Latino members share tips for networking on LinkedIn

Today, Collective Inc. chief executive Omar Ramirez is a success in business – and a popular, admired presence on LinkedIn. But it wasn’t always that way. In his early 20s, during the 2008-09 economic slump, Ramirez struggled to find his first job out of college.

“It was a very painful experience,” Ramirez says. Nobody wanted to hire the young man with a B.A. in religious studies from Pennsylvania’s Moravian University. Even when he found work, it wasn’t glamorous. He became a facilities assistant at Google’s New York offices, fielding service tickets and delivering mail.

Then his luck started to change. Ramirez built up his LinkedIn presence, connecting with a wide range of recruiters who might know of external opportunities. He switched to a new Google role as a space-planning assistant – and began to sense a path toward a high-impact career overseeing global workplace operations. “I was starting to explore,” he recalls.?

Over the next decade, Ramirez kept landing bigger jobs at the likes of Netflix, Dropbox, Stripe and Atlassian. What’s more, “I never actually applied for a single job,” he adds. “I just kept getting recruited by people who knew me through LinkedIn.”

For all the power of Ramirez’s example, many Latino members on LinkedIn may lack the strong professional networks that can fuel career success. A detailed analysis by LinkedIn’s Economic Graph team – based on professional-network data for millions of U.S. members who self-reported their race – reveals the following:?

• On average, LinkedIn networks for Latino members are 20.2% smaller than White members. (Black members’ networks are 13% smaller than their White counterparts.) For this section’s statistics, the term Latino is used to cover members of all genders.?
• Latinos receive 7.5% fewer invitations and have a 2.0% lower acceptance rate on the invitations they send, relative to White members.??
• Among women, Latinas have the smallest average network sizes of the groups we examined. Theirs is 33.5% smaller than the national average and 42.6% smaller than the average network size of White men.
• The gap in network growth rates between White and Latino members is shrinking. In early 2018, White members added 8.4% more connections monthly compared with Latino members. By early 2023, that difference diminished to a 1.9% larger rate for White members.
• Latino members’ overall network strength averages in the 46.5th percentile, 3.5 percentile points below the all-member median. The explanation is two-fold. Latino members have fewer connections on average – and their network connections are less likely to be in senior positions in industries and occupations poised to help their careers.?
• One potential win: Latino members’ networks have less redundancy than what’s typical for the entirety of LinkedIn’s community. This creates a higher share of so-called “weak ties” with more distant contacts, whose wider professional circles can increase the flow of information about job opportunities.

For Latino members who have built strong networks on LinkedIn, success often started with early advice – and encouragement – from a trusted colleague. Norma Ortega, an instructional designer in southern California, says her breakthrough came a couple years ago, when she didn’t see a path for advancement via her job at the time.

“My very dear manager said: ‘You need to open up a LinkedIn account,’” Ortega recalls. “I was hesitant at first. I’m not a big social media person. But then I said: ‘I’ll do it.’” Well-known within her organization, she had little trouble building an initial network of 75 to 150 colleagues from work.

Ortega identified people at other organizations, who held job titles similar to hers, and reached out to connect with them. She knew she wanted to keep working remotely, and since that wasn’t a strong option in her job at the time, she wanted to build bridges to other organizations that might be a better fit.

“I was on LinkedIn every day,” Ortega recalls. She signed up for various LinkedIn Groups that cater to learning and development professionals and drew energy from the helpfulness of her new connections. As Ortega puts it: “Our field is very willing to collaborate and share tips and tricks.”?

Expanding a network by reaching out to people you don’t know well can seem daunting, especially for minorities who want to “aim high,” and be connected to their industry's big decision makers. Fashion brand expert Keith Gonzales, whose family is Filipino, says it helps to bunch up these long shots in ways that take the stress out of trying.

“In business meetings, I’ll throw out a hundred ideas, and if just one of them gets traction, that’s a success,” Gonzales says. “It’s the same thing with making new connections.” His roster of 1,300 LinkedIn connections includes some titans in his field, in a payoff for his ambitious outreach. As he points out: “I just need one person to say yes.”

LinkedIn data shows that Latino members are much more likely to exchange invitations with other Latino members, rather than connecting with other racial or ethnic groups. (Researchers call this pattern homophily.)?

For example, Latino members’ rate of seeking connections with other Latino members is 47% above the all-member U.S. rate of invitations sent to Latino members. Similarly, Latino members' rate of receiving invitations from other Latino members is 60% higher than the all-member norms for such invitations.

Omar Ramirez, the workplace design and construction expert, says he’s been fortunate to work at companies “that have always had a lot of different types of people.” His LinkedIn network today consists of nearly 6,000 connections, plus another 1,000 or more people who follow him but aren’t connected.?

Ramirez is prominent enough now to receive flurries of incoming connection requests. He says he tries to accept many of them, unless he feels they are the prelude to sales pitches that he doesn’t need. “I try to be very generous with my time,” he says. Because his specialty of workplace design and construction is a broad field, he says, “I’ve ended up connecting with economists, business leaders and analysts.”

You can expect more research from LinkedIn’s data teams in the future, looking at the ways that ethnicity, race and gender interact with the nature of members’ professional networks on LinkedIn. Our data-driven analysis will look at aggregate patterns, but we’ll also be mindful that each member’s story is unique. Or, as Ramirez points out: “My mom’s Irish and my dad is Peruvian. I grew up in both worlds.”?

Methodology

LinkedIn’s Economic Graph researchers limited analyses to non-restricted, active accounts. Race demographic analysis is further limited to individuals who self-identified their race and gender. Because self-identified members comprise approximately 5% of total U.S. members, results based on this subset may not be generalizable to the entire U.S. LinkedIn membership. Moreover, the entire US LinkedIn membership may not be representative of the overall U.S. population. This may be particularly true for the industries and occupations in which members work, with LinkedIn being overrepresented in certain professional fields such as engineering. Differences between groups may at least partially reflect differences in LinkedIn membership concentration between occupations and industries. Despite these limitations, our analysis can still provide valuable insights into how network trends influence economic opportunities.?

This work draws from the anonymized and aggregated profile information of LinkedIn's 202+ million U.S. members. As such, it is influenced by how members choose to use the platform, which can vary based on professional, social, and regional culture, as well as overall site availability and accessibility. These insights show aggregated information for the corresponding period following strict data quality thresholds that prevent disclosing any information about specific individuals in order to ensure members’ privacy.

?Gender identity isn’t binary, and we recognize that some LinkedIn members identify beyond the traditional gender constructs of “man” and “woman.” If not explicitly self-identified, we have inferred the gender of members included in this analysis either by the pronouns used on their LinkedIn profiles or inferred based on first name. Members whose gender could not be inferred as either man or woman were excluded from this analysis.?

LinkedIn senior staff economist Matthew Baird, data scientist Danielle Kavanagh-Smith and senior AI researcher Osonde Osoba contributed to this article.