Category: UNCATEGORIZED

A few months ago, I wrote a piece about esports and the Olympics after sitting on a panel discussing whether, as a result of the coronavirus pandemic, esports had an opportunity to work with the International Olympic Committee. After careful consideration and research, my conclusion was basically, “I think that the Olympics need esports a whole lot more than esports needs the Olympics.”

I was surprised by some of the data I uncovered in the course of researching the Olympics piece, specifically on audiences for international, professional and collegiate sports. I observed that while the esports model isn’t as mature as in traditional sports, esports actually garnered close to the same level of viewership, and the audience was growing astronomically. I couldn’t help but wonder how long this phenomenon would go unacknowledged by the institutions that might benefit most from it.

Enter colleges’ and universities’ flirtation with esports: There are currently more than 170 collegiate varsity gaming programs in NCAA Division I, and the number of clubs is even higher. So even as institutions investment in esports, there are still many misunderstood and overlooked aspects of the potential to drive value (and even revenue) in the collegiate esports space.

College in the 21st century

The college experience today is very different than it was 50 years ago. The pace of change outside of institutions is ever-accelerating, often leaving colleges struggling to keep up. Technology, students’ interests, evolving economies and workplaces, and changes in cultural norms have left colleges and universities in a place of less relevance than at many points in the past.

The same can be said of college sports: Outside forces have eroded a once-near-hegemonic source of collegiate pride, cultural power, recruitment, alumni engagement and, in some cases, revenue.

I did a quick review of the audience for the biggest NCAA events in the world; the Football Bowl Subdivision Bowl Championship and the NCAA Men’s Division I Basketball Tournament.

Image Credits: Brandon Byrne

Image Credits: Brandon Byrne

Look at the average viewership of the big bowl games before the championship system went into effect in 2015, as well as after. Above, you see the trend line for viewership for the various big bowl viewership as well as an average. While there are certainly occasional spikes, the best case you could make here is that the product is flat — when you isolate the trend line for both, here is the result:

Image Credits: Brandon Byrne

In the aggregate, the trend seems mostly downward.

Look at the same trends in viewership for the NCAA Final Four — the early semi-final, the late semi-final and finally the championship game.

Image Credits: Brandon Byrne

They look rather similar. So, while collegiate sports still have a massive following, there are two concerning issues here. First, the audience isn’t growing at all; in fact, it appears to be slightly contracting. Secondly, the audience is aging, making collegiate sports less relevant to younger people. While an older audience is still a valuable source of alumni donations and ancillary revenue, it doesn’t exactly align with another core target demographic: potential college students.

Now despite this, there is data that suggests that schools with elite academic departments do enjoy a phenomenon known as the “Flutie effect,” named after Doug Flutie, a quarterback for Boston College whose exciting performance on the gridiron was credited with boosting BC applications. An article in Forbes breaking down an HBS study goes into the phenomenon more deeply than we can here.

Granted, much of the data is from a few years ago, when college sports were perhaps more relevant, but the point is broadly the same: Having an elite program in an activity students enjoy benefits the institutions that sponsor and promote them. But what happens when enthusiasm for those activities among the student body is waning? One idea is to explore involvement in what the students of today are interested in.

As a comparison to FBS football (maxed out at 35 million viewers) and the NCAA Final Four (maxed out at 28 million), Riot Games’ Mid-Season Invitational event for League of Legends had a total viewership of 60 million people. In second place is the Intel Extreme Masters tournament in Katowice with 46 million people. While precise demographic data isn’t readily available, it stands to reason that the latter two events skew younger than the former two.

A few caveats, as these are not precisely apples-to-apples comparisons: These esports events are broken up over a number of days and encompass a significant number of matches — comparable to March Madness, perhaps — and the content is consumed in different ways. Much of the NCAA’s content is presented on television, some of which is on paid, premium channels. Esports events are broadcast on Twitch and YouTube via streams for free.

But the thing to understand is that esports audiences are growing at a 15%-16% year-over-year clip and it commands a worldwide audience, meaning its total addressable market (TAM) is MUCH bigger. The NCAA events are not likely to draw serious audiences outside of North America.

