Introducing: Open Source Cohort Analysis

Now you can build your own cohort analysis tools, with total control over the logic, look, and feel.

Today we’re releasing a new open source tool for cohort analysis. Cohort analysis is incredibly valuable when you’re trying to understand retention and patterns of behavior over time. If you’re not familiar with retention analysis by cohort, you can read more about the fundamental concepts here.


Outside of the obvious community benefits of open source contributions, there are a few reasons we wanted to share this simple tool:

  1. Easier cohort and retention analysis on Keen IO data You’ve always been able to run retention analysis on Keen data, but this is the first time we’ve released a tool for visualizing the results.
  2. Open source analytics building blocks Keen IO’sanalytics building blocks enable super custom, powerful analysis. Looking at the source code, you can see how in looping over a simple funnel analysis you can build this detailed behavior view. What else could you build with these powerful primitives?
  3. Give developers totally customized cohort analyses based on their business If you’ve ever been frustrated that the retention views in your analytics tools don’t quite match how your business works, or didn’t quite display the information in a way that made sense to you, now you have something to fork and make your own. As with most things we build here at Keen IO, you could even white label something like this in your product.

To start running your own cohort analysis you can create a free Keen IO project and fork our open source repo. We hope you’ll find this useful, and share your feedback in the Keen IO community slack.

Happy coding

How I Wrapped My Head Around Analytics-as-a-Service

In July I joined Keen IO, transitioning from working with organizations focused on the software development lifecycle (SDLC) to data analytics. Keen’s analytics SaaS is an end-to-end platform that allows organizations to approach data from an analytics-as-code perspective. To speed my learning process I began creating comparisons across the two industries to better understand the value and benefits that customers glean from using an API-centric analytics platform. (We call it the Intelligence API.)

In this post I’ll be sharing my thought process as I developed a deeper understanding of analytics and how it relates to SDLC concepts: specifically agile, continuous integration, continuous deployment, DevOps, and infrastructure-as-code. For a bit more background on each of these terms, feel free to read my previous blog post.

Applying Agile to Analytics

Agile is no longer just a software development term. It is now ubiquitous across marketing, sales, and organizational design. The primary principles of agile revolve around delivering what the customer needs through short sprints involving collaborative teams.

As I started contemplating analytics-as-a-service, I discovered that organizations want to be able to start collecting data on web, mobile, or IoT devices with ease and almost immediately, rather than having a drawn-out process of building an entire in-house analytics infrastructure from scratch.

The goal is that the heavy lifting should be taken care of on the backend by a service that can be responsive to peaks and valleys and the projected growth of the data collected. It doesn’t take an organization long to get started with an AWS server, and analytics should be no different, where you should be able to start making data-driven decisions to guide product direction, customer acquisition, and resource allocation strategy within days.

Achieving Continuous Integration

Continuous integration grew out of a need to add automation to agile practices, first starting with the concept of accomplishing automated unit tests on the host machine of a developer. This quick feedback allowed developers to fix their code as it was still fresh in their minds and get instant feedback regarding quality.

By using an analytics-as-code approach via API, developers can automatically gather data from cached queries, allowing these organizations to quickly ask questions of large datasets and return near-instant results. This ability to run complex queries without a lag-time allows analysts and business leaders to build momentum on ideas and begin executing on their insights in the time it takes to run a CI build.

Continuous Delivery and Deployment of Data

Continuous delivery and deployment started to become ubiquitous as top web organizations began promoting their ability to roll out code to subsets of their user bases for A/B tests in production, with the ability to quickly deploy fixes and updates while production was still running.

I found this process similar to the way analytics-as-a-service provides flexibility with data models, allowing users to collect and store unstructured data that can be analyzed in the future alongside yet-to-be-collected data from emerging technologies such as Internet of Things, Virtual Reality (VR) and Augmented Reality (AR). In this way, organizations never have to limit their future analytics capabilities by being forced into an overly rigid data model today.

Analytics Through the Lens of DevOps

While all of the unit and production testing grew in importance, organizations realized that they needed to adapt their IT operations teams to be more flexible and able to respond to internal teams’ requests. This led to the prominence of DevOps, where traditionally siloed operation teams became part of agile development teams, with the goal of delivering configured infrastructure on demand.

With analytics-as-a-service, organizations don’t need to rely on specialized data scientists, data engineers, database architects, and datacenter architects to deliver powerful analytics capabilities. Instead, the ability to ask and answer complex questions via code allows every team, from sales to marketing and product to engineering to begin discovering value.

If all of these teams can easily access, query, and customize their data views to match their specific needs then their day-to-day operations will be optimized and they essentially have a data scientist on each of their teams. One great thing I learned about Keen was that companies can even provide this ability to their own customers by integrating data visualizations directly into their products as a native part of the user experience.

From infrastructure-as-code to analytics-as-code

The most exciting evolution that unlocks all of the above capabilities for the SDLC is the adoption of infrastructure-as-code. Initially popularized by Amazon, infrastructure-as-code is now a core tenet of many IaaS or PaaS offerings, where you’re able to modify, setup, or tear down your infrastructure by utilizing an API or CLI.

Admittedly, not every analytics-as-a-service provider follows this model, but Keen has always maintained the API as the backbone of the service, with all analytics capabilities built on top of it: collection, storage, query, visualization, access, account provisioning, and more being added all the time. Since our customers are able to use our services in a programmatic fashion (a la: analytics-as-code), they are able to scale from 1 to thousands of unique projects, collections or analysis by writing a few lines of code. They don’t need to build up a huge in-house infrastructure or assemble a specialized IT and data science team to run the system. A developer is all that’s required.

Closing Thoughts

This post is by no means trying to make a comprehensive comparison of every aspect of these technologies. My goal was to walk through my own thought process in case it helps others with an SDLC background make sense of the comparatively new field of analytics-as-a-service.

If you’d like to discuss these ideas in more detail or if you have any follow-up questions about Keen, analytics-as-a-service, or analytics-as-code, I’d be happy to chat. Feel free to reach out to me at

Vladi Semenov

Strategic, Individualizer, Relator, NBA Fan

25 Examples of Native Analytics Data Designs in Modern Products

Data is so ubiquitous, we are sometimes oblivious to just how much of it we interact with—and how many companies are making it a core part of their product. Whether you’re aware of it or not, product leaders across industries are using data to drive engagement and prove value to their end-users. From Fitbit and Medium to Spotify and Slack, data is being leveraged not just for internal decision-making, but as an external product offering and differentiator.

These data-as-product features, often displayed as user-facing dashboards, are known as “native analytics” because they are offered natively within the context of the customer experience. We’ve gathered 25 examples of native analytics in modern software to highlight their power and hopefully inspire their further adoption.

Ahrefs Lets Website Owners Drill Down on Referrers

Every day, Ahrefs crawls 4 billion web pages, delivering a dense but digestible array of actionable insights from 12 trillion known links to website owners (and competitors), including referrers, social mentions, keyword searches, and a variety of site rankings.

AirBnB Helps Hosts Improve their Ratings and Revenue

In addition to providing intimate housing options in 161 countries to 60M+ guests, Airbnb also reminds its more than 600,000 hosts of the fruits of their labors—with earnings reports—and gently nudges them to provide positive guest experiences—with response rates and guest ratings.

Etsy Helps Build Dream Businesses

The go-to online shop Etsy, which boasts 35M+ products, provides its 1.5M+ sellers with engagement and sales data to help them turn their passion into the business of their dreams.

Eventbrite Alerts Organizers to Sales and Check-ins

Event organizers use Eventbrite to process 4M tickets a month to 2M events in 187 countries. They also turn to Eventbrite for real-time information, to stay up to date with ticket sales and revenue, to track day-of check-ins, and to understand how to better serve and connect with their attendees.

Facebook Expands Reach of Paid Services

With Facebook striving to take a bigger bite out of Google’s share of online ad sales, its strategic use of data has spread beyond the already robust Facebook Ads Manager to comprehensive metrics for Pages, including, of course, key opportunities to “boost” posts.

Fitbit Helps Users Reach Their Fitness Goals

Fitbit’s robust app, connected to any of its eight activity trackers, allows its 17M+ worldwide active users to track steps, distance, and active minutes to help them stay fit; track weight change, calories, and water intake to stay on pace with weight goals; and track sleep stats to help improve energy levels.

GitHub Tracks Evolving Code Bases

GitHub, the world’s largest host of source code with 35M+ repositories, allows its 14M+ users to gain visibility into their evolving code bases by tracking clones, views, visitors, commits, weekly additions and deletions, and team member activity.

Intercom Targets Tools—and Data—to Users’ Needs

Intercom, the “simple, personal, fun” customer communications platform, delivers targeted data-driven insights depending on which of the platform’s three products a team uses: Acquire tracks open, click, and reply rates; Engage tracks user profiles and activity stats; and Resolve tracks conversations, replies, and response times.

Jawbone UP Enables Ecosystem of Fitness Apps with Open API

Jawbone’s four UP trackers helps users hit fitness goals by providing insights related to heart rate, meals, mood, sleep, and physical activity both in its award-winning app, and through an extensive ecosystem of apps that draw data from the platform’s open API.

LinkedIn Premium Tracks Funnel Conversions

LinkedIn’s Premium suite of networking and brand-building tools helps demonstrate the ROI of sponsored campaigns by providing users with visibility into their engagement funnel—from impression, to click, to interaction, to acquired follower.

Medium Provides Publishers with Key Reader Metrics

Though Medium’s model is sometimes murky—publishing platform, publication, or social network?—it provides clear insights to its writers (or is that publishers?) in the form of views, reads, recommends, and referrers for published stories.

