# How Cox Automotive uses Observe.AI

**2–3%** rise in QA scores

As published on [observe.ai](https://www.observe.ai/customers/cox-automotive). Captured by usedby on 2026-10-10.

- Company: [Cox Automotive](https://www.usedby.ai/companies/cox-automotive.md)
- Tool: [Observe.AI](https://www.usedby.ai/tools/observe-ai.md)
- Industry: [Logistics & Supply Chain](https://www.usedby.ai/companies/industry/logistics-supply-chain.md)
- Teams: Client Operations, Contact Center, Center of Excellence

## The use case: how Cox Automotive deploys Observe.AI

Cox Automotive uses Observe.AI's Auto QA to standardize quality assurance across the contact centers of its 13 brands. It automatically evaluates interactions using a unified evaluation form, replacing a small random sample of calls per agent.

Summary written by usedby from the source page, in English. The figures are those of Observe.AI and Cox Automotive, not ours.

> 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.

- **90,000**: “With Auto QA, Cox Automotive has scaled this process to more than 90,000 evaluations per month, including approximately 2,500 manual evaluations.”
- **100%**: “Auto QA automatically evaluates up to 100% of interactions to gain visibility into teams’ strengths and weaknesses without bias.”
- **13 brands**: “rolling it out across contact centers in its 13 brands to unify the evaluation process.”

> 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.
>
> Matthew Fishbein, Director on the Client Operations team

Source: [observe.ai](https://www.observe.ai/customers/cox-automotive), captured 2026-10-10.

## Other AI tools used by Cox Automotive

- [AWS Bedrock](https://www.usedby.ai/tools/aws-bedrock.md) — Confirmed
- [HighRadius](https://www.usedby.ai/tools/highradius.md) — Observed
- [Jasper](https://www.usedby.ai/tools/jasper.md) — Observed

## Observe.AI users in Logistics & Supply Chain

- [Doordash](https://www.usedby.ai/companies/doordash.md) — Confirmed

## What usedby checked

We compared the story with its live page on 2026-10-10.

- Checked: the figure 2–3% is on the page; its label is our wording.
- Checked: the passage quoted above is copied word for word from the page, near the name of Cox Automotive.
- Checked: each number in our summary is printed on the page.
- Checked: Cox Automotive uses Observe.AI. Confirmed line. Latest check across sources: 2026-10-20.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/cox-automotive-observe-ai · How we check: https://www.usedby.ai/methodology