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Chat Analytics Continues to Deliver Program Performance
Case Study

Chat Analytics Continues to Deliver Program Performance

Our Brand Partner

Recognized as a global leader in interactive and digital entertainment, this client markets gaming consoles, interactive games and online entertainment for all ages. They have become the leader in their industry with products that are changing the quality and definition of gaming and home entertainment for all.

Challenge Presented

SYKES brings continual improvement to all our client programs. This brand partner’s chat program was mature — meeting agreed KPIs and customer-experience expectations.

While delivering satisfactory performance for both the brand partner and their customers, SYKES recognized that further improvements were possible within the program.

Our Approach

SYKES’ customer-experience analysts conducted an Insight Analytics™ study tailored to the chat environment. This type of study consists of five strategic stages, starting with a discovery phase and ending with our Analytics in Motion™ (AIM) program.

The process includes:

• Active reading of a sample of chat conversations to determine the voice of the customer

• Identifying patterns through transactional data

• Focusing on customer needs and opportunities

The study identified the following six agent attributes as having the most influence over customer experience:

⦁ Appropriateness of offered solution

⦁ Understanding customer needs

⦁ Advocacy

⦁ Case ownership

⦁ Product knowledge

⦁ Probing skills

The impact of these can be seen in the following ways:

Partnership Outcomes

The Insight Analytics study produced a detailed 30+ page report that was delivered to the brand partner detailing current processes, methods and performance. It also highlighted improvement opportunities and recommendations including:

Chat Processing Times

Recommendation: Improve the pre-chat web form to assist the agent in identifying the customer’s issue rather than using the start of the chat session to do this.

Goal: Reduce the number of exchanges per chat session and decrease average chat time by 1.3 minutes.

Agent Attributes

Recommendation: Identify the agent attributes that resulted in positive outcomes such as true first-contact resolution and lower handle times.

Goal: Help quality assurance monitors and team managers coach behaviors that are proven to improve performance.

Follow-Up Questions

Recommendation: Identify questions to ask the customer after the solution is delivered to address issues that might result in another call. Modify the Quick Text to address common questions and those interactions driving longer handle times.

Goal: Avoid subsequent contacts by proactively addressing common follow-up questions and related issues.