Mint Helps Users Budget and Save

Mint encourages users make better finance decisions and save up for big goals by giving them visibility into their spending trends, especially as they relate to personalized budgets.

Pinterest Allows Pinners to Track Engagement

The internet’s favorite mood board, Pinterest provides it 110M monthly active users with traffic and engagement stats including repins, impressions, reach, and clicks.

Pixlee Illuminates Its Unique Value Proposition

Pixlee helps brands build authentic marketing by making it easy to discover images shared by their customers, and then deploy them in digital campaigns. To help its clients understand the impact of this unique value proposition, Pixlee serves up an on-brand, real-time dashboard that presents custom metrics like “lightbox engagement” alongside traditional metrics like pageviews and conversions.

Shopkeep Improves Business Decision Making

Shopkeep’s all-in-one point-of-sale platform uses a wide range of data—from best-selling items to top-performing staff—to helps businesses make fact-based decisions that improve their bottom line.

Slack Delivers Visibility Into Internal Communications

The messaging app of choice for more than 60,000 teams—including 77 of the Fortune 100 companies — Slack delivers stats related to message frequency, type, and amount, plus storage and integrations.

Spotify Shares Stats as Stunning Visuals

Spotify’s stream-anywhere music service turns data insights into beautiful, bold visuals, informing their listeners of how many hours of songs they listened to in a year and ranking most-listened-to artists. They also help artists get the most from the platform by highlighting listeners by location and discovery sources.

Fan insights by Spotify

Square Zeros In On Peak Hours and Favorite Items

Going beyond credit card payments to comprehensive business solutions, Square provides business owners with real-time reports that include hourly sales by location, which help them hone in on peak hours and preferred products.

Strava Turns Everyday Activities Into Global Competitions

Strava turns everyday activities into athletic challenges by comparing its users’ performance stats against the community’s for a given walk, run, or ride. The app also used its 136B data points to create the Strava Insights microsite, providing insight into cycling trends in its 12 cities across the globe.

Swarm Updates the Foursquare Experience with New Gamified Features

Swarm adds additional gamification and social features to the original Foursquare check-in experience, providing users with their popular check-ins broken out by type, as well as friend rankings and leaderboards for nationwide “challenges.”

Triptease Builds Strong Relationships with Hotels

The Triptease smart widget allows hotels to display real-time prices for rooms listed by competing sites like to help convince guests to book directly and help the hotel build richer customer relationships. To keep a strong relationship with their own hotel-users, Triptease shows the impact on revenue of widget-enabled conversions, as well as the hotel’s real-time price rankings compared to other websites.

Twitter Beefs Up Its Business Case

As the internet’s 140-character collective consciousness positions itself more decisively as a boon for businesses, it has beefed up and beautified its analytics dashboard. Twitter’s dashboard now includes impressions, profile visits, mentions, and follower change for the past month, plus cards for Top Tweet, Top Follower, and Top Mention.

Vimeo Provides “Power” Stats in a Straightforward Interface

“We basically wanted to give users a power tool, but didn’t want them to feel like they needed a license to operate it,” explains Vimeo senior product designer Anthony Irwin of the video-hosting platform’s analytics tool. Today, Vimeo’s 100M+ users can dig deep—or stay high-level—on traffic, engagement, and viewer demographics.

Yelp Extrapolates Conversion-Generated Revenue

More than a ratings site for local businesses, Yelp also helps its 2.8M businesses engage and grow relationships with their customers. To highlight this value proposition, the company provides business users with a tally’s of customer leads generated through the platform, as well as a calculation of estimated related revenue.

Zype Helps Users Track Video Revenue

With a single interface, Zype makes it easy to publish and monetize video content across various platforms. Core to its value is the ability to provide users with key stats including monthly earnings, new subscriptions, and successful revenue models.

Building analytics into your product? We can help with that. Check out Native Analytics.

Want to see your stats featured in our next post? Send us a note


We’ll be releasing more guides and examples in the coming months. Subscribe to join hundreds of other product leaders who are following native analytics trends: ->

Alexa Meyer

Growth and UX. Cheese chaser. Aspiring behavioral economist.

Rocking Customer Success from a Segway in Portland

There are many reasons why Customer Success is important to a healthy business - from growth to retention to referrals to product development - but I do it not for those reasons at all…

I do it because I love it!

I was in the middle of a Segway tour in Portland this past weekend and we stopped for drinks (yeah, apparently it’s legal to drink and ride a Segway there), and as soon as I found out that one of the other Segwayers was interested in adding analytics into his company, I started quizzing him about how he was looking to grow his business and talking about what he could do with Keen. I just couldn’t help myself. It’s like a puzzle he and I could work together to solve and then hop back on our Segways feeling refreshed!

The big difference between Customer Success and Customer Support

Before the Customer Success team existed, we had a team dedicated to helping customers, but it was reactive. If a customer wanted help modeling data or had a question on how to create a dashboard, we would help them. And sometimes we got to learn about what they were doing. We prided ourselves on being customer oriented, but it wasn’t really customer success. It was customer support.

Customer success is about preemptively helping a customer before they have even really asked for it. I am a people pleaser by nature, and if I can help a customer before they even know the need it, then I feel great!

I went to a talk the other day about Consciousness Hacking and they talked about how there are studies to measure whether people can tell what image they are going to see before they actually see it. I am still processing the talk, but I love that idea. If I could apply that to knowing what the customer is going to have questions about, and helping them before they even ask, that would be amazing.

Fortunately for me, it’s a little easier to predict customers’ behaviors than determine whether we can really predict which future image we will see. (By the way, Robert Krulwich from Radiolab has an interesting commentary on that subject)

Did Alice know what was behind that curtain?

Understanding customers’ needs before they feel the pain

The customer may not always know the best way to achieve their goals. By getting an overarching understanding of how they want to grow their business, we can figure out how they can get the most value out of Keen.

These conversations help us avoid the potential pain points a customer might have with our product today and also help us understand how our product needs to grow to support them in the future. We can now align our product roadmap based directly from an understanding of how our customers would like to expand. I love this! I get to help the customer by being their advocate at Keen and I get to help Keen by making sure customers are taking advantage of new features and capabilities we add.

And, I get to hear about really cool projects that people are working on!

One customer,, used the metadata of where they placed different news articles and advertisements on their webpage to provide information to their editorial staff which could then optimize how many articles a user was likely to read.

Another customer, Net-a-Porter, was able to use Keen to monitor web performance, which they displayed in their common room to alert them when the network went down.

Another customer,, built their own desktop analytics right on top of Keen] and used that to provide information to their clients about user engagement with their own application.

And I even learned about a customer, Whitesmith, that used us to measure happiness in their workplace. How cool is that?

Customer Success is a win for everyone

I feel like Keen has really stepped up the growth phase ever since we started the Customer Success team. We have become proactive instead of only reactive. We have gotten a much better understanding of our customers’ growth plans and how to provide direct value as they scale. Most importantly, we turned on the faucet to enable a constant stream of communication between the customer and our product team. Now we are aligning our growth to the growth of our customers.

And I get to be in the middle of all that, helping customers even before they are our customers, just riding around on a Segway.

If you’d like to talk more about Customer Success or building analytics with Keen or Segway safety tips, I’d love to chat! Feel free to drop me a line at

Maria Dumanis

Good news everyone!

Focus on Allies - Learning Ally Skills at Keen IO

Photo by #WOCinTech Chat

At Keen IO, we value introspection, continuous learning, honesty and empathy. In the spirit of those values, we are eager to learn how we can leverage our individual and collective privilege to work towards a more tolerant and inclusive world. As such, we teamed up with Trello to host a leading expert in diversity and inclusion, Valerie Aurora, to share how we can all become better allies.

Most diversity and inclusion initiatives focus on changing the behavior of targets of oppression, rather than allies. This talk helped to explain why we should focus on changing the behavior of allies instead. It described about a dozen specific ally skills and talk about effective ways to develop your own ally skills, including attending the Ally Skills Workshop

At a glance, here are the 13 skills Valerie explored in her talk:

  1. An ally self-educates
  2. An ally listens
  3. An ally gives credit
  4. An ally asks for consent from the target, if they’re doing something that might possibly harm them.
  5. An ally keeps the focus on helping targets.
  6. An ally speaks up and draws fire.
  7. An ally uses their energy wisely.
  8. An ally spends money. 
  9. An ally uses their social capital.
  10. An ally acts even when it’s uncomfortable.
  11. Sometimes an ally sacrifices personal gain. 
  12. An ally follows leaders from marginalized groups. 
  13. An ally makes mistakes and apologizes.

We’re happy to share the recording and transcript with you.

We’re hopeful the skills Valerie covered will help to inspire our community members to use their specific constellation of privilege to identify opportunities to support, protect and amplify the voices of targets of oppression. We’ve already had several conversations internally about how we can do that, and have been thrilled to hear event attendees have been having similar conversations at their companies.

Valerie’s slides can be accessed here.



I’m here tonight to talk about Focusing on Allies, which is what I think we should do for diversity and inclusion in technology in 2016. I’ve already got a bit of an introduction, so I’ll just quickly go through the stuff that Sarah-Jane didn’t mention. I am the founder of Frameshift Consulting, which is a consultancy for diversity and inclusion in technology. That will shock you. I actually was also the lead author of that code of conduct that they just read to you. It was fantastic to hear the code of conduct implemented well with the reporting information, thank you. I also, prior to doing this work, I spent a number of years, over ten years, as a volunteer doing work for women in open source in particular. I’ve taught the Ally Skills workshop and given this talk around the world, including a number of places in Europe as well as Mexico, Australia, and our neighbors to the north.

