Diversity, Equity, and Inclusion at Loom
What we stand for
Loom enables individuals, teams, and organizations to communicate more authentically. We aspire to build a company and a product where everyone feels seen, heard, and appreciated.
What we’re doing
We want to build a culture where everyone has what they need to thrive and where identity is not a barrier to impact. We're focused on doing the foundational work of making this a reality. We still have a long way to go, but we’re committed to seeing it through.
- Representation
- We diversify our interview pipelines through our own sourcing efforts and partnerships with organizations like Techqueria, Women Impact Tech, and Women Who Code.
- Using third-party tools, we audit each of our job descriptions for gendered, ethnocentric, or otherwise biased language.
- We train our hiring managers to use a structured interview process and assess for culture addition rather than culture fit.
- We conduct a bi-annual DEI Survey to track and report who we are internally and externally.
- Pay Equity
- We tie compensation to role, not location, allowing Loommates to choose where they live within a country without impact to their pay.
- We follow a standardized offer process to ensure all prospective Loommates receive consistent and transparent offers.
- We conduct a structured compensation review twice a year to check for pay equity, and make any adjustments when necessary.
- We ensure our equity program is accessible to all by offering early exercise and longer post-termination exercise windows.
- Growth & Mobility
- We conduct 360 reviews and a structured promotion process twice a year so we recognize Loommates who have grown in their roles.
- We have an internal transfer process that allows Loommates to take on new functional roles where possible.
- Our unconscious bias training is mandatory for managers and open to all Loommates.
- We measure and report on engagement and inclusion metrics by different groups.
- Community
- Starting in June 2020, we began to donate 1% of monthly recurring revenue to organizations who make the world more equitable and inclusive. In 2020, we donated to the American Civil Liberties Union.
- We made Loom free for educators so they could sustainably use Loom during the COVID pandemic.
- We support accessibility in our product and marketing, including developing video transcription functionality.
Who we are
It’s not enough to make an effort — we want to make progress. The data below shapes our thinking as we work to support the teammates we have, and reach out to those we haven’t met yet. This is a mix of data we collect using U.S. government reporting standards (Equal Employment Opportunity, or EEO) as well as self-reported data we gather using anonymous surveys. We do not track self-reported data for team-level reporting in order to preserve anonymity. We plan to continue to survey Loommates and will update this page accordingly.
Age
Self-reported data from 187 responses
18-24 | 6% |
25-34 | 70% |
35-44 | 18% |
45-54 | 6% |
55-64 | 0% |
65+ | 0% |
I prefer not to disclose | 0% |
Disabilities
Self-reported data from 187 responses
Blind | 0% |
Chronic illness or pain | 4% |
Deaf or hearing-impaired | 1% |
Intellectual disability | 0% |
Neurodivergent | 9% |
Wheelchair users | 0% |
None of these apply | 86% |
Epileptic | 1% |
Education
Self-reported data from 187 responses
Employee Education
Less than high school or GED equivalent | 0% |
High school or GED equivalent | 7% |
2 year college degree | 3% |
4 year college degree | 73% |
Advanced degree (MA, JD, MD, PhD, etc) | 18% |
Parent or Guardian Education
Less than high school or GED equivalent | 4% |
High school or GED equivalent | 14% |
2 year college degree | 7% |
4 year college degree | 34% |
Advanced degree | 41% |
Family
Self-reported data from 187 responses
Parent/Legal Guardian
No children | 73% |
Partnered parent/legal guardian | 26% |
Single parent/legal guardian | 2% |
Caregiver (other than children)
Yes | 6% |
No | 78% |
Does not apply | 17% |
Gender
The below includes a mix of EEO and self-reported data. Note: EEO/U.S. Federal Govt. reporting standards on gender only allow respondents to select "Male" or "Female." We affirm the full spectrum of gender identity and the distinction between sex and gender, so if you see different wording in the self-reported data sections, that’s why.
