Tuesday, May 03, 2016

Say you want a resolution (FCR, you know)?

A multi-thousand seat Business Process Outsourcer (BPO) in the east has seen an increase in repeat calls for similar issues. After doing some research and analysis, it was discovered agents were not properly trained in handling specific types of customer interactions and this was leading to repeat calls.

First Contact Resolution (FCR) is a common Key Performance Indicator (KPI) in contact centers. 

Resolving customer issues on first interaction is paramount to quality customer service, reduced costs and ultimately an improved bottom line. 

However, FCR is not easily measured. It's a common KPI but what defines a repeat call is not a static data element. 

Every contact center is different. Every customer is different. Every interaction is different. 

How then can FCR be measured?

The BPO's customer service department uses a workforce optimization solution (WFO) which gathers Automatic Call Distribution (ACD) statistics from their Unified Communications (UC) platform. Among the stats gathered include Agent State Changes and Computer Telephony Integrated (CTI) metadata for enhanced data points. 

Armed with all this data, the system is capable of detecting repeat interactions, and ultimately, FCR.

The organization implemented the FCR Service and created business rules and alarms to detect and notify supervisors of customer interactions that could be classified as repeat contacts. 

Since no two contact centers are the same, management mapped out data elements in their enterprise that signified repeat contacts. 

For them, this was easily defined by their ticket number. The Interactive Voice Response (IVR) unit requires all customers to enter their ticket number prior to being routed to an agent. The WFO system reads this ticket number through CTI and attaches it to each recorded interaction. 

The FCR Service monitors recorded interactions and ticket numbers and links interactions together. Multiple interactions with similar ticket numbers are flagged as repeat contacts.

The distributor has a strong leadership team and is capable of mapping their technologies together end to end. Not all contact centers are capable of capturing IVR information, such as ticket number, and mapping it to CTI data harnessed by other technologies, such as their recording system.

Their properly enacted data sharing plan allows them to simply use ticket number to determine FCR. However, for most contact centers, the task of measuring FCR is not so simple. 

With the power of WFO and the FCR Service, this task is handled effortlessly. The FCR Service allows for contact center managers to program it using any piece of data captured from the environment. This can be via claim number, case number, ticket number, customer number, account number, process id, or even un-mapped basic telephony information such as caller id, extension, agent or even date and time. 

At its most basic level FCR can be measured by caller id, date and time. 

Has this phone number called in within a recent period of time? If so, it’s a repeat contact. At its most advanced levels, FCR can be measured using mapped telephony data.

Once the BPO had configured the FCR Services to capture and flag repeat interactions, it was simply a matter of reviewing and evaluating those interactions to determine root cause. The Evaluation Assignment Services were configured to automatically assign all interactions flagged for FCR to the next available evaluator. Evaluations were performed on those repeat interactions and the system automatically pushed the proper learning materials to the agents.

The WFO system uncovered a lack of core competency by agents in a key portion of the BPO's processes. By revising their learning materials, the BPO improved agent knowledge and noticed a considerable drop in repeat interactions over the next 60 days. This reduced their overall call volume and ultimately improved their bottom line.

However, it doesn’t stop there. One workforce optimization solution, Virtual Observer, has extended FCR through to the Speech Analytics feature set to harness the power of the spoken word to uncover repeat interactions. 

Virtual Observer's "FCR Services" look for any number of configurable words and phrases to determine repeat contacts, such as, “I’ve called before”, “I’m calling back”, “This is the nth time I’ve called”, and many more.

Wednesday, April 27, 2016

How Avoidance Data Helps to Identify Trends in Your Contact Center

An enterprise healthcare provider in the Midwest has seen an increase in their average handle time and a reduction in the overall number of calls, chats,& interactions handled over the last 30 days by their customer service center. After doing some research and analysis, it was discovered there had been a spike in what we'll label as "Avoidance",

Avoidance has actually been defined a few different ways so it’s important to point out exactly which variation of avoidance we are referring to. 

In this case, we are referring to contact center agents purposefully avoiding calls, emails or chats to reduce workload. 

We're not referring to the act of building self-help tools and alternative ways for customers to fulfill inquiries without interacting with an agent and thus "avoiding" calls into a customer service center.

As satisfying and comfortable as management tries to make it, contact centers are notoriously difficult places for agents to work. Customers can be at times perceived as demanding or difficult. Leadership is constantly measuring, reviewing, evaluating and training to create happier customers, lower talk times and reduced costs. It’s a never ending cycle of increased expectations. 

Agents are human, and in the highly stressful environment of a contact center, they will inevitably try to fake out the technology and find a way to reduce the amount of work crammed into a work day. This is where Avoidance comes in. Avoidance is behavior agents use to purposefully avoid engaging the customer. 