COVID-19

In the context of the pandemic, colleges are hamstrung by students’ inability to engage in a college experience in-person, which is one of the primary reasons one goes to college. Networking, developing new friends and having new experiences are all a part of the collegiate draw, none of which work as well from students’ parents’ living rooms. Similarly, collegiate sports as we know them have essentially ceased to exist, along with their functions of institutional pride, marketing and revenue. The NCAA Tournament was canceled in March of 2020 and there is no sign that it, or any other sport, will be back anytime soon.

Esports, on the other hand, are thriving in this context, thanks mostly to their ability to offer remote competition and viewing. Esports tournaments can isolate audiences, teams and even referees to allow for safe content creation and consumption.

Esports and college

Believe it or not, esports is a better fit for college than it is for the pros. I won’t go into all of the details here, but I actually wrote a separate article about why the pro sports model is NOT a good one for esports. In this article we talk about intellectual property, who owns the league in esports and how all of the entities make money. The biggest problem is, in pro sports, the teams own the league and can then act in the best interest of all of the teams. In esports, the league is usually owned or regulated by the publisher of the video game, meaning you have hands in the monetization pie in a way that pro sports doesn’t have.

The interesting thing about this is that college athletics actually has the same problem and has found a way to mitigate that. The athletes get their scholarships, and the schools, their athletic conference, and the NCAA itself all own a piece of the pie that gets packaged and sold for distribution to the ESPNs and Fox Sports of the world.

This is a much better model for esports. It’s unlikely that any group that “owned” football IP would tell the Dallas Cowboys how to market their team, what their cut is and how it will be distributed. This process happens all the time in college, though. In fact, in order for everyone to get their seat at the table, you HAVE to work all of this out so that the schools make some money (equivalent to a team), the conference makes their money (equivalent to the league) and the NCAA makes their money (equivalent to the publisher themselves). If the chain breaks down at any point, then the whole process grinds to a halt and nobody makes money.

I mention this in my article about the Olympics. The IOC is used to having full autonomy over how the Olympic Games are broadcast, which events are part of the games, who is eligible and who isn’t, etc. There is no chance this would be the case if the Olympics took on esports. The publisher would absolutely wield an incredible amount of influence over how the games are portrayed, broadcast, judged and the like. The IOC isn’t used to that. In college, that’s just a typical Saturday afternoon.

College admission is down and not just because of COVID-19. Even before the pandemic, colleges were trying to find their footing with potential students as people reevaluate the college experience. Forbes wrote back in 2019 that college enrollments were down two million students in that decade. Add onto that the preliminary data we are getting on the effect of COVID on colleges, we could see enrollment in 2020 down anywhere from 5%-20%.

Image Credits: Brandon Byrne

The outlook

For colleges, it’s not great. Revenue is massively down, with even stalwarts like Harvard University hemorrhaging cash. With enrollment down before the pandemic, we have reached a point where colleges and universities have to adapt to survive.

The good news is, I believe that esports could be an opportunity to do just that. Colleges are diving into esports, with 115 different programs offering scholarships for esports and club programs are growing even faster. Certainly, it will help attract students, but monetization in esports is really tricky.

It’s critical that colleges and universities get expert advice on how to create an ecosystem that ultimately compensates all of the stakeholders, including the college themselves. It also will require universities to move quickly and get on board with a model that is still being formed in real time. The coronavirus pandemic isn’t going away anytime soon, but I think there will be many colleges that will. The time to move is now.

Deep Vision, a new AI startup that is building an AI inferencing chip for edge computing solutions, is coming out of stealth today. The six-year-old company’s new ARA-1 processors promise to strike the right balance between low latency, energy efficiency and compute power for use in anything from sensors to cameras and full-fledged edge servers.

Because of its strength in real-time video analysis, the company is aiming its chip at solutions around smart retail, including cashier-less stores, smart cities and Industry 4.0/robotics. The company is also working with suppliers to the automotive industry, but less around autonomous driving than monitoring in-cabin activity to ensure that drivers are paying attention to the road and aren’t distracted or sleepy.