I just have been having a bit of branding confusion so I now have a slide explaining the difference between this talk and the Ally Skills Workshop. This is about a 30 minute long talk with hopefully 20 minutes of Q&A (please!), explaining why we should teach people Ally Skills and going over some Ally Skills. The workshop is actually a three-hour workshop where you spend most of it speaking to each other and discussing real world scenarios. You can find out more about it at this link, and all of these slides and a number of other resources are available on my website as well, the Frameshift website. About the questions again, I love questions, questions are my favorite part; I hate just talking, the thing I’ve already said a million times. Writing them down on index cards gives us much higher quality questions. I’m really looking forward to that. Alright, so let’s go into some terminology.

We’re talking about Ally Skills; what is an Ally? The first thing we need to do is define a few other terms. The term privilege means an unearned advantage that’s given by society to some people but not all, so emphasis on the unearned. Oppression - systemic, pervasive inequality that is present throughout society, that benefits people with more privilege in harms those with fewer privileges. I’ll get into an example in a moment. A target is someone who suffers from oppression, also called a member of a marginalized group. Now we can define Ally. An Ally is a member of a social group that enjoys some privilege, that is taking to actions. They’re working to end oppression and to understand their own privilege. The thing about being an Ally is that that’s not an identity, it’s not a thing that you are, it’s about the actions that you take.

We’ll do an example. Here’s a privilege you may have and not be aware that you have. This is the ability to walk into a convenience store and have the owner assume you are there to buy things and not to steal them. Oppression in this case is the self-reinforcing system of stories, TV, news coverage, and the entire legal system, hooray, that stereotypes black people as criminals, that benefits non-Black people and harms black people. It’s important to remember this is benefiting someone, that’s why it exists. The target in this case is any black person who wants to enter a convenience store. It could be a nontrivial number of people. An Ally in this situation is a non-Black person who does things like donate to legal system reform organisations, actively objects when people tell racist stories or make racist comments in their presence, votes in and anti-racist ways, and reads news articles about this privilege. Those are some of the ways that you could act as an Ally in this situation. I like to hold most questions to the end but if something’s not clear, I’m happy to answer the question during the talk.

I want to talk more about what diversity and inclusion mean. A lot of people will use these words and not be quite short what they mean by them. Diversity is the state of having people in a group who differ along the lines of race, gender, sexuality, age, disability, religion, class, or caregiver status. That includes things like being a mother, or caring for your parents, things like that. Inclusion is when you have a diverse group, run in that group is valued, included and respected without unfair discrimination or bias. That’s why we say both diversity and inclusion. It doesn’t help if you have a diverse group but you’re not treating people equally and fairly within that group. Here’s a couple of common misunderstandings. An individual can’t be diverse, so please don’t say diverse hire. Diversity exists in the context of a group. One of these yellow balls with a smiley face increases the diversity if it’s added to this group of balls, but it’s not having any effect on diversity in this group. Many efforts in this area focus on increasing diversity and don’t follow through on inclusion.

Alright, so here’s some examples of diversity and inclusion efforts: volunteer-run affinity groups for people to support each other within particular groups; travel scholarships from members of marginalized groups; coding boot camps; advice books aimed at targets; volunteer-run mentoring programs; recruiting outreach to places like historically that colleges and universities; conferences for marginalized groups… this is a photo from AdaCamp which is one of the conferences I have drawn for women in open technology and culture. What’s wrong with diversity and inclusion today? I think that the problem is that most work is aimed at changing the behavior of targets of oppression. Less work is aimed at changing the behavior of allies. Let’s talk about some of the reasons why we do this in the first place.

Some of the reasons we focus on changing behavior targets are targets directly benefit from change and tend to be more self-motivated. It’s easy to get someone to take action if it’s going to personally benefit them than if it’s going to take away one of their privileges. Targets are often but not always more aware of oppression. One of the ways you can cope with being a member of a marginalized group is to be unaware of it for whatever reason. That worked for me until about age 21. Usually you get to skip the part where you raise awareness if you’re trying to convince targets to change their behavior. Targets are often lower status and easier to tell what to do. It is much easier to tell your intern that they need to speak up more often in meetings than it is to tell your CEO to stop interrupting the intern. It’s just an easier thing to do.

Targets are often seen as the cause of the problem. You’ll see this when people propose solutions to sexual harassment in the workplace or the military, by saying, why do we remove women from the workplace or the military? This ignores the fact that the majority of sexual harassment is committed by men, but people don’t suggest removing men from the workplace because they’re not seen as the cause of the problem. Finally, really focus on targets and telling targets had to change the behavior, it helps you avoid confronting the feelings of guilt that you might have from any part of your privilege. If the target is at fault because they’re not behaving properly, then there’s nothing that you have to acknowledge about your own advantages that  weren’t earned.

Let’s talk about what’s wrong with focusing on targets. In the first place targets tend to be overworked. You may have heard the old phrase, “Ginger Rogers did everything Fred Astaire did, but backwards and in high heels.” I finally found a fair use photo of them. This is maybe not technically true but it’s a very popular thing because it really accurately reflects the feelings of many people who are targets, that they’re working twice as hard to get half as much credit. The truth is is that that’s actually what is happening. One aspect of this is discussed in the book “What Works for Women at Work”? This is the only book of advice will targets that I recommend for two reasons; the first one is that it really presents sexism in the workplace as structural oppression… it says, you’re not going to solve it as a woman by acting in these ways, but you can make life a little bit easier for yourself.

The other thing I like about it is that more than half of the women that they interviewed for this book were women of color, and that they went into details about what the different experiences were and coping strategies for women of different races and ethnicities. In a way that was very detailed and granular. It’s a great book, I highly recommend it, but yeah, it just talks about in particular the prove-it-again bias. This is a pattern that they see, which is where, the way that our brains work is that it’s easier for us to forget things that go against our stereotypes, and it’s easier to remember things that confirm our stereotypes. If you had two co-workers, one of them is stereotyped in your head as the perfect manager and the other one is stereotyped as, you can’t be a manager at all. You’re going to remember all of the good management decisions that the person who fits the stereotype did. It’s going to take you forever to remember all of the examples of the person who doesn’t fit your stereotype. Prove it again, you have to do it over and over again.

Targets are under more stress. Stereotype threat is the fear of confirming negative stereotypes about a group that you are part of. This causes a measurable overhead when you’re working and when you’re thinking that affects your performance. You have to work harder because at the same time you have a voice in your head saying, don’t do it, don’t do it, don’t screw it up. Discrimination is a very miserable experience to be treated unfairly, and to know it. It as a lot to your stress. Harassment, abuse and assault, happen way more often than rethinking the workplace and elsewhere. People often don’t speak about it, because they don’t want to be retaliated against, but this stuff is all happening and it would obviously cause you a lot of stress and overhead. Post-traumatic stress disorder is the result of living through this level of stress for years upon years. Targets are under more stress in general.

Targets have less money. This is very small font. Each of these numbers varies each year. These are mostly 2015 numbers but there’s a few from 2013, so don’t get too worried, but you should get the general idea. Asian women and paid 87% of what white men are paid, and these are all US numbers obviously. Lesbian couples are paid 79% of what men married to women are paid, the individual in that couple. White women are paid 70% of what white men are paid. Black men 73% versus white men. Mothers 73% versus fathers, and fathers often get a small raise after becoming fathers. Trans women, 66% of their pre-transition income. Black women, 65% versus white men again. People with disabilities, 63% versus those without. Latinos, 58% versus white men. There’s more stats obviously but I think you get the message.

You’re also more likely to have unpaid caregiver responsibilities if you’re a member of a marginalized group. Targets are more likely to suffer retaliation. I mentioned this briefly before. There’s actual studies done on this. I’ll just with a quote from the study here. “Ethnic minority of female leaders who engage in diversity-valuing behavior are penalized with worse performance ratings; whereas ethnic majority or male leaders who engage in diversity-valuing behavior are not penalized for doing so.” You can probably think of some experience in your own life where someone who was male or ethnic majority did something related to diversity and got a benefit from, but this really showed that yes, it depends on who’s doing it and whether you’re seen as advocating for a group that you’re part of, or a group that you’re not part of, and the status that you’re part of.

Targets are often but not always in the minority. Here’s two communities I’ve been part of: this one on the left here is for open source software, the only study we have of gender distribution is from 2006. It’s a very small slice men make up 98.5% of the community, women make up 1.5%. I’m an operating systems developer and one of the things we learn is when you’re optimizing a program, you aim for the part that takes up most time. You work on that part first. You do not work on the 1.5% first. It was very clear to me that we couldn’t make any progress if we only tried to change the behavior of women in this community. By the way, I disagree with the categories they used to survey gender in these two studies. If you’d like advice on that I’d be happy to give it offline. Gender of Wikipedia editors came out as 90% men. It’s very clear that you can be more effective if you’re working on the people who are in the majority as well.

Targets have less power and influence. Fewer than 5% of Fortune 500 CEOs are women, fewer than 5% of Fortune 500 CEOs are people of color. Ursula Burns is two of those people, for the purposes of statistics, so when she steps down this is going to drop significantly, I think 20%. The Smurfette Principle was coined by a TV writer named Katha Pollitt. She pointed out that there are a lot of TV shows that had an all-male ensemble cast with the exception of one female character. The message here is that being a woman is strange, and it’s unusual, and it’s rare, when actually it’s one of the two most popular options. Of course, after Smurfette the village of male smurfs with only one female smurf.

This works out in the leadership teams of companies as well. Leadership team is the Board of Directors and the C suite, CFOs, CEO, COO, things like that. Here’s a study that looked at the SMP 1500, and here’s what they found. The probability that a woman occupies a top management team position is 51% lower if another woman holds a position on the same team. The Smurfette Principle lives and tokenism is real. The important thing to remember here is not just that you need to educate your top management team and get them to be making better decisions, but that if you ever see members of the same marginalized group who seem strangely competitive with each other, or even members of different marginalized groups, it’s not because they are terrible people who are competitive. It’s because they are working in a system in which only one of them can win, if they’re both aiming for a promotion higher up.

