# How Edelman uses Labelbox

As published on [labelbox.com](https://labelbox.com/customers/edelman-customer-story/). Captured by usedby on 2026-10-07.

- Company: [Edelman](https://www.usedby.ai/companies/edelman.md)
- Tool: [Labelbox](https://www.usedby.ai/tools/labelbox.md)
- Industry: [Agency & Studio](https://www.usedby.ai/companies/industry/agency-studio.md)
- Teams: Data Science & Machine Learning, Edelman Data & Intelligence (DxI)

## What the story says

Edelman's Data & Intelligence team uses Labelbox to produce training data for proprietary models that score consumer trust in brands from web text. The process includes selecting contributors, incorporating internal domain-expert feedback, and assessing data quality, with the Python SDK connected to its AWS data lake.

Summary written by usedby from the source page, in English. The figures are those of Labelbox and Edelman, not ours.

> The key step was folding in internal domain experts who carry institutional knowledge of brand trust, answering questions like “what indicates trust?” and “how do you spot a crisis?” to refine the signal.

> one of the most important components is around domain expertise. Expert feedback is expensive. It's less expensive than it used to be thanks to services like Labelbox, but it’s still a time intensive process, so we first need to incorporate the domain expertise that we have across our business and our clients and then pull that into ML projects.
>
> David Bartram Shaw, SVP, Global Head of Data Science & Machine Learning at Edelman

## What usedby checked

We compared the story with its live page on 2026-10-07.

- Checked: the passage quoted above is copied word for word from the page, near the name of Edelman.
- Checked: Edelman uses Labelbox. Confirmed line. Latest check across sources: 2026-10-07.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/edelman-labelbox · How we check: https://www.usedby.ai/methodology