Image Credits: Deep Vision

The company was founded by its CTO Rehan Hameed and its Chief Architect Wajahat Qadeer​, who recruited Ravi Annavajjhala, who previously worked at Intel and SanDisk, as the company’s CEO. Hameed and Qadeer developed Deep Vision’s architecture as part of a Ph.D. thesis at Stanford.

“They came up with a very compelling architecture for AI that minimizes data movement within the chip,” Annavajjhala explained. “That gives you extraordinary efficiency — both in terms of performance per dollar and performance per watt — when looking at AI workloads.”

Long before the team had working hardware, though, the company focused on building its compiler to ensure that its solution could actually address its customers’ needs. Only then did they finalize the chip design.

Image Credits: Deep Vision

As Hameed told me, Deep Vision’s focus was always on reducing latency. While its competitors often emphasize throughput, the team believes that for edge solutions, latency is the more important metric. While architectures that focus on throughput make sense in the data center, Deep Vision CTO Hameed argues that this doesn’t necessarily make them a good fit at the edge.

“[Throughput architectures] require a large number of streams being processed by the accelerator at the same time to fully utilize the hardware, whether it’s through batching or pipeline execution,” he explained. “That’s the only way for them to get their big throughput. The result, of course, is high latency for individual tasks and that makes them a poor fit in our opinion for an edge use case where real-time performance is key.”

To enable this performance — and Deep Vision claims that its processor offers far lower latency than Google’s Edge TPUs and Movidius’ MyriadX, for example — the team is using an architecture that reduces data movement on the chip to a minimum. In addition, its software optimizes the overall data flow inside the architecture based on the specific workload.

Image Credits: Deep Vision

“In our design, instead of baking in a particular acceleration strategy into the hardware, we have instead built the right programmable primitives into our own processor, which allows the software to map any type of data flow or any execution flow that you might find in a neural network graph efficiently on top of the same set of basic primitives,” said Hameed.

With this, the compiler can then look at the model and figure out how to best map it on the hardware to optimize for data flow and minimize data movement. Thanks to this, the processor and compiler can also support virtually any neural network framework and optimize their models without the developers having to think about the specific hardware constraints that often make working with other chips hard.

“Every aspect of our hardware/software stack has been architected with the same two high-level goals in mind,” Hameed said. “One is to minimize the data movement to drive efficiency. And then also to keep every part of the design flexible in a way where the right execution plan can be used for every type of problem.”

Since its founding, the company raised about $19 million and has filed nine patents. The new chip has been sampling for a while and even though the company already has a couple of customers, it chose to remain under the radar until now. The company obviously hopes that its unique architecture can give it an edge in this market, which is getting increasingly competitive. Besides the likes of Intel’s Movidius chips (and custom chips from Google and AWS for their own clouds), there are also plenty of startups in this space, including the likes of Hailo, which raised a $60 million Series B round earlier this year and recently launched its new chips, too.

It’s price hike season!

Just a few weeks after Netflix bumped up prices on a bunch of its plans, it looks like Hulu will soon be charging more for its Live TV service.

The company has confirmed to us that it will be bumping the monthly cost of Hulu + Live from $54.99 to $64.99 as of December 18th — an increase of around 18%. The price increase will go into effect for both existing and new subscribers. The “No Ads” live TV plan, meanwhile, will increase from $60.99 per month to $70.99 per month.

To be clear, this price increase seemingly only impacts the plans that include live TV; there’s no word, currently, on any price changes for Hulu’s on-demand streaming offerings.

Hulu + Live originally launched in May of 2017, initially costing $40 per month.

Many consumers might think Noom or Weight Watchers are industry leaders with their nonstop commercials, but neither is the fastest-growing weight management program.

Over the past year, nutrition app Lifesum has acquired users at nearly twice the rate of both Noom and Weight Watchers, according to statistics from Sensor Tower, the independent market intelligence for the mobile app economy.

Over this past summer, we surpassed Noom on the global scale with 45 million users. More impressively, we accomplished this without any TV buys. That’s right — no multimillion dollar ad campaigns, allowing us to redistribute precious marketing dollars to other growth projects.