Finally, targets are seen as whiny, complaining and jealous when they advocate for themselves. I took this one from my personal experience. When I published the example conference code of conduct on the Geek Feminism blog, someone wrote this comment. There’s a little bit of mild profanity and vulgarness, I’m sorry: “Do you actually code anything or contribute to the open source software/hardware community in any tangible way or do you just bitch and moan about having a period and write conference conduct policies?” This was my favorite part. “It is a legitimate inquiry.” My friends had a lot of fun explaining to this person my ten year history of leadership in file systems and development of operating systems. That was enjoyable for them, but it just goes to show that you cannot get to a place where you are successful enough that you are not open to this criticism as a member of a group advocating for your own group.

Those are all the reasons why allies should take action more than targets, and yet when we look at groups and books that are aimed at improving diversity and inclusion in technology, you’ll see they’re still all aimed at targets. I’m not criticizing any of these groups except for the book, I don’t like the book, but these groups are doing great work. Black Girls Code aimed at black girls, Callback Women aimed at women speakers, Natives Who Code, Lesbians Who Tech, TransH4CK, The Pregnant Scholar, Code2040 is for (Black) and Hispanic Latina and Latino coders, and Mother Coders. Those are all explanatory. Lean In of course is the book that says, hey, if women just worked twice as hard, magically sexism will go away. Here’s the complete list of books, nonprofits and organizations for allies in technology that I could find, and yes, it’s blank on purpose.

This is my proposal: that 2016 is the year that we focus on allies and changing the behavior of allies, and whoah, we’re already three quarters of the way through. I wasn’t thinking when I put the year in this. I just want to summarize why we should focus on allies, and then I will talk about ally skills. Allies have more time and energy. Allies have more money. Allies aren’t harmed for diversity valuing behavior. Allies are often in the majority. Allies have more power and influence. They are seen as altruistic, giving and kind when they’re speaking up for members of groups they aren’t part of. What do ally skills look like?

1) An ally self educates. Often people will learn a little bit about a new word or something they don’t understand, and then insist that someone who’s a member of a marginalized group explain it to them, like suddenly they forgot how to Google.

This is a really important, crucial first step to take in your work as an ally, is to really accept the responsibility for teaching yourself, and going out there and making the best effort to learn what you need to learn. If you’ve exhausted the online resources, watched the videos, read the blog posts and you still don’t have an answer to your question, that’s a pretty good question. You can feel free to ask someone that one, but it’s really important to take responsibility for educating yourself in the first place, as the default.

2) An ally listens. I had a hard time deciding whether to put self-education or listening first. They’re parts of the same coin, but yes, a really important thing is as someone who has more privilege, you’re used to talking and other people listening to you. That’s an easy pattern to fall into. Pay attention next time you go to dinner with your friends. There might be a pattern that you see.

An important part of being a good ally is listening to members of marginalized groups and believing what they say, and taking it seriously. Here’s a great example that happened at the 2014 Grace Hopper celebration. They had a panel of all men, about male allies, in front of an audience of about 7,000 women. Multiple people warned them that this might go badly. It went badly and there were multiple press releases and PR disasters, and a cleanup that they needed to do, as well as the people in the audience having a miserable time. One of the people who was on that panel is Alan Eustace, who was at that time a senior vice president at Google. He used his Twitter account to send this one Tweet, “Let’s reverse the male allies panel. You talk, I listen.” Then he gives the room information. He and two of the other panel members spent an hour in this room sitting and listening, while women came to the mic and said what they experienced at work and how the words they had said on stage had hurt them. That was a great example of an ally listening.

3) An ally gives credit. Again, as someone with more privilege, people will assume that you did the thing that you’re talking about. This has only happened to me a few times when somebody thought I wrote a file system I didn’t write, but that was very sweet. It must be wonderful to happen all the time. As an example, there’s a link down here about this. Women get less credit for co-authoring papers. In fact, it has zero effect on their careers according to a study of economics professors, people with PhDs. That’s just one example of how that happens. Here’s another example of how to give credit. In social justice circles there’s a norm that whenever you use the word intersectionality, that you credit the inventor of that term by name, Kimberlé Crenshaw. Briefly, the term intersectionality describes the concept that people can be subject to multiple overlapping forms of oppression that intersect and interact with each other in different ways.

Kimberlé Crenshaw is herself a black woman, so she gets a form of oppression based on being black, she gets a form of oppression based on being a woman, and she gets a whole special form of oppression based on being a black woman together, but it’s really important to give credit frequently and copiously and whenever you’re not sure. The one exception to this is if giving credit will put someone in a position where they might be attacked. If you’re not sure about that, ask whether or not somebody wants credit in that situation.

4) An ally asks for consent from the target, if they’re doing something that might possibly harm them. We all understand that the fight for improving equality and bringing rights to people often involves harmed individual people who are members of that group. Think of anything, really. The important thing is that if you as an ally are taking an action that’s going to put someone in that position, you have to ask them first. An example of this situation is the fight for marriage equality here in the United States. That involved individual same-sex couples going to court and having their personal lives examined with a fine tooth comb and being a symbol and an example and being harassed by people. The important thing is that they volunteered to do that. If you as a straight person walked out there, picked a couple and said, you’re going to be the people that we’re fighting for in this court case, that would not be asking for consent.

5) An ally keeps the focus on helping targets. A common problem is called derailing. If somebody’s trying to talk about the problems facing targets, that other people will try to recenter the discussion on the feelings of people with more privilege. Here’s an example of someone pushing back on that, from Twitter. Jenn Schiffer is an excellent programmer, artist and humorist. You should check out her blog if you have a chance. She says on Twitter, “A shoutout to my girls out there who want to be visible in the tech community but also want a family, but have to choose because Earth is terrible.” Some rando replies and says, “Well, it’s a problem for fathers too. Balancing networking and family isn’t easy for anyone. Then Moishe joins in and says, "As a dad,” so invoking his privilege, he says “I’m going to go ahead and say it’s objectively harder for moms.” He’s getting the discussion right back on track from where it started, so yeah, keeping the focus on helping targets avoiding derailing.

6) An ally speaks up and draws fire. The converse of this is that when being the focus of the discussion is bad, it’s going to get people attacking you, that’s the time to speak up and draw fire as an ally. I got another example of that here, again from Twitter. It’s my friend who goes by @hashoctothorpe. She says, and she’s a straight white cis woman, “In one joke, (elided) and (elited) managed racism, misogyny and transmisogyny. Total (elided) weasel territory,” and also says “The talk from (blank) and (blank) was offensive in every way and violated the code of conduct, please expel them.” There’s a great resolution to this story, the conference did expel these two folks for the remainder of the conference. They both apologized on Twitter and they came back the following year and were not making offensive jokes anymore. This is a great example of when it’s okay to be the center of attention when you’re acting as an ally, because obviously my friend risked being the center of a trollstorm by taking this action.

7) An ally uses their energy wisely. Some of you may have seen this. This is Anita Sarkeesian, who did the tropes about Women in Video Games series for Feminist Frequency. One of her critics said, “My biggest problem with Anita is that if I used her logic, I could see sexism everywhere.” Yes… so close. (laughter) Seriously though, you can’t go to the grocery store without some form of oppression. It’s around you all of the time. It’s systemic, it’s pervasive. What’s important is to be able to see, hey, where do I have the most power and influence? Where can I use my energy in a way that’s going to have the biggest impact? Do I just need to take action, even though it doesn’t make sense, because it’s important to my values? You don’t have to address everything you see, but really you’re starting to pay attention, and say hey, when can I take an action and make a big effect. That’s a great thing to keep in mind.

7a) Charles’ Rules of Argument: This is one of the things I teach in the Ally Skills Workshop, Charles’ Rules of Argument. This is Charles Miller. He had a blog on the internet in 2004. He currently works for Wikia just up the street. He spent a lot of time arguing on the internet, and then decided that was not how he wanted to spend his time, so he made Charles’ Rules of Argument. Rules are, the first one is, don’t go looking for an argument. Somebody’s wrong on your part of the internet that you normally read. Trust me, it’s true. If you do choose to have an argument, state your position once speaking to the audience. This is important because you’re unlikely to change the mind of the rando or the troll or whatever it is that you’re addressing, but the people who are watching haven’t made up their minds, and they want to emulate the person who seems to be the most admirable.

Wait for absurd replies is the next step. On a mailing list this will take two or three days, on Twitter it will take two or three minutes. Once you get a few absurd replies accusing you of saying things you didn’t say, you reply one time to correct any misunderstandings of that first statement. This is the most important part, do not reply again. Spend time doing something you enjoy like going outside or drinking a beer or petting a dog. It’s very important.

8) An ally spends money. An ally has more money. A great thing to do with it is give it to support groups that are fighting to end oppression. If you’re not sure which groups to give it to, this is one time that you’re allowed to ask a member of a marginalized group, “Hey, where should I put my money?” and expect some good suggestions.

As a former executive director of a nonprofit and the fundraising lead, I would like to say please don’t offer to donate your time unless it’s an organization that’s set up specifically to do that, like Black Girls Code has a very efficient system for doing that. If you’re not sure why one or two hours of your time, of your expertise and web design is not helpful, imagine you walked into work tomorrow and somebody said that you have 500 interns, and each have one hour available. Just give people money.