"Bring on the chat bots!" they scream in a soft whisper.

Avoidance comes in many different flavors:

1) Agents might stay on the line for hours when the customers line did not disconnect. 
2) Agents have been known to simply hang-up on a caller as soon as the call gets routed to their phone. 
3) Agents might take a call, place it on hold for long periods, then either disconnect or resume the call until completion. 
4) Another example of avoidance is to shuffle yourself in queue. Agents will switch state to unavailable, then immediately back to available to be moved to the bottom of the queue and therefore wait longer for their next call. 

These are just a few examples of agent behavior that can be classified as Avoidance.

The enterprise healthcare organization, fortunately, uses a workforce optimization solution which records all customer service interactions including audio, video, chat, email, twitter, Facebook messenger and other social channels. The solution also gathers ACD Statistics and Agent State changes for scheduling, forecasting and adherence. Armed with all this data, they are able to detect Avoidance.

Management implemented an Avoidance Service from the Workforce Optimization solution and created business rules and alarms to detect and notify supervisors of agent behavior that could be classified as Avoidance. 

The avoidance rules implemented were limited to:
- calls much shorter than the average talk time
- calls much longer than the average talk time
- calls with 15% or more hold time
- calls with long hold times
- calls where the agent hung up first
- abandoned chats within the first minute
- deleted emails
- unanswered emails
- tweets which went unanswered
- frequent state changes
- very short state changes and long periods as unavailable. 

Now, when one of these conditions is detected, the supervisor is alerted through email of the agent behavior and even given the event to playback, review and act upon.

Over the next 60 days management was able to detect, and act on with evidence, many occurrences of Avoidance. 

After proper HR documentation and agent retraining, management used the Analytics feature to monitor and trend a decrease in average talk time and an increase in total number of calls handled and customer satisfaction scores.

If you suspect your agents of avoidance, find a robust workforce optimization solution which offers Avoidance reporting, simply build in your business rules, set up your alerts and wait for the results. 

Tuesday, April 19, 2016

Utilizing Social Media Marketing within the Workforce Optimization process accelerates customer experience gains

social media marketingThis customer profile features a Fortune 500 clothing retailer, which includes a chain of popular women’s wear outlets and has multiple contact center locations in the eastern United States. They've been experiencing rapid growth and have added 5 new locations in the last 6 months. 

As their business grows the executive leadership team is most concerned with the quality of their brand that customers have come to love and expect. “Growth is great but maintaining that close personal touch with quality fare is our number one concern”, said the Director of Quality.

The retailer uses a state of the art Contact Center which accepts orders online and then customers can drop in and pick-up their merchandise at the nearest location. “The e-commerce store is what drives our business now to the brick and mortar. Customers expect their orders delivered quickly and accurately”, he added.

The contact center is built on leading communications technology and monitoring tools where orders are entered into the CRM (customer relationship management) software, from either the website or handled through the telephone, and immediately routed to the proper store location and designated for pickup as though customers ordered right off the rack.

Not only does the team of quality experts look to ensure order accuracy but they are also responsible for measuring the quality of the contact center interaction. Using a workforce optimization suite, the team plays back recorded events from phone calls, emails, web chats, Twitter, Facebook Messenger, SMS as well as any other active channels. The team of supervisors will then evaluate and score the events to ensure proper dialogue and resolution. The goal is to have their agents cultivate the ultimate customer experience.

The contact center supervisors also use social media monitoring tools to monitor their brand on Facebook, Twitter, Instagram, etc. and respond when they can. The tools also provide metadata which can be used to improve performance and responsiveness.

For example, if a customer had a bad shopping experience at a local store, they might be inclined to make their next purchase online. 

However, in a worst-case but likely scenario the customer took to Twitter to express their dissatisfaction. 

The contact center’s social media monitoring tools detected the Twitter activity and issued a reply via Twitter from an available agent. The agent expressed an understanding of the customer’s issue, and told them normally there would not have been an issue. 

They assured the customer that the next time they entered the store, they would have a more satisfactory experience, and a 30% off coupon may help them get what they are looking for at a fantastic discount. They told the customer to keep them in the loop on any future experiences. 

The Twitter chat was then escalated to a supervisor, who authorized the coupon and scored the agent’s response a decent 90 points out of 100. The only improvement suggested was the agent not addressing the customer’s Twitter handle in the response. The supervisor then scheduled a re-training of the Twitter Response procedures to be delivered to the agent via the WFO suite's E-learning features within an agent portal.

This is atypical of standard features found in Workforce Optimization Suites, but "social media monitoring" is available in the Virtual Observer suite.