Here’s a closer look at the three growth marketing tactics I credit with helping us scale Lifesum over the last 36 months. It’s a strategy any startup can use, regardless of size or budget.

Understand the different generational lenses

Generations approach products differently. It’s important for startups to understand the different generational approaches of their customers. Startups that spend time thinking and strategizing about where generational trends are going will scale faster.

Millennials and Generation Z are now the largest consumer market in the world, so you can’t ignore them if you want to scale. With Lifesum these generations have helped our brand surpass the older and well-established competitors. We achieved this by intimately understanding how they view health and fitness.

Gen Z and millennials are all about empowerment. They grew up with Google and Facebook, having information at their fingertips. They are far less likely to be moved by a TV commercial since they desire to discover the world on their own.

In our industry, we’ve learned millennials and Gen Z don’t want a one-size-fits-all weight loss program or to count calories like their parents did 20 years ago. As millennials and Gen Z started embracing keto, intermittent fasting and pescatarian diets, our nutrition team had already created tailored programs to help them stick with it.

Bypass traditional marketing methods

As a brand, it’s important to look ahead and anticipate what is coming next. This also applies to marketing your product. If you get in early with emerging marketing platforms, you will save money and potentially reach more early adopters.

Arrikto, a startup that wants to speed up the machine learning development lifecycle by allowing engineers and data scientists to treat data like code, is coming out of stealth today and announcing a $10 million Series A round. The round was led by Unusual Ventures, with Unusual’s John Vrionis joining the board.

“Our technology at Arrikto helps companies overcome the complexities of implementing and managing machine learning applications,” Arrikto CEO and co-founder Constantinos Venetsanopoulos explained. “We make it super easy to set up end-to-end machine learning pipelines. More specifically, we make it easy to build, train, deploy ML models into production using Kubernetes and intelligent intelligently manage all the data around it.”

Like so many developer-centric platforms today, Arrikto is all about “shift left.” Currently, the team argues, machine learning teams and developer teams don’t speak the same language and use different tools to build models and to put them into production.

Image Credits: Arrikto

“Much like DevOps shifted deployment left, to developers in the software development life cycle, Arrikto shifts deployment left to data scientists in the machine learning life cycle,” Venetsanopoulos explained.

Arrikto also aims to reduce the technical barriers that still make implementing machine learning so difficult for most enterprises. Venetsanopoulos noted that just like Kubernetes showed businesses what a simple and scalable infrastructure could look like, Arrikto can show them what a simpler ML production pipeline can look like — and do so in a Kubernetes-native way.

Arrikto CEO Constantinos Venetsanopoulos. Image Credits: Arrikto

At the core of Arrikto is Kubeflow, the Google -incubated open-source machine learning toolkit for Kubernetes — and in many ways, you can think of Arrikto as offering an enterprise-ready version of Kubeflow. Among other projects, the team also built MiniKF to run Kubeflow on a laptop and uses Kale, which lets engineers build Kubeflow pipelines from their JupyterLab notebooks.

As Venetsanopoulos noted, Arrikto’s technology does three things: it simplifies deploying and managing Kubeflow, allows data scientists to manage it using the tools they already know, and it creates a portable environment for data science that enables data versioning and data sharing across teams and clouds.

While Arrikto has stayed off the radar since it launched out of Athens, Greece in 2015, the founding team of Venetsanopoulos and CTO Vangelis Koukis already managed to get a number of large enterprises to adopt its platform. Arrikto currently has more than 100 customers and, while the company isn’t allowed to name any of them just yet, Venetsanopoulos said they include one of the largest oil and gas companies, for example.

And while you may not think of Athens as a startup hub, Venetsanopoulos argues that this is changing and there is a lot of talent there (though the company is also using the funding to build out its sales and marketing team in Silicon Valley). “There’s top-notch talent from top-notch universities that’s still untapped. It’s like we have an unfair advantage,” he said.

Image Credits: Arrikto

Apple is making it easier to discover and listen to podcasts via the web. The company announced today an Apple Podcasts embed web player is now available, allowing anyone — including creators, listeners or marketers — to generate embed codes for the over 1.5 million shows available across the Apple Podcasts service.