9) An ally uses their social capital. One of the things you can do is give people money, and then tell other people that you gave money. This is not to make you look good, this is to set an example for other people - “I believe in this cause enough and I believe in this group’s effectiveness well enough that I gave them x dollars.” That is a wonderful thing to do, please do it. You can also use your social capital to help people get talks, to make introductions to people who are useful to someone’s career, not just people who are like them in the way that they are marginalized, and to amplify other people’s voices, amplify the voices of targets. One of the things I try to do is I relatively rarely tweet myself, I usually retweet somebody who has a lot of knowledge about a particular subject.

10) An ally acts even when it’s uncomfortable. Poor dog, I always feel sad when I get to this slide. It may be really uncomfortable for you to speak up if your coworkers are using the words “crazy” or “lame” in conversation, because most people don’t know that that’s not okay and it just feels so extreme, but it really helps to remember, hey, if you feel uncomfortable, how does the person who has undisclosed mental illness feel? Or the person who uses a wheelchair, When you’re talking about your product being lame? Being aware that whatever you’re feeling is probably an order of magnitude less will really help you act in a lot of these situations.

11) Sometimes an ally sacrifices personal gain. That’s how privilege works. You don’t have to sign up for it. You don’t have to say, I accept this unearned advantage that you are giving to me. People just hand it to you constantly all of the time, and sometimes you have to turn around and say, no, I don’t accept that. An example of this happening is you may have seen a panel at a tech conference that looks like this before (picture of tech panel with 5 white men). You may be invited to a panel in which you round out a panel that’s all white or all men or something like that. That’s a great time especially if you are already fairly far along in your career, to say,” hey, I no longer serve on panels that are all white, or, I no longer serve on panels that are all men. Here’s my list of suggestions of people to replace me with that are more qualified than I am.” This is obviously better to do once you have more influence and power in the first place, but you can do it at any point.

12) An ally follows leaders from marginalized groups. Again, as someone with privilege you’re used to people following you and doing what you say. The thing is that if you’re trying to support the marginalized group and you’re not part of it, you often don’t know what they need or what would help them. People who are a member of that group do know that and you can instead support them, give them your money, amplify their voices, encourage other people to follow them. There’s a phrase from disability activism; “Nothing about us without us”. There’s a great Wikipedia page on that you’d like to check it out more. That’s a good thing to remember.

13) An ally makes mistakes and apologizes. If you never make a mistake, you’re not doing anything risky or worthwhile.  It’s also impossible not to make a mistake. What’s important as an ally is not that you are perfect and you never make a mistake; what’s important is that when you make mistakes, you immediately apologize, correct yourself, make amends if necessary, and then move on. It’s not about you, it’s not about your mistakes, it’s not about feelings about your mistakes. It’s about trying to support this group, this is the best way that you can do it. It’s also a good way to set an example for other people were wondering how to behave, if you can graciously admit your mistake, apologize, correct yourself, move on.

We are almost to the end. That’s just a very high level hand-wavey summary of I think thirteen ally skills, and it’s going to take a little bit more than that to learn them and just to use them. You can learn ally skills but it’s actually sort of difficult right now. Most of the information is spread out, you noticed the number of links to research papers I had in these slides. I’ve collected those over multiple years. There’s not a good set of books right now. There are books that will cover one aspect of being an ally but have maybe a chapter on ally skills, but there’s not a theory of being an ally out there yet.

I’m working on a book about ally skills, you can follow my twitter account @frameshiftllc for more news on that. In the meantime, I and many other people teach an ally skills workshop. It’s interesting that the San Francisco Bay Area has the largest number of people teaching these kind of workshops. We might be the area of the world that needs it least, but that’s how it is. That’s why I’m working on the book.

The ally skills workshop I teach, the materials are all freely usable under the Creative Commons share alike by attribution licence, and there are many ally skills workshops that are derived from the same set of materials you can get from other people as well. There’s a “train-the-trainers” also available. I think I’ve taught about fifty people to do it and there’s a number of people who are self-taught as well. All the materials for that are freely available. Currently this workshop is being taught internally by internal trainers at Google, Square, Slack, and Spotify, and I have some other companies that will hopefully be joining them soon. You can go to my website and find out more about that.

Conclusion, this is what I’d like you to take away from this talk. Most diversity and inclusion efforts focus on targets. Targets have less time, energy, power and influence. Allies have more ability to make change, and ally skills can be learned. Let’s focus on allies for 2016. All right, thank you so much.


I would love to do questions at this point. If you haven’t written your question on an index card, please do and pass it up front. Are there any coming up to the front? Great. I can also answer questions that people ask with voice. I wrote a blog post about how to have better questions - you know,  the “this is more of a comment than a question.” If somebody has to write it down on an index card, you can just skip that one!

Wow, this is big picture…

What is your ideal vision of an ally organisation?

Yeah, so the interesting thing about …This is tough, people have always asked me, hey can you start a mailing list or Slack community or something like that for people who want to act as allies? It’s never felt right and I think it’s because there hasn’t been a focus yet on specific ally skills that can be written down. If you’re a member of a group that’s a marginalized group, you have a shared identity. That’s an identity, you have shared experiences. Being an ally is about actions, and there’s not …It’s not the same sort of way that you have this shared experience and this need for the same support group. An ideal vision of an ally organisation I think would be something that’s really focused on supporting people who are doing this kind of work, who are members of marginalized groups. A fantastic form of an ally skills organisation would be a giving club. This is a group of people who get together and share information about what organisations they want to donate to with a focus on diversity and inclusion in technology. That’s an extremely powerful thing to do. You can bring together ten people and perhaps you had a bonus this year for $5000, that’s $50,000 that you can agree on and share your information about how to use. I really think ally organisations would be focused around those specific ally skills in supporting each other, but it would have to have that goal rather than, I’m an ally, you’re an ally, yay, let’s ally together.

Oh wow, good set of questions…

Can you please get Linus (I assume Linus Torvalds) to attend one of your workshops?

No. It doesn’t work that way, I wish it did. That was a hilarious question, thank you whoever wrote it, but that actually is part of a class of questions I often get asked which is, how do I convince people to want to be allies? The answer is you can’t. If you could convince someone to want to be an ally, they could conversely convince you to not want to be an ally. I can tell you how I’ve seen people make this decision, and it is often someone very close to them has a miserable experience. Someone they’re married to gets fired for one of their kids gets attacked or something like that. That can often be an experience that make someone go, “whoa, I just opened my eyes.” A slightly different version of that is if multiple people who are somewhat close to several of your co-workers all tell you about a similar experience they’ve had, and that completely changes your view of the world because you didn’t know that was happening… that’s another way that I see people wanting to be allies. Another way I see it is people who care about studies in science and things like that. There’s just this point where they’re like, “I’ve read the fiftieth study saying the same thing about bias and discrimination. I think it’s true!” It’s often really somebody who has a value, a value of being fair. Most people have a value of being fair and inclusive, and then their eyes are open to the reality that that’s not true. That usually helps people in my experience, become allies. If you don’t have that value in the first place, meh. Linus is pretty clear about what his values are.

Amplifying voices; should we ask for consent?

This is a great question. Sometimes amplifying someone’s voice will help them, sometimes it will harm them. If you’re not sure, if there’s a question in your mind, yes, you should ask for consent. This is a thing I normally do, I’m part of a private discussion group and we have the system of, someone says something really funny that we want to share publicly. It’s, “may I share that and do you want credit for not?” We never assume either of those two things. Once you normalize it, it just becomes part of the usual.

Wow, so many questions, this is great.

How can allies work against unconscious bias?

Yeah, becoming aware of it and setting up structures and checks. Often, one of the great examples I like is that I hear that at Google promotion meetings, where they decide who gets promoted, the beginning of the meeting they read a prepared statement that says, “hey, here’s what unconscious bias is. This is what it looks like. If you think you see it in this meeting, here are the words to say.” That’s a fantastic way of creating a structure to go back against this. Oppression is part of …It’s a systemic structure. It’s got lots of form and ritual around it, so creating new structures is part of how you do that.

Yeah, so this is asking about when do you want separate groups where it’s allies and targets and when you want to be in the same group and giving examples like, white women versus groups of black women and sometimes working across purposes. Oh yes, and that often it seems patronizing, when people are telling people what to do.

Yeah, that’s why I emphasize so much on the ally skills, starting with listening, self educating, and then following and supporting. I believe that this is something that has become clear of the last ten years of doing this sort of work, is that I believe you do need separate groups for members of a marginalized group to support each other, then you need an integrated group of people who are both allies and targets for doing work to change the system. The reason is that it’s just, you need support groups where you can say things without being questioned, when you don’t need to educate people. A group where you can just say, “hey, blah-de-blah happened at work today,” people will just be like, “oh yeah, that really sucks when that happens,” instead of being like, “that doesn’t happen. Could you explain to me why that bad?” All that sort of thing. I really encourage people to have both of those things at work, at school, and in all sorts of things. To be very clear, when you have an event, whether this is a thing for members of the group only, or for members of the group and allies. If you leave it unsaid people will usually assume that the good people, the actual allies, will assume it’s for members of the marginalized group only. The annoying people who want to tell you what to do will assume that they’re welcome and show up. I have this happen a lot with Women in Linux events. (from audience) So an example is the East Bay Meditation Center which has events for specific groups and then they have events for teaching people about inclusivity.

Sometimes a co-worker say something disrespectful and I’m not sure whether to say something to them. What if the result is that they just stop saying those things round me or if I end up blacklisted as a result?

Yes, so first of all if you are in danger for speaking up, you should maybe rethink whether you are an ally in that situation. You may be a target, if speaking up is going to get you in trouble. You may not have the advantage and the privilege and the power and influence that you need in that situation, and it’s fine not to speak up in that case. The concern about people just going underground and just not doing it in front of you…? Sometimes the only thing you can accomplish is to say,”hey, this is not socially acceptable in this situation.” You can’t control what someone’s doing away from you. You can just make clear that it’s not welcome and that it will have consequences if it’s around you. I view that as a win. You’re setting a standard and there’s a lot of other people who are going to see what’s happened and act differently.

