# How Career Karma uses Regal

**2x**: “2x Lift in Conversions”

As published on [regal.ai](https://www.regal.ai/case-study/career-karma). Captured by usedby on 2026-10-08.

- Company: [Career Karma](https://www.usedby.ai/companies/career-karma.md)
- Tool: [Regal](https://www.usedby.ai/tools/regal.md)
- Industry: [EdTech & E-learning](https://www.usedby.ai/companies/industry/edtech-e-learning.md)
- Teams: enrollment team, Community Managers, Community Producers

## What the story says

Career Karma uses Regal to automate outbound calling to inbound leads, prioritize fresh leads, and route each lead to a specific Community Producer through configurable journeys. It also added Regal as its SMS partner for omnichannel journeys.

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

> With Regal.io, Career Karma was able to automate calling, prioritize the right leads and take advantage of real-time data and custom journeys to deliver much better customer experiences.

- **25%**: “25% Lift in Engagement Rate”
- **10x**: “10x Increase in Conversations”
- **70%**: “70% Task Completion Rate”
- **2x**: “2x Increase in Total Subscribers”

> With Regal.io's journey builder and intelligent routing capabilities, we are able to streamline our outbound sales process. We are able to assign a prospective student to our coaching team to create a more consistent and impactful experience for our community.
>
> Jacques Rojahn, Head of Sales

## What usedby checked

We compared the story with its live page on 2026-10-08.

- Checked: the figure 2x is printed word for word on the page, near the name of Career Karma.
- Checked: the passage quoted above is copied word for word from the page, near the name of Career Karma.
- Checked: Career Karma uses Regal. Confirmed line. Latest check across sources: 2026-10-08.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/career-karma-regal · How we check: https://www.usedby.ai/methodology