The codes can be generated from the Apple Podcasts Preview pages on the web or from the Apple Podcasts Marketing Tools website.

For the former, you would first click the share icon on the Preview page for either a show or an individual episode. You’ll then see a new “embed” button on the left hand side.

And in the case of the latter, you would enter the URL for the podcast or episode you want to embed on the Marketing Tools website, then scroll down to the bottom of the page to see the options for the embed player.

Here, you can also adjust the options for the player’s height and width to your own specifications or leave it at the default setting of 450px x 660px. When you’re ready to grab the code, you just click the “Copy Embed” button which automatically copies the code to your clipboard for pasting elsewhere.

Here’s an example of what the embed looks like:

When visitors happen upon the embedded web player, they can interact with the podcast immediately by playing the episode and by opening the Apple Podcasts app for iOS, iPadOS or macOS to learn more about the program or to add it to their existing podcast subscriptions.

The new feature aims to help Apple retain and grow its audience of podcast listeners who use its own app for following their favorite audio programs. It arrives at a time when rivals, led by Spotify, are increasing their investments in podcasts. Spotify continues to acquire podcast studios and ad technology, while also rolling out more tools and features for podcast creators and listeners alike. Spotify, too, already offers an embed feature for its podcasts, which allows it to direct users to its own service.

Apple says its Apple Podcasts web embed is broadly available as of today.

GitHub has restored the code of a project that the RIAA demanded it take down last month after finding that the group’s DMCA complaint was meritless. YouTube-dl, a tool that lets videos from the streaming site be downloaded for offline viewing, is back in action — and GitHub is changing its policy and earmarking a million dollars for a legal defense fund against future importunities.

The controversy began in mid-October when the RIAA sent a DMCA complaint to GitHub claiming that YouTube -dl violated the law no only by providing a tool for circumventing DRM, but by promoting the piracy of several popular songs in its documentation.

GitHub, like many tech companies, tends to assume the veracity of a complaint like this if it’s from a known entity like the RIAA, and it seems to have done so here, taking down YouTube-dl and publishing the complaint.

As many pointed out at the time, saying this project is a tool for circumventing DRM is like saying a tape recorder is a tool for music piracy. It’s used for far more than that, from research and accessibility purposes to integration with other apps for watch-later features and so on.

After a fork of YouTube-dl was created that lacked the references to popular YouTube videos as examples for use, the project was largely back online. But then GitHub received a letter from the internet freedom advocates at the Electronic Frontier Foundation and realized they’d been had.

As the EFF letter explains (and as the technically savvy GitHub must surely have suspected from the start), the YouTube-dl project was never in violation of the DMCA. In the first place, what the RIAA described as a suggestion in the documentation to pirate certain songs is only a test that streams a few seconds of those videos to show that the software is working — well within fair use rights.

More importantly, the RIAA misconstrues the way YouTube and YouTube-dl’s code works, mistaking a bit of code on the video site for encryption and concluding that the tool unlawfully circumvents it, violating section 1201 of the DMCA. They also refer to a court case supporting this interpretation.

In fact, as the EFF explains patiently in its letter, the code does nothing of the sort and the way YouTube-dl’s agent “watches” a video is indistinguishable to YouTube from a normal user. Everything is conducted in the clear and using no secret codes or back doors. And the court case, the EFF notes, is mistaken and at any rate German and not applicable under U.S. laws.

GitHub, perhaps feeling a bit ashamed for having folded so quickly and completely in the face of a shabbily argued nastygram from the RIAA, announced several changes to prevent such occurrences in the future.

First, all copyright claims under section 1201 — which are fundamentally dubious — will receive a technical and legal review, and an independent one if necessary, to evaluate the truth of their assertions. If the findings aren’t decisive, the project will be left up instead of taken down while the proceedings continue. Should the project seem to be in violation, they will be given a chance to amend it before takedown. And if a takedown occurs, the developers will still be able to access important data like pull requests and bug reports.

Second, GitHub is establishing a $1M developer defense fund that will be used to protect developers on the platform from bad section 1201 claims. After all, faced with the possibility of a court battle, many a poor or hobby developer will simply abandon their work, which is one of the outcomes being counted on by abusers of the DMCA.

