Category Archives: Support

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.


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 


6 Issues that Slow Down Your Support Team

Historically, the great thing about Genesys is that the systems can be programed to do just about anything, in any environment. The tough thing is, with such flexibility, it can be difficult to support.

The 6 things that slow down a support team, and can cause frustration for the business are:

1.  Getting Accurate Information

When the support team is first made aware of an issue, the first challenge becomes getting accurate information to help pinpoint where to find evidence of the problem.

The most common info required is a decent description of the problem, the agent ID, a specific detail of the call or event, such as the caller’s phone number, and of course, the date and time. Often one or more of these are not provided, or are not accurate, wasting time looking in the wrong place, and prolonging the outage.

So, why is it so hard to get accurate info? Well, often the person reporting a technical problem does not have a technical background; but more significantly, the data often can’t be verified right away. This is because getting the info and validating it is typically a two step process. The support team has to get the logs (and probably CME info) first before they can tell if the data provided makes sense.

2.  Assembling the Data Files

Typically, the logs are stored on each server, but sometimes they are centralized and archived. There could be thousands of files.

Often, all the logs for a specific time range need to be isolated to narrow what to look at in order to trace an issue. A lot of time is spent just in the preparation stage, assembling files before someone even looks at the problem. Sometimes even hours. At times the data is gone, the files rolled over, and that issue cannot be examined.

3.  Sifting through the Data Files 

Genesys log files are text based, describing events such as errors, or the various states of a call like “queued” or “ringing”. They require a level of skill to read and understand the call sequences. Several sequences are not documented, so it would take an experienced person to trace through all of the data to find certain types of issues.

4. Determining the Scale of the Issue

A significant problem with a reported issue is knowing how widespread it is. Sometimes the agent reports it after already experiencing it a few times, maybe over several days. If one agent has it, it is possible that others have the same issue but are not reporting it.

In one case that Aria Support diagnosed for a client, one of their customers was kind enough to mention that they were disconnected on a previous call, and the agent reported it. With little other information, we were able to locate the problem, and could quickly determine that it was affecting lots of callers every day. As it turned out, the configuration on the phone system had been changed for several treatment ports, and dozens of customers’ calls were being dropped every day.

5.  Genesys Escalation

When one opens a ticket with Genesys Support, we are often starting from scratch. Explaining the issue, letting them look at the data files, and giving them some time to catch up to the level of understanding already developed by the internal support team, so that Genesys can take it further, even to engineering if required. While there are some issues where this is unavoidable, it would be preferable to be able to diagnose the issues without having to go to that step, since it stretches out the duration of the outage.

6.  Lack of Tools to Assist and be Proactive

The most common tools used are text editors that can color code text, generic search tools like Grep to look for files that contain certain text, and Kazimir, a crude log file text viewer showing one file per tab. The lack of tools contributes to the skill required and the time it takes to identify issues. This impacts a support team’s ability to be proactive in identifying and solving issues, even ahead of them being reported. Every minute of downtime can cause lost revenue and impacts to customer service, affecting loyalty and customer satisfaction scores.

CIMplicity Visualizer

These issues so frustrated Aria’s Support and implementation teams that Aria was determined to find an easier way. Those teams now use a product developed by Aria, called CIMplicity™ Visualizer, which allows the user to see calls graphically. The engineer can zoom in to one call, or zoom out to see all that is happening at the same time. Ask the data questions, or even dive back into the associated log file if desired. Visualizer is now available for organizations using Genesys to allow them similar benefits as with Aria’s internal teams.

With automatic multi-site and multi-server data collection, Visualizer lets you start analysis immediately. It combines interaction and configuration data into a powerful color-coded dashboard, condensing large amounts of data into actionable information to quickly zero-in on any issues that arise. An intuitive interface lets you filter, highlight and drill down to get to the root behavior of your Genesys system for resolving issues and improving the overall system for optimum efficiency.

CIMplicity Visualizer, is the best tool available to diagnose, zero-in, and resolve issues in a fraction of the time. It helps agents see the data they need, understand this data to know why, and save the day by having the right answers needed to solve problems.