Ah, self-education. What’s a good website or Google search to start at?

The way that I like to recommend people with self-education is, you find a starting point and you fan out from there. I’ll give you a specific concrete starting point. I use Twitter a lot. I will follow someone on Twitter, I will pay attention to what they’re saying in their own Tweets, but I’ll also pay attention to who else they are amplifying, who else they are retweeting, and then I will follow them. Often using that you can find your way to extremely knowledgeable people who are sharing for they know for free. You can do the same thing with blogs or Tumblr or mailing lists and things like that. The thing I usually suggest is to start with the Ally Skills Workshop handout on my website, which has a number of different websites and wikis and things like that. Wikis are another good place where you can fan out and begin to learn things, but mainly, find people who are knowledgeable on the subject you’re interested in and who write things in some form that’s distributed on the Internet, and start there.

Let’s see what else. Are consultants the best way for an aspirationally diverse and inclusive company to make concrete progress? If so, can you recommend any?

Yeah, so this is diversity and inclusion, I like for people to think about it like any other aspect of doing business. What would you do if you needed to improve the security of your project? What would you do if you need to improve your HR practices? What would you do if you need it to do more stress testing then you could do with the computers you have in your office? Often you, as you’re growing, you have to outsource these to consultants at various levels and eventually you can bring them in-house once you’re large enough. I don’t think Google is renting botnets to stress test anything at this point, and they are also doing all their internal diversity and inclusion stuff.

A place to start for consultants is, I would say beginning looking at Project Include’s resources to get an idea of what’s the structure, what are you missing, what other things you might do? Personally I often recommend The Ready Set, which is ostensibly a recruiting assistant organisation, but they also do diversity and inclusion training. That’s run by Y-Vonne Hutchinson. Another one I really like is Paradigm IQ, founded by Joelle Emerson and a number of other women, and it’s like they’ve got so many partners now I can’t say all their names. Another good one, shoot …Look to see where Caroline Simard is working right now. I don’t remember the exact name right now.

Those are some good places to start. I do some consulting but I’m fairly specialised. I usually do ally skills workshops or ally skills related things, and I do code of conduct consulting, but I can definitely direct you to other folks. Oh, textio is another good resource. As a company that does large-scale analysis of text corpus to look for bias in language. That can include things like your job descriptions or your performance reports. Again, talk to people who are experts in that area and ask them for advice.

Alright, so this is a tough question but I’ll read it anyway. How do we incorporate cultural competencies in the education of an organisation around diversity and inclusion?

I think what this is saying is how do you use what a company is already good at in terms of its culture and the way works, and use that as a tool to make diversity and inclusion more effective, whatever work you’re doing there. Yeah, I think it’s helpful to have people who have experience in the field that your company is in, be the people that you’re working with as consultants or getting advice. So, really matching up the style of training and information with the cultural biases of your group. One of the things I did with the Ally Skills Workshop is my target audience tended to be introverted, tended to be not interested in standing up in front of other people, tended to be easily bored. It took a while to develop a workshop that worked for that group of people. If I was doing a workshop for a group that was not mostly software engineers like say, people who were sales engineers, that would be a very different format of the workshop, because they would be very excited about speaking in front of other people. That’s what I would look to say in that case.

How do you be an ally to someone who is a target who reports to you? (Given that there’s this other power dynamic which is that you are their manager and they report to you.)

First, kudos for understanding that there is a power dynamic. That’s not a popular thing to talk about or admit in Silicon Valley, that these things exist. Being aware of that power dynamic and being aware that it will cause things like, this person’s less likely to tell you what’s actually going on, they’re less likely to complain to you, they’re less likely to share with you about things, so being aware that you’re limited as a manager in that way. However, then you also have power and influence that’s greater, because you are manager, so if someone does come to you with a problem, you can then go talk to their manager. It’s actually your job to resolve people issues and that sort of thing. I would just say be aware of both the disadvantage and the advantage that that gives you. This is an example of choosing your battles and figuring out where you have the most power and influence.

We have three more minutes, are there any more cards?

Every conversation about diversity and inclusion at work ends up with me trying to educate people. How many *expletive* links do we need to send?

Yes, I know. This is an interesting dynamic. I started to do this, whether or not it’s intentional as an actual strategy to exhaust people who are trying to change the world, who are trying to make the world a better place. It may come unconsciously from this entitlement, this being used to being able to ask for other people to do work for you. Being used to just getting what you want, being used to having people being afraid of you and all that kind of stuff, but I think also people do do it intentionally at some level or another. One of the things I have learned to do is to figure out whether someone is truly open to changing their mind, and is willing to do the work, or if they just want to argue with me, or if they just want to have some excuse to say no and not do a thing. One of the ways I would do that is upfront, I will ask, “hey, why don’t you do this Google search?” If they don’t do that Google search I know that they’re not open to actually learning and I’m wasting my time on them. Setting up a series of small tests to use to figure out whether to spend your time on people. A thing that totally confuses me and just makes me really unhappy is when I see people explaining their block policies on Twitter. You don’t have to justify why you’re blocking someone. I’ve seen people who have come through the other side of that, and have been like, “I don’t explain any more because you know what? None of these people deserve my time. They don’t have any sort of entitlement to it.” I realize that and I realize I don’t have to give them a fair hearing. One of the ways to do this is to compare the amount of time that they spend asking you a question to the amount of time you spend answering the question. A great place to start people, both for feminism and for a number of other things is the intersectional feminism Geek Feminism Wiki. That’s in the slides, or it should be. Oh my gosh, it’s not in the slides, wow. Geek Feminism wiki is a great resource because it has a lot of cross-linked articles about a number of topics. Yeah, really getting that sense of whether someone is open to that level of self-education, and then just not spending your time on those people if they aren’t. I think that’s it. Thank you so much for coming, and does anyone want to say anything before we end? Yes, all right, great.

Sarah-Jane Morris

Community and Awareness

Lesson One

Person Working

As Keen IO’s Chief Data Scientist, I’ve worked with thousands of companies over the years. Today I’m sharing one of the most impactful lessons we’ve learned in building successful analytics integrations.

The lesson is: take some time to reflect on what you are trying achieve. Once you are confident about that, your decisions about what data to collect and how to use it fall more naturally into place.

Here’s a mini-worksheet to get you started:

  1. What’s most important to my company/team right now?
  2. What are our goals?
  3. How can data help us achieve those goals?

Write out your answers. Reflect back on them whenever you feel overburdened by the seemingly infinite possibilities for your data. Re-center and drive forward. You’ve got this.

By the way, we’re pretty helpful people over here at Keen IO. Maybe we’ve already solved a problem like yours and we can help you do it faster.

Michelle Wetzler

Chief Data Scientist

What we learned dogfooding our Native Analytics product

This week, we released Project Analytics – a brand new analytics dashboard displaying service level usage for our customers. This project is the beginning of a new effort aimed at bringing greater insight and observability of Keen IO service usage to our customers. Many of our customers rely on our platform to deliver Native Analytics to their customers, directly in their own products. Now we’re doing exactly that: analytics for your analytics. Pretty meta, huh?

Sample Keen IO project analytics console

This project was super fun for us to build and an opportunity for us to dogfood our recently released Native Analytics product. Read on for some juicy details on how and why we built this and some of the design challenges we faced along the way.

Why did we build Project Analytics for our customers?

First and foremost, our goal with this update is to improve the product experience by bringing more information to the surface of our web console. We have a clear vision for our apps and interfaces that leans heavily on native analytics powered by our own platform. Account usage information has also long been a common customer request that would land on our support and customer success teams. Baking these metrics directly into the product reduces both support ticket volume for this topic and the time spent tracking down this information for each customer.

This was also a chance to dog-food our own Native Analytics product in ways we haven’t had to yet. The insights we’ve taken from this project have already influenced future product development in big ways, for both our API and data visualization capabilities.

What were some of the challenges we faced while building this?

The design phase of this project was pretty intense! We spent a lot of time sketching and iterating – not just what you see now, but what is coming next. This project also coincided with a substantial visual refresh, several big performance improvements behind the scenes, and an active recruiting effort by the engineering team responsible for building this project. Coordinating a successful release around so many moving pieces proved to be a bit challenging.

These obstacles probably won’t sound too surprising or unfamiliar for anyone reading this; that’s just daily life at a growing company. The experience did reaffirm how important Developer Experience is for API-based services like ours. We put a lot of thought and care into how quickly developers can get up and running with our API and SDKs. We know our customers already have a long list of obstacles and blockers to deal with to get a project out the door. Integrating with Keen and getting data flowing in and out of your app shouldn’t be one of them.

How did we decide which metrics to show?

For this first release, we really had to resist the urge to go big, or to over-commit to granularity or complexity. This is just one small piece in a roadmap that that will unfold over time, and we know we have a lot to learn along the way. We give our customers the same advice: start small and move fast; experiment, iterate, and leave room to be surprised by what you learn. This lets you develop deep understanding and momentum at the same pace. You need both. Having one without the other generally doesn’t work out too well.

What’s next for Project Analytics?

Next, we’ll be diving deeper into project-level usage stats, data visualization, and data management, bringing more information and utility into the web console. Basic usage metrics and fixed dashboards like these are just the beginning. We believe the apps and interfaces of the future will be highly self-aware, educating users about usage behavior and opening up new feedback loops that encourage better decision-making with less effort.

