Ensuring consistency across brands
With 2,000 agents across 13 brands, Cox Automotive’s contact centers varied significantly in terms of QA maturity. Newly acquired brands often had limited QA investments, while established ones boasted sophisticated processes.
To create a comprehensive strategy for bringing together these diverse arrangements, the COE team needed a strategic approach supported by intelligent technology.
“The goal of our COE was to consolidate the contact center operations across Cox Automotive to maximize our use of tools and deliver an exceptional client experience,” says Matthew Fishbein, a Director on the Client Operations team.
To support this effort, the team adopted the Observe.AI Conversation Intelligence platform. They began by manually scoring agent evaluations within the platform, which helped them establish a consistent quality review form.
“This milestone allowed us to standardize our quality evaluation form across all contact centers and move from various stages of QA maturity to a more cohesive, competency-based system,” says Fishbein.
Streamlining with Auto QA
To drive greater efficiency, the COE team integrated Auto QA across all their contact centers. This rollout enables the evaluation of 100% of customer interactions and offers deeper and clearer insights into areas for improvement in agents’ support delivery.
At the center of this new system are Observe.AI Moments—specific instances in customer interactions that uncover important trends and insights. Cox
Automotive’s standardized evaluation form now features around 25 Moments and more than 2,000 keywords and phrases, facilitating focused assessments of all relevant aspects of customer interactions.
As Fishbein notes, “This approach provides a comprehensive and consistent evaluation framework while allowing brands the flexibility to maintain their unique identities within the overall QA structure.”
Scaling call analysis
The COE team previously relied on a limited evaluation sample of about four calls per agent each month, which introduced potential bias and limited insights into agent performance.
With Auto QA, the team now completes more than 90,000 evaluations a month. This capability offers a more thorough and precise understanding of customer interactions. Thanks to the higher volume of evaluations, the team generates more data to support accurate QA scoring and continuous improvement in service delivery.
Likewise, Auto QA provides valuable data on agent evaluation forms by identifying which forms and questions have the highest and lowest scores.
“The depth of insights we’re now receiving is invaluable,” says Fishbein. “Through comprehensive assessment, we’re able to provide more precise coaching to help us enhance agent performance.”
Elevating customer experiences
Since implementing Auto QA, Cox Automotive has seen its QA scores rise by
2–3%, which translates directly into better customer experiences. The streamlined process empowers agents to improve support delivery at every touchpoint.
Fishbein is optimistic about even more gains ahead for Cox Automotive.
“Insights from Auto QA enable us to maximize the customer experience by empowering agents to deliver outstanding service in every interaction,” he says.
Advancing capabilities
Cox Automotive’s collaboration with Observe.AI extends beyond Auto QA. The COE team is now exploring new features to boost customer service quality. This includes rolling out real-time capabilities that automate case documentation and provide immediate solutions through Summarization AI and Knowledge AI.
“We’ve built a great partnership with Observe.AI,” shares Fishbein. “It’s now a crucial part of our quality processes at Cox Automotive. Our relationship has grown over the years, and we’re excited to keep evolving together.”
