goal. Creating an integrated solution is a big part of this process.

In fact, integrated solutions are already delivering. The majority of companies improving agent productivity and performance can access relevant customer data through a single screen, therefore, improving first contact resolution and customer retention rates. For any business concerned about employee retention, this is the way to ensure it.

Contact us today to learn how Aria can help your contact center maximize agent productivity and ensure customer satisfaction across multiple channels.

Don’t Squeeze the Life Out of Your New Contact Center Project

Congratulations, your new contact center solution finally received budgetary approval! You have been waiting years for the opportunity to provide a better experience for your customers, a more empowering solution for your employees, and a rich new set of data for your managers. Now you are thinking, “This is my chance and it does not come often. So, I am going to dig my heels in and squeeze everything I can get out of this project.” We don’t blame you! However, starting a project with this mentality does not always generate the best outcome.

Why? You are learning the capabilities of the new solution while at the same time agonizing and scrutinizing over all of those pent-up needs and requirements. This often leads to project paralysis, longer project durations, and a reduced return on investment (ROI).

By the time the project is rolled out, you’ve got implementation fatigue from being involved in the project while continuing to deliver your day job responsibilities. At this point, you accept whatever went into production as you need to move on to other business priorities. The result is something less than you desired. There are usually compromises during the initial deployment and new requirements identified once customers and employees start using the system.

In our experience, it is better to determine complete requirements once the solution is being used. Therefore, we would like to recommend a different implementation approach that reduces project stress, engages customers, empowers employees sooner, increases ROI, and has better end results.

  • Phase 1: Deploy – implement a basic or templated solution as part of the initial deployment. In most cases, the capability being deployed still provides an improvement compared with what is in your environment today. So, a basic solution gets you going with new technology and still provides an improvement over what you currently have.
  • Phase 2: Learn – gather feedback from customer and employees. Compare what they say about how you are engaging with customers, with how you defined your solution.
  • Phase 3: Adapt – enhance, tailor, and customize the solution based on a more thorough set of requirements.

With this approach – time, energy, and costs saved through the “Deploy Phase” are reinvested in the “Adapt Phase”.

From what we’ve seen, this approach results in a higher quality solution with less stress and similar costs. Increased ROI and customer and employee engagement are realized by a quicker initial deployment and through the opportunity to enhance the solution after a period of use.

A New Way of Implementing the Genesys CX Platform

Robert Church, CEO of Aria Solutions, unveils a new 60-day implementation approach called SWIFT™ Premises – a complete, modernized, Genesys contact center solution that can be implemented rapidly and expanded to incorporate the omni-channel experience customers expect.

“We’ve seen a lot of companies experiencing revenue and customer satisfaction pressures, because they were looking for a new contact center solution and spending years deploying and customizing a new system, while their current systems were no longer meeting business needs and needs of their customers”, says Church.

Aria’s new solution model enables companies to make the investment based on a more efficient and thorough implementation process:

  • Deploying a modernized, enterprise-class inbound contact center foundation in 60 days
  • Learning the new solution and refining the requirements based on findings
  • Adapting to current and future needs by expanding the platform with enterprise-class capabilities[su_spacer]

The keys to this solution is its automated, but flexible deployment approach and its configuration capability, which come from Aria’s pre-tested, pre-built, and pre-validated assets: SWIFT™ Auto Attendant, SWIFT™ Routing, and SWIFT™ Real-Time Reporting. They provide options to meet various contact center requirements, speed up the deployment process, illuminate risks, and allow businesses to retain a complete control over their systems for easy maintenance and support.

In addition to Aria’s assets, SWIFT Premises includes core components, such as: SIP/Legacy PBX integration; High Availability – Dual Data Centers; Desktop and CRM integrations; WFM; Real-time Dashboard Reporting; and More.

“Many contact center implementations spend more time than desired in analysis paralysis, documenting hundreds of requirements, and customizing while learning a new system. This leads to long implementation times while in reality 80% or more of contact center requirements are the same”, says Kelly Wilson, Aria Solutions’ VP of Client Solutions.

Wilson says that Aria’s 20 years of experience in partnering with Genesys, building contact center technology and implementing complete solutions have enabled them to develop a unique implementation approach that no one else has.

Fast deployment, speed to market and adaptability are key reasons why Aria’s new solution approach is called “Swift” – one of the fastest, most agile and adaptable birds on the planet.

To learn more about this solution approach, visit https://aria2019.wpengine.com/swift-solutions/swift-premises/