Log-in to your Keen IO account to check out your project analytics or create an account to get started. We’d love your feedback. Just shoot us a note on Slack.

How Jawbone uses wearable sensor data to drive habit change

Think about every time you take a step, increase your pace, skip a heartbeat, roll over in the night. If you were to count each time, how many total actions would you have in a day, in a week, in a year?! How would you go about keeping track?

More importantly, how could all that data point the way to a happier, healthier life?

In this data and product design speaker series at Keen IO HQ, Sameera Poduri, Principal Data Scientist at Jawbone, describes how they harness wearable sensor data to help people make healthier choices every day. She covers critical considerations like:

  • What is the right architecture for streaming and processing data from a wearable device?
  • What do you do with the wearable sensor data once you have access to it?
  • How do you process and display personalized insights to each user?
  • How do you use the data to inform product features that drive behavior change?

Check out her talk below:

We love chatting about wearable data analytics strategy. If you’re interested in enhancing your wearable device analytics, reach out to us anytime.

Want to be notified about the next live event at Keen IO? Sign up below to get on the invite list.

Alexa Meyer

Growth and UX. Cheese chaser. Aspiring behavioral economist.

Webinar: Introducing Native Analytics

Thinking about introducing data views as a part of your product?

Native Analytics is a suite of tools that empower you to build and ship white-labeled analytics in your product, in record time. 

Peter Nachbaur, our Director of Product, hosted this 30-minute webinar walking attendees through examples of Native Analytics, its features, and how to get it deployed. 

Why Native Analytics?

A few reasons our customers choose to build Native Analytics into their products:

  • To quantify the impact and value of their product to their customer
  • To drive more sales by selling Native Analytics as a premium feature
  • To differentiate their product from competitors (or keep up with them!)
  • To deliver analytics features that customers have been requesting forever
  • To increase user engagement and get customers hooked

Do you have questions about getting started with Native Analytics? Get in touch!


All right, we’re going to get started with the webinar today about Native Analytics with Keen IO. We’re going to be talking about how to build and ship analytics features for your users, that’s what Native Analytics is all about. I’m Peter Nachbaur. I’m the Director of Product at Keen IO. Been with the company for a long time. I started out as the first engineer, then moved into an architecture role. Today I’m really focused on making use cases like Native Analytics as enjoyable as possible.

Today we’re going to kind of reiterate what Native Analytics is and make sure that you understand what we’re talking about. We’re going to go through some customer examples to highlight some exciting things the folks that we work have done, and then walk through a more specific example to understand the actual features that support Native Analytics and then we will get to questions at the end. Through the Go-to-Webinar interface you can put text questions in there and we’ll get to those at the end of the webinar.

As we start, what is interesting here is that for years Keen IO has built this really scalable and very flexible analytics platform. We can collect data from anywhere and we can help you query that data from anywhere. We’ve supported a number of use cases over the years, a number of different industries for people both working with their data both internally and working with their data externally, but today’s focus is on the Native Analytics use case, which is all about putting your analytics directly in front of your own customers.

This is something that is a little bit different than the internal analytics folks who we are generally familiar with. There’s different latency needs and different privacy needs, but there is also a really, really huge payoff. Rather than working with internal teams you are able to really directly increase the value of the product to your customers and as part of that you are going to be controlling the experience natively so that it kind of increases the perception of your brand.  You’re going to do all of this in a very quick iterative fashion without having to worry about the operational overhead. Keen’s Native Analytics is all about letting you focus on the product design space without having to worry about the broader data infrastructure challenges that we take care of behind the scenes.

Bluecore is one of our most interesting examples. They’re a customer experience platform. They help manage marketing automation campaigns for some really, really major brands; retailers like Staples, and Tommy Hilfiger. What they are able to do is have really fine-grained tracking of the products that they share. When someone is working with you, when Bluecore is working with you, they can say that they do something for you but it is immediately more valuable when they can prove what it does for you. They can get these numbers in front of you and show you the open rate, show you the conversion rate. That’s actually just the beginning. You can then take that data that they show you and more intelligently control the campaigns that you are running and get more out of the automation tools. So it really goes beyond proving what the product does and actually makes the value that much higher.

Pixlee is another interesting example. They work with major brands to get significant conversions from newer social media like Instagram. So they help people track conversions that are otherwise hard to understand and they are able to drive really significant traffic through these brands and in a way that is really valuable to them. But again, being able to actually prove that this is happening is a huge part of it. Being able to understand which pieces of content are most valuable helps these brands come back again and again, to really get more value out of Pixlee.

SketchUp is someone I started working with recently. I just got off a call with them and they do some really fascinating stuff. They are a marketplace for 3D sketches and designs for architects, for manufacturers, for homeowners who are looking to improve things. They are able to allow these designers to understand who is viewing their models and their sketches and sort of begin to create new sketches that will work with their audience even better, to be able to follow up with people who are engaging heavily with the content that is working well for them.

Finally, is perhaps one of the most interesting examples on this list because they built this really fantastic tool to show the performance of the media that they are producing. Both the long form articles and videos but the primary audience for one of the tools they built is not just the publishers they work with but actually the internal editorial team, who doesn’t have to worry about the complexities of an analytics platform or a visualization tool, or having to know a whole lot about how to dig into data. All they have to do is go into this system that was built for them and they can consume and ingest the information that they need to do their job better, and that’s natively built into the internal product that the Mic team maintains.

So we are going to now peek under the hood a little bit about the pieces of functionality that we have built that enable this use case. As we do so we are going to talk about this upcoming company you may have heard about called Walruspring. It’s a pretty crazy thing. The ascension intelligent walruses are coming out with really interesting fashion designs that fit the walrus body type and this all coming out of my mind, of course. I haven’t cloned any walruses and given them superpowers, but you can start to understand the features we’re talking about within the framework of a marketplace where clothing designers are coming in on one end and walrus consumers are coming in on the other end and trying to figure out how to match jackets to their tusks.

When a company wants to do Native Analytics they have some shared requirements. Things they need to understand. They need to be able to have fast and reliable query performance because consumers or partners or publishers are not necessarily going to be patient in the way that internal analysts will be. The team that’s delivering this needs to easily manage this for each customer that comes on. In the past when people would try and showcase data to their own users it would be a very manual process - for each user they added, they would have to configure everything and really customize it and have a lot of overhead and headaches there. A lot of the ways that they would end up doing it, it would be very janky - it wouldn’t match the brand and wouldn’t be a seamless part of the experience. So when people are look for Native Analytics, they are looking to be able to have all of these capabilities.

The cool thing is that this is a lot of functionality that we’ve designed and built on top of the core horizontal platform. So as you think about some of these things that we’ve built, I’d be interested to hear how you might want to use them in different use cases beyond just adding analytics into your own application.  The main components here are being able to programmatically create accounts, to manage access, to introduce caching, to get good performance, to be able to embed the charts, and then to be able to fully customize and control the visualizations.

So for Walruspring, when they are onboarding new designers they’ve got a flow where you sign in, you’re introduced to the platform, you get a sense of the features and behind-the-scenes, they start managing your account information. As part of that, they can make a simple API call to Keen that says “Hey, we had this new designer sign up and here is the information about Mark, and we are going to create this project that is totally separate for him. His data will be isolated both for privacy and for performance concerns.” So when they then move on to the next stage to pick out what access Mark should have into the data, it’s really going to be only the data that his consumers are seeing. Once you have those specific projects you are able to then have custom API keys, and these keys can have a lot of functionality baked into them - filters, so if you want to control the exploration and experience that they get, if you want to have different roles, so maybe, within the Walruspring environment, there is a basic tier for designers and there is a more premium tier where they are able to have to have additional access. You can control that through a customer specific key. You can say “Well okay, they have now unlocked this additional potential.”

Additionally, on the flipside, as we’re collecting data as part of a platform, these custom keys can actually automatically add customer specific data and enrichment so that the application itself is worried about here is the core data model that is shared across all customers and then, depending on the key that is used to collect data, one designers data will be added or another designers data will be added. That then seamlessly flows into how you think about the data model. You’re able to have the information about the product, or about the behavior, viewing different pieces of clothing as well as the specific customer properties that let you both do the internal analysis that you have done historically, and then also be able to present that in a way that is meaningful to each individual designer.

So, the Walruspring team is at a stage where they’re creating projects on the fly as new designers sign up. They’re managing the privacy performance of that. They’re collecting the data. Now they’re able to sit back and say “From a product design perspective, what do our walruses need to make sure that they’re selling the most clothing”, (…) make sure they are understanding their audiences so they can go through this exploratory phase and get to that "Eureka” moment of thinking, “Well these are few queries that will really help the designers get the most out of the Walruspring platform.”

Once those queries have been identified, they can be optimized. They can be cached. These high value questions are then going to respond very very quickly, in very predictable fashion, so that the designers, when they are logging in, they’re not seeing really long load time or having a bad experience there, so that they can jump around, but their own exploration is not slowed down by the challenges of the data infrastructure. So caching is a really huge tool. Once you’ve done that initial design-level exploration to figure out what people care about, you can then productionalize individual queries or full dashboards to make sure that experience is perfect.

Once you’ve got those queries it really becomes a matter of embedding the analytics, and this is really what makes it a native experience. We’re not talking about really heavy weight iframes or stuff that has a logo or a brand - you have complete flexibility with these charts, so you’ve got a pretty decent design sense when things come out of the box. You’ve got a color palette that you think is pretty attractive but the thing is that it has nothing to do with your branding and as you are going from that internal use case where it’s really easy on the eyes but a little generic, you are able to then, in the JavaScript itself, control what visualization library you’re using, specific chart types, the size, and the color. We’ve actually seen folks really go the extra mile here, and produce visualizations that would be worthy of the front page of The New York Times. It’s really impressive stuff.