And third, the company will be continuing its lobbying work to amend the DMCA and equivalents around the world, with a specific focus on section 1201 it plans to announce soon.

It’s a happy ending for this little saga, and while DMCA abuse is a serious and ongoing issue, at least the bullies didn’t get their way this time. Until the law changes this will continue to be an issue, but vigilance and strongly worded letters will do in the meantime.

Activity and fitness tracking platform Strava has raised $110 million in new funding, in a Series F round led by TCV and Sequoia, and including participation by Dragoneer group, Madrone Capital Partners, Jackson Square Ventures and Go4it Capital. The funding will be used to propel the development of new features, and expand the company’s reach to cover even more users.

Already in 2020, Strava has seen significant growth. The company claims that it has added over 2 million new “athletes” (how Strava refers to its users) per month in 2020. The company positions its activity tracking as focused on the community and networking aspects of the app and service, with features like virtual competitions and community goal-setting as representative of that approach.

Strava has 70 million members already according to the company, with presence in 195 countries globally. The company debuted a new Strava Metro service earlier this year, leveraging the data it collects from its users in an aggregated and anonymized way to provide city planners and transportation managers with valuable data about how people get around their cities and communities – all free for these governments and public agencies to use, once they’re approved for access by Strava.

The company’s uptick in new user adds in 2020 is likely due at least in part to COVID-19, which saw a general increase in the number of people pursuing outdoor activities including cycling and running, particularly at the beginning of of the pandemic when more aggressive lockdown measures were being put in place. As we see a likely return of many of those more aggressive measures due to surges in positive cases globally, gym closures could provoke even more interest in outdoor activity – though winter’s effect on that appetite among users in colder climates will be interesting to watch.

Strava’s app is available free on iOS and Android, with in-app purchases available for premium subscription features.

Four years ago, shared e-scooters didn’t exist. Today, they’re on track to surpass half a billion rides globally by 2021, far outpacing early growth in the carbon-heavy ride-hailing industry founded by Uber in 2009.

That’s a dramatic shift in urban transportation by any measure, and it prompts a simple but important question: How did we get here?

Understanding the key developments that helped advance micromobility over the past several years can give us valuable insights not only into where the industry is headed, but about how we can successfully shape it to meet the needs of hundreds of millions of current and future riders around the world.

From vehicle design and data to safety reporting and infrastructure, these five innovative moments have helped fuel the global growth of shared e-scooters and are helping lead cities into a healthier, more sustainable future.

#1: Shared scooters launched (fall 2017)

The very first fleet of Bird e-scooters was launched in Santa Monica, California in September of 2017. Up until this point, the micromobility industry consisted almost entirely of docked and dockless bike sharing systems that were averaging approximately 35 million trips across the United States every year — more than half of them in New York City alone.

After an encouraging start, shared e-scooter riders in the U.S. took nearly 39 million trips in 2018 and another 86 million the following year. A similar trajectory is being seen across the Atlantic, as nations such as Italy, England and the Ukraine join a rapidly expanding list of countries including Germany, France, Israel, Spain, Portugal, Belgium, Denmark, Poland and others who have chosen to supplement their urban transportation networks with modern micromobility alternatives.

Shared scooters can now be found in over 200 cities on almost every continent around the world.

#2: First custom-designed shared scooters released (fall 2018)

The first e-scooter programs taught us two things very quickly: There’s high demand for this type of micromobility offering, and custom-designed vehicles are necessary to successfully meet that demand.

The fact is, shared scooters are ridden more frequently, handle more diverse road surfaces and endure more varied weather conditions than privately owned ones. That’s why Bird’s vehicle team unveiled the industry’s first custom-designed e-scooter, the Bird Zero, in October of 2018. Equipped with more battery life, better lighting, enhanced durability and more advanced GPS technology, this was the first in a series of comprehensive vehicle evolutions intended to increase safety, sustainability and lifespan — and it worked. Tens of thousands of these scooters are still in use today, and every month of continued service reduces their already low per-mile lifetime carbon emissions even further.

