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DevRel Collective 2021 Salary Survey - Introduction

The DevRel Collective (DRC) has been running a survey over the past few quarters regarding the salaries and benefits paid to DevRel professionals around the globe. The DRC exists to facilitate sharing information, resources, and encouragement among the professional Developer Advocates, Evangelists, and Technical Community Manager community with ~2000 members and counting.   

In this report we take a look at some of the results from the survey with a view to summarising the key themes. 

The purpose of the survey


A challenge faced by many practitioners has been a relative scarcity of reference materials pertaining to career growth and salary trajectories. The sometimes ambiguous nature of titling across companies, the recent growth of DevRel as a formalized profession, and the frequently small size of teams, along with the variation of where DevRel “sits” within an organization all contribute to a lack of clarity around compensation.  

The survey is intended to offer insight into the state of compensation in DevRel. We examine roles including and adjacent to “developer advocate”, “evangelist” and “technical community manager.” Our twofold goal in its creation was to: help individual contributors (non-managers) ensure that their salary is comparable for their geographic region and experience level; and assist hiring managers as they calculate appropriate budgets for headcount.

It is our hope that this report can function as a balanced resource to both employees and managers to arrive at an understanding around norms. 

Survey design

We spent a great deal of care and time on survey design. The full survey questions have been added as an appendix.


Some of the questions are qualitative and some are quantitative.  That said, it was perhaps inevitable that the responses occasionally begged additional questions which were beyond the scope of the survey. We discuss why those choices were made in the requisite sections.

Areas of inquiry included: 

  • Cash salary
  • Benefits and perquisites (also known as “perqs” or “perks”)
  • Total compensation
  • Country respondent is based out of
  • Sentiment on compensation
  • Job titles
  • Length of tenure in industry and time at current position
  • Career level and manager/non-manager status
  • Ethnicity
  • Gender
  • Age
  • Sexual orientation

The survey topics are of a sensitive nature. It was therefore important to preserve anonymity of, and restrict access to, the raw data. The raw data is viewable only by the admin team and data scientist. We only use it to create visualizations that will show (among other things) average compensation for specific geographic areas.


We also spent a lot of time digging into the questions themselves to identify the real underlying questions. For example, some questions are very cut and dry such as: what country do you live in? While others are sentiment based: what’s the cost of living in your area? The reasons for that are cost of living (CoL) can be relative, and also some regions vary widely in pricing over a small geographic area. So the real inquiry is not about the cost of typical rent in your area, it’s about the lived experience.

For every question we added or deleted, we considered what story its data could tell in combination with other fields.

A note on the data

This sample is small (~150 replies,) and highly skewed to the US (~80 replies). It is therefore difficult to draw general conclusions from this data that can be applied to the wider DevRel community, and care should be taken when doing so. 

It is our hope that future iterations of the survey will be more geographically diverse across non-US markets. Please see the location sections if you would like to learn more.

The survey looks at data collected in October-December 2020. Some later responses trickled in after that time (11 in total). The survey link was promoted in the DevRel Collective Slack, and also posted to Twitter, LinkedIn and dev.to as well as several industry newsletters.

There were some areas where it was important to understand the potential impact of marginalization but were hindered by a small sample set. We sometimes made the decision to report on the dominant group versus the rest of the responses. After some consideration we decided it was preferable to show what we were able. This is in no way meant to flatten the experiences of people, create an improper hierarchy, or “other” anyone. It was the best we could do to bring back some insights without de-anonymizing the data. 

For the results below, we have worked to summarize what we have from the survey responses only. To validate any of these findings more generally would require more focused work, which we may spend additional time on in future iterations.

It’s important to remember that the lumping together of disparate groups into the “non-X” category can be misunderstood as non-X == Y.  Actually non-X is a catchall category. In other words, what we learn is mostly about the majority group. We’re hoping this will change in future interactions. In the meantime, this data can offer some amount of insight to people interested in equity. This is important because a key factor of marginalization is that members tend to have less access to information available to them versus the information shared across in-groups.

A reminder about the models contained in this document: please bear in mind that these are simple models, and you should use them to augment your own experience. The sample is small. We would want to look at more robust analyses before we make any sweeping claims for a specific individual. 

Processing

Some steps had to be taken to make the data usable. Due to the small sample size, it wasn’t possible to process each country in its own currency. Given that the majority of the survey responses came from the US, recent currency exchange rates were used to convert the `Salary` responses into US Dollars.

We filtered one or two unrealistic replies (over $700,000) to prevent skewing the results – these seem unlikely to be real responses (although well done to whoever that is if they are real!)

Before diving in: the larger conversation

As mentioned above, our goal for this survey is to get information to people on both sides of the table to help move forward productively with conversations grounded in data. To that end, we aren’t selling anything: no products, memberships, or courses. We don’t charge to view the report or require signing up for a mailing list to view our results. 

If you would like to offer some kind of support, here are some ideas:

  • The best way to do so is to help support is by simply getting the word out: Polywork, Twitter, LinkedIn are great places to start
  • Social media is great but so is old-fashioned word of mouth (for example at the hallway track of your next event)
  • Please let your colleagues and managers know about it
  • Finally, if you have contacts at any of the industry “salary database” resources and can facilitate introductions we would love to speak with them about how to get DevRel represented in meaningful ways. This would also help streamline conversations for managers who currently resort to plugging in (commonly conflicting) values of engineering and marketing at review time

The more people who know about this survey, the richer the results will become with every iteration! We can be reached at team@devrelcollective.fun

This request is completely optional, of course. If you choose to engage privately with the results, that’s totally fine — either way, we are happy to have been a resource in your career journey.

TABLE OF CONTENTS

Introduction

Pt. 1 | Pt. 2 | Pt. 3 | Pt. 4 | Pt. 5 | Pt. 6 | Pt. 7 | Pt. 8

Conclusion and Takeaways

Appendix A: | Appendix B:

SPECIAL THANKS TO OUR DATA SCIENTIST, GREG SUTCLIFFE
Greg Sutcliffe has been working in community management for a decade, and is currently the Principal Data Scientist for the Ansible Community. He's interested in how appropriate use of data can inform the development and governance of communities, especially with regards to open source projects. He also likes cooking.

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