We have a link here that we can share later, we can share an example of all the different ways that the data can be visualized and the library can be used.

Beyond some of these core things about onboarding your customers, and controlling access, and managing performance, you can actually then expose some of the more raw functionality and let the customers dig into CSV files, to be able to pass those reports around but plug them into systems that they already have. So we see use cases where people are regularly sending exports to their users so that they can wire that into existing systems. They can then answer their own questions and really get the maximum value from that. And again, because of the custom keys that we discussed earlier, you can rest assured that the data they have access to is only the data that belongs to them. They are then able to do complex modeling on their own or you can downstream, use the raw data that we’ve collected to start adding more predictive analytics functionality or recognition functionality to, again, keep making sure that they get as much value out of the data as possible.

A final aside is that, along on this theme of natively and seamlessly matching your brands, you can make sure that the API endpoint itself takes advantage of a custom cname so that, in this case, you would be able to send data to and there would just be no external way to know that this is powered by Keen. We’re thrilled to be able to help folks with this use case in a white label capacity.

We’ll briefly just talk over this little demo site that we’ve got that shows the Walruspring experience. This first page is what the consumer walruses would be seeing, and they’re able to kind of take a look at all this ridiculously creative clothing that the walrus designers have put together. I think, of these, I’m really feeling the pajamas right now. It’s little chilly in the office and I wish I had some nice fuzzy stars.

To reiterate, this is the same data that you are probably already collecting today, you’re thinking about the flow, you’re able to think about what the product ID is, the product name, all that sort of core information; and as the consumer is progressing through the site, different events are being sent. All that information is being tracked. As they continue down the flow, they check out, more data is collected. When they purchase it’s a really big piece of data that is an important part of the flow.

As far as the consumer is concerned that is just the experience. The analytics is not detracting from that. They’ve gotten these awesome, super comfy button-up pajamas, for a really reasonable price, and they can go on with their lives. But then, internal to the product experience, a Walruspring designer is going to be able to login in and have this analytics tab, which shows them what their conversion rate is, what their repeat purchase rate is, and really help them understand, “Okay, for the different products that I’m offering I’m really seeing heavy conversion in this area but pajamas are somehow really popular and that’s a bit unexpected and we can actually maybe look into why that might be.” As a design team you think “Okay, well we should make a couple different types of pajamas and really capitalize on that.” That’s the kind of decision making the customers can feel really good about. So, not only are they getting value from all of Walruspring because it connects them to these consumers and they can put a product up on the website and get sales from it, but they can actually then have this additional information to get more in depth sales.

So, to reiterate, the Native Analytics is all about full control while still having a very simple integration and an integration where you don’t have to worry about the challenge of data construction, the challenge of scaling. You can focus on the really fascinating questions on what makes your customers happier, what makes your customers smarter. These are often very aligned with the metrics that help you grow your product internally, as a product team or as a marketing team. You’re already looking at some of this information in aggregate but you can slide around a little bit and put yourself in their shoes, or wear their tusks for a day, to understand, as they’re doing their job, and as they’re using your product, what will help them get the most out of it and what is a natural progression. So they’re logging in and they’re going to check on the functionality that you’ve already got, whether that’s marketing automation, or social media conversions, or walrus clothing. What’s going to be a natural part of their flow and is that a full-on dashboard? Is that just small pieces of data that are wired directly into other parts of their experience? It’s a pretty open-ended question. It’s something that I encourage you all to think about. It gives you a lot of flexibility to iterate quickly.

So, be happy to take some questions. Both about the specific features and details that we talked about there or the use cases that we’ve seen.

Author’s note: apologies for the echoes and inaudible moments in the recording during the Q&A, and the impact this had on our transcript!

All right. This is Sarah-Jane. We’ve got a couple of questions in through our question interface and we’re going to leave that open a little while, so if you have any questions feel free to drop those in. Just give me one second while I bring those up.

All right. So the first question is what other charting libraries can it support and can I use my own visualizations?

Yes, absolutely. So, on that previous slide where we’ve been looking at the visualization code you can very easily toggle between charting libraries, Google charts, C3, D-3, those are all powered by our API. The raw JSON that is returned can be visualized by any system that you’re more comfortable with.

Great. Another question here. Can I update the metrics that I show my customers without coding once Keen is implemented?

Yes and no. There’s a really cool way to be able to do that today and we’ve actually got some products available to make that even easier. But we have saved queries where as you’re doing exploration of the data, thinking about what’s valuable in terms of that  that “Eureka” moment I was mentioning, you can then save that actual query. You can actually tie that to a custom API key and say, “This key for Tommy Hilfiger only has access to these saved queries.” Maybe have a Tommy Hilfiger Average Purchase query. If you then make a chart for that and put the metric for that chart into your products you can go back and using our interface, change the saved query and where you have embedded and then you just naturally take advantage of the changes that you’ve made to that saved query.

Great. Got a question here. Is it possible to track location natively with Keen? Would you just send an event with the locational information?

Oh yeah. You have a handful of different tools and put those into add-ons into these custom API keys and geolocation wise (…) because it lets you do mapping views of data to figure out by state, by zipcode, by country, where people are buying all this clothing, you can take (…) patterns,  you can take an IP address and can expand that out into geographic information. We can give you latitude and longitude so you can really map that info . We have some stuff in the backboard there that geographic… everything’s basically even more powerful.

Great. One more question here. What is the current timeline to get Native Analytics implemented?

Oh, that’s a great question. So, Bluecore, which was one of the examples we talked about earlier, is probably the most impressive example. They were able to get that dashboard looked at briefly and up-and-running in less than 24 hours. It was actually just built by an internal team that they had. I know that the team was able to get that information to their editors as part of their workflow in a matter of days. Generally the answer that I give is tied to an individual company’s development workflow. So, if your team is pushing code to production in a matter of hours then you can absolutely start making these changes very quickly. (…)

Great. I believe we’re going to be answering question for a little bit longer. If there’s anymore… We’re going to be sharing the recording of this webinar, so if you have any further questions go through one of the channels listed on this final slide. For our Slack chat go to and join us there with any questions you may have. Maybe check out our Github repos and, of course, tweet us any time and tweet us on our website with any further questions. Have any closing thoughts, Peter? I will hand it over to you… Oh, we have some more questions. One second, here… alright, what’s the pricing model? Is it by license or SaaS subscription?

Yeah, that’s a good question. So, we look to understand your usage, unlike products like a marketing automation platform for example, where you’d be sending out a very discrete, understandable number of emails. With Keen, the data that you’re tracking… the volume can get very large. A whole bunch of data has allowed us to look at that but the impact in usage varies dramatically depending on whether you’re doing a couple queries a minute, or an hour, or a day for that internal use case that some of you are familiar with. On the Native Analytics side, what we like to understand to get a sense of usage is how many customers you’re looking to serve today, to ensure the number of queries you’re going to be looking to optimize and keep running so that they get that seamless cached experience. Because our core offering is a very flexible and very customizable API, then we’ll perfectly match your product needs to let you build exactly the analytics experience that you want. There isn’t really a one-size-fits-all, if you’re going to be querying across hundreds of millions of events and you’re going to be doing that thousands of times an hour then it’s going to be more expensive than if you only have a few million events and fewer customers asking questions across that data.

Great. Another question is, “Do you offer machine learning algos on the data and if not, how can one run a custom routine on your data”

So, we don’t have API-level functionality around running machine learning today, although it is definitely part of our design and roadmap. So what we do to meet that use case is our solutions architects will sit down and take a look at the raw data that’s available and help put together the laws that make sense. Generally what folks want to be able to do is have offline classifiers that you’d be able to actually, as part of a clone, make online checks against that. We’ve got a handful of folks on the team, myself included, have done that a number of times. What did end up happening was largely downstream from the data production and analysis and Native Analytics features that we were talking about today.

All right. So that’s pretty much it. No more questions. Thanks so much Peter and thanks to everyone on the webinar today. As I mentioned, we’re sharing the recording and feel free to connect with us on our community channels. Have a great day.

Looking forward to hearing more and let me know how I can help.

Sarah-Jane Morris

Community and Awareness

Introducing the Keen IO Community Code of Conduct

A few weeks ago we sent an email to the whole company introducing the Keen Community Code of Conduct. This blog post includes most of that email with a few more things added that we wanted to share with our community.

A few months ago the work began on the Keen IO Community Code of Conduct. We’re very excited to announce v1.0 of the Keen IO Community Code of Conduct is now public. 🎉

This Code of Conduct applies to all Keen IO Community spaces, such as the Community Slack group, open source projects, Keen IO meetups, Happy Data Hours, and more! It will be added over the next few weeks to different projects and other community spaces.

It is the product of many meaningful conversations and advice from many Keenies and other humans from outside of Keen IO. To anyone that contributed to this Code of Conduct, thank you. The process of creating a document like this isn’t easy, and we have so much respect for anyone who has done it before.

The Code of Conduct is a living document. This is only v1.0. It will grow and change with Keen IO and its community. This is why it is on Github. Issues can be created to help with revisions and updates. There is also a feedback form, which can be filled out anonymously. Feedback is always appreciated. It will also help guide training and more internal procedures for the Community Code of Conduct.

Lastly, we’re looking forward to making it even clearer to our community that we are dedicated to providing a safe, inclusive, welcoming, and harassment-free space and experience for all community participants, which will help grow our community in amazing ways. We hope this Code of Conduct clearly states what behavior is expected and not tolerated as well as establishes a path for community members to report possible incidents and seek help.

Please feel free to ask me any questions! I would be more than happy to have a larger conversation about it and its existence. 😀

Taylor Barnett

developer, community builder, and huge fan of tacos