Subsequent custom vehicle designs, including the Bird One and Bird Two, have added onto this foundation, introducing industry-first features such as:

• On-board diagnostic sensors capable of detecting over 200 faults.
• Vehicle intelligence systems capable of running and reporting millions of autonomous fault checks per day.
• IP67 or IP68 waterproofing on batteries.
• 14,000 mile (22,500 km) battery life, resulting in more than 10 years of average everyday use.
• Mechanical design independently tested to withstand more than 60,000 curbside impacts.

#3: Comprehensive industry safety report released (spring 2019)

Safety has rightly been the most important focus, and the most discussed aspect, of shared micromobility since its inception. It’s why Bird launched the industry’s earliest and most comprehensive free helmets for all riders campaign in January of 2018, along with a host of other safety initiatives.

In April of 2019, these programs culminated in a comprehensive e-scooter safety report. This was the first in-depth look at modern micromobility systems, using accident reports and other data to demonstrate that shared scooters have risks and vulnerabilities similar to bicycles. The report laid the groundwork for cooperative safety measures to be taken by both operators and cities to ensure that not only riders and pedestrians but all road users are protected.

Over the past year and a half, we’ve used the findings contained within the report, along with others that have since echoed its findings, to imagine and develop a series of product innovations that are helping set the standard for e-scooter safety across the industry. These include:

• Shared micromobility’s first Helmet Selfie feature to promote helmet use.
• Shared micromobility’s first Warm Up Mode feature to assist new riders.
• The first and most accurate geofencing for e-scooters to create reduced-speed and no-riding zones.
• Responsible data-sharing standards and practices to help cities build new infrastructure for bikes and scooters.

#4: Open Mobility Foundation created (summer 2019)

The last bullet above is particularly important. Cities have a crucial role to play in limiting the number of cars on the road and maximizing the amount of infrastructure available for bikes and scooters. It’s a proven strategy to improve the safety of all road users that depends heavily on one critical input: reliable, standardized data.

Since our first launch, Bird has been a strong proponent of responsible data sharing with cities. What was lacking, however, was a unified body to help guide and develop mobility data standards across the micromobility industry.

All of that changed in June of 2019, when cities like Los Angeles, New York and San Francisco came together with companies like Bird and Microsoft and a consortium of nonprofit organizations called OASIS to form the Open Mobility Foundation (OMF). As chairperson and general manager of the LADOT Seleta Reynolds wrote in Forbes, the OMF platform “helps us achieve important city goals like increasing safety, equity, and health outcomes, while lowering emissions, and reducing congestion.”

These collaborative efforts to manage micromobility systems using open-source code and shared data standards might seem wonky, but they’ve had some very tangible real-world effects. In Atlanta, shared e-scooter data has been used to quadruple the city’s protected bike lanes by 2021. Santa Monica recently used scooter data to draft and pass an amendment that will add 19 new miles of separated micromobility infrastructure.

#5: UK, NY e-scooter programs approved (spring 2020)

This year’s decisions by the UK and the state of New York to legalize shared e-scooters and launch respective pilot programs may not be an innovation, but it’s a crucial development that will ensure the industry tops 500 million rides in 2021.

From an environmental and urban mobility perspective, London and New York are two of the most important cities in the world. Combined, they’re home to 17 million people and more than 10 million daily car trips. The introduction of e-scooters into these two densely packed and highly mobile cities will have a dramatic impact on daily commuter habits, particularly at a time when public transit ridership is still suffering due to COVID-19. That’s good news for cities, citizens and the environment.

The data that will be gained from such a high volume of micromobility rides won’t just help inform infrastructure improvements in New York and London. It will be added to a growing body of research that’s rapidly influencing micromobility technology and accelerating its adoption around the world.

Looking forward

So what can we learn from all of this? What will the first four years and 500 million rides of the shared e-scooter industry tell us about the future of micromobility?

First, we should expect its growth to continue. Adaptable, environmentally friendly solutions to car congestion and urban pollution were in high demand even before the global spread of the coronavirus in 2020. Now they’re proving themselves to be a necessity. Look for the relationships between cities