The Challenge

A large entertainment provider was launching a subscription service to offer their live events online. A big portion of the millions of customers that had previously purchased each event on cable or satellite would now be purchasing a subscription to stream online. The organization needed a contact center partner that could quickly scale to handle all customer inquiries, including billing, product and technical support. The partner also needed to provide customer support across multiple channels, including phone, email, chat and social, ensuring that each subscriber could properly stream the event on their device-of-choice and was satisfied with the service.

With less than 90 days until the first online event, our team had to staff up to receive and resolve over a hundred thousand customer support inquiries within a two-to three-hour window before each major event. We leveraged our own contact centers, as well as our geographically-diverse network of partners, to staff a huge team within a tight timeframe.

Our Insights

A major challenge for this client was managing the variety of streaming devices and operating systems on the devices, each with its own challenges. To support customers using different devices, our team developed and deployed extensive content for a robust agent knowledgebase.

We created and deployed a cross-channel CRM using Oracle Service Cloud to a core group of agents that could support customers across channels using one knowledgebase—a key differentiator in CRM technology that allowed for consistency across call center locations. We also developed a separate, simplified system that was built to mirror the Oracle Service Cloud application. Deployed with the majority of our agents, this cloud-based platform reduced training, contributed to a faster deployment and helped to avoid server overload.

If these customers couldn’t quickly pay for, sign on and get connected to the streaming service, our client would lose them to the cable company. Every call was revenue. We met customers in the channel of their choice, quickly solving their support inquiries across phone, email, chat and social.

Our Approach

To keep costs reasonable, we segmented the agents, into several groups that received varying levels of training: a core group trained on all primary call types; an escalation group trained to handle more complex calls; the remaining agents trained in one of two key support areas. Through a learning management system, we successfully deployed training content to the multiple agent locations, administered assessments to certify the capabilities of all agents. New or revised content could also be effectively deployed in the same manner.

We hired, trained and deployed a separate group of agents that handled customer support on Facebook, Google+ and Twitter. Specifically trained to solve problems in social communities, this dedicated group was able to provide valuable information to subscribers and resolve many issues online, which ultimately deflected calls from the inbound phone lines.

It’s a rarity in this business that any client would need 7,000 people on the phone at the exact same time—most systems are not built for this type of load. Just like the CRM, every other technical system had to be evaluated and the redundancy improved. To address this need, we made use of multiple data centers with redundancies of all systems and used a cloud-based telecommunications infrastructure for effective call routing.

The Results

With 15 years+ of experience supporting the streaming services industry, we were able to deliver a successful, large-scale, cross-channel customer support solution within a tight timeframe. Our expertise allowed us to lead the project, from determining the correct agent skillset to hiring and training, to measuring success. We also came in under budget through efficient workforce management and offshore, near-shore and skills-based routing.

Specific results include:

Ramped to

7,000 agents

to manage the simultaneous response

Exceeded customer performance (SLA)

by 430%

Reduced handle time

by 20%

based on average performance

Reduced forecasted average wait time

by 10%