Gender identity
Self-reported data from 187 responses
Agender | 0% |
Bigender | 0% |
Genderfluid | 0% |
Man | 47% |
Non-binary | 1% |
Woman | 52% |
Transgender
Self-reported data from 187 responses
No | 100% |
Yes | 0% |
Gender by team
EEO reported data from 187 responses
| All teams | |
|---|---|
| Female | 51% |
| Male | 48% |
| Leadership | |
| Female | 69% |
| Male | 31% |
| Engineering | |
| Female | 26% |
| Male | 73% |
| Non-binary | 1% |
| Product | |
| Female | 50% |
| Male | 50% |
| Design | |
| Female | 42% |
| Male | 38% |
| Data | |
| Female | 62% |
| Male | 71% |
| Revenue | |
| Female | 64% |
| Male | 36% |
| Marketing | |
| Female | 71% |
| Male | 29% |
| Customer Support | |
| Female | 73% |
| Male | 27% |
| People | |
| Female | 100% |
| Male | 0% |
| Operations | |
| Female | 74% |
| Male | 26% |
Native Language
Self-reported data from 187 responses
Native English speaker | 81% |
English is not my native language | 19% |
Race/Ethnicity
The below includes a mix of EEO and self-reported data. Note: EEO/U.S. Federal Govt. reporting standards on race/ethnicity include fewer categories than self-reported data.
Race/ethnicity
Self-reported data from 187 responses
African American/Black | 4% |
East Asian (including Chinese, Japanese, Korean, and Mongolian) | 22% |
Hispanic/Latinx | 4% |
Middle Eastern | 1% |
Native American/Alaskan Native | 1% |
Pacific Islander | 0% |
Southeast Asian (including Burmese, Cambodian, Filipino, Hmong, Indonesian, Laotian, Malaysian, Mien, Singaporean, Thai, and Vietnamese) | 5% |
South Asian (including Bangladeshi, Bhutanese, Indian, Nepali, Pakistani, and Sri Lankan) | 13% |
White | 50% |
Race/ethnicity by team
EEO reported data from 187 responses
| All teams | |
|---|---|
| White | 54% |
| Asian | 32% |
| Black or African-American | 5% |
| Hispanic/Latinx | 3% |
| Two or more races | 5% |
| Leadership | |
| White | 56% |
| Asian | 28% |
| Black or African-American | 46% |
| Hispanic/Latinx | 6% |
| Two or more races | 3% |
| Engineering | |
| White | 36% |
| Asian | 50% |
| Black or African-American | 3% |
| Hispanic/Latinx | 8% |
| Two or more races | 3% |
| Product | |
| White | 63% |
| Asian | 25% |
| Black or African-American | 13% |
| Hispanic/Latinx | 0% |
| Two or more races | 0% |
| Design | |
| White | 38% |
| Asian | 54% |
| Black or African-American | 0% |
| Hispanic/Latinx | 8% |
| Two or more races | 0% |
| Data | |
| White | 21% |
| Asian | 64% |
| Black or African-American | 7% |
| Hispanic/Latinx | 0% |
| Two or more races | 0% |
| Revenue | |
| White | 82% |
| Asian | 7% |
| Black or African-American | 4% |
| Hispanic/Latinx | 0% |
| Two or more races | 7% |
| Marketing | |
| White | 71% |
| Asian | 14% |
| Black or African-American | 7% |
| Hispanic/Latinx | 0% |
| Two or more races | 7% |
| Customer Support | |
| White | 73% |
| Asian | 9% |
| Black or African-American | 0% |
| Hispanic/Latinx | 0% |
| Two or more races | 18% |
| People | |
| White | 20% |
| Asian | 50% |
| Black or African-American | 10% |
| Hispanic/Latinx | 10% |
| Two or more races | 10% |
| Operations | |
| White | 35% |
| Asian | 39% |
| Black or African-American | 17% |
| Hispanic/Latinx | 9% |
| Two or more races | 0% |
Sexual Orientation
Self-reported data from 187 responses
Asexual | 2% |
Bisexual | 5% |
Gay | 4% |
Heterosexual | 84% |
Lesbian | 2% |
Pansexual | 1% |
Queer | 2% |
Veteran
Self-reported data from 187 responses
No | 99% |
Yes | 1% |