By implementing Auto QA to standardize processes across its contact centers, the company has enhanced operations and improved agent performance.
Cox Automotive is the world’s largest automotive services and technology provider. Fueled by the largest breadth of first-party data fed by 2.3 billion online interactions a year, Cox Automotive tailors leading solutions for car shoppers, auto manufacturers, dealers, lenders, and fleets. The company has over 29,000 employees on five continents and a portfolio of industry-leading brands that include Autotrader®, Kelley Blue Book®, Manheim®, vAuto®, Dealertrack®, NextGear Capital™, CentralDispatch® and FleetNet America®. Cox Automotive is a subsidiary of Cox Enterprises Inc., a privately owned, Atlanta-based company with $22 billion in annual revenue.
Cox Automotive, a leading player in vehicle advertisements, digital retailing, and automotive software solutions, has rapidly expanded in recent years, growing its portfolio to more than 13 brands. However, this expansion led to a fragmented approach to contact center quality assurance (QA), with each brand operating independently.
To address this, the company’s Center of Excellence (COE) sought to standardize QA processes across its contact center organization.
“The goal of our COE is to consolidate the contact center operations across Cox Automotive to maximize our use of tools and deliver an exceptional client experience,” explains Matthew Fishbein, a Director on the Client Operations team.
In particular, the COE team aimed to find a solution that could create consistent QA processes across various contact centers.
By deploying Auto QA from Observe.AI, the team unified its QA operations and created a consistent, quality experience for customers.
Cox Automotive’s contact centers range from 10 agents in the smallest to 150–200 agents in the largest, totaling 2,000 support agents across the enterprise. These centers primarily provide inbound customer support, and their QA processes varied widely depending on the maturity of the brand when it was acquired. Some newer brands had not yet invested heavily in their contact centers, while more established ones had well-developed programs and processes in place.
These differences created the need to standardize QA processes. Initially, the COE team focused on manually scoring quality evaluations within the Observe.AI platform and onboarding teams from various contact centers.
“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,” shares Fishbein.
To further enhance efficiency and agent performance, the team integrated Auto QA from Observe.AI, rolling it out across contact centers in its 13 brands to unify the evaluation process.
Auto QA automatically evaluates up to 100% of interactions to gain visibility into teams’ strengths and weaknesses without bias. This streamlined approach improves consistency while enhancing the overall efficiency of QA practices. The unified evaluation form simplifies the QA process and ensures that all contact centers adhere to the same high standards.
Observe.AI Moments—key instances in customer interactions that reveal specific insights and trends—are crucial to Cox Automotive’s new QA system. The standardized evaluation form integrates around 25 Moments and over 2,000 keywords and phrases, ensuring that the automated QA process captures all relevant aspects of agent interactions.
According to Fishbein, “This approach provides a comprehensive and consistent evaluation framework while allowing brands the flexibility to maintain their unique identities within the overall QA structure.”
Implementing Auto QA has significantly transformed the evaluation process by vastly expanding the scope of call analysis.
Previously, performance evaluations relied on a random sample of just four calls per month per agent, which often introduced high grading subjectivity and limited visibility. With Auto QA, Cox Automotive has scaled this process to more than 90,000 evaluations per month, including approximately 2,500 manual evaluations.
This shift provides a more accurate and comprehensive view of agent performance by eliminating biases and unlocking enhanced scale, visibility, and accuracy. The higher volume of evaluations generates substantial data, allowing for more precise scoring and improvement, particularly for compliance and legal-related cases.
Auto QA also provides valuable insights into 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.”
Since implementing Auto QA, Cox Automotive has seen a 2–3% rise in QA scores.
Fishbein anticipates further benefits from the implementation. “Insights from Auto QA enable us to maximize the customer experience by empowering agents to deliver outstanding service in every interaction.”
Looking ahead, the COE team is exploring the incorporation of additional Observe.AI features, such as real-time capabilities. Future enhancements will help the team automate case documentation and provide instant answers to customer queries using Summarization AI and Knowledge AI.
“We’ve built a great partnership with Observe.AI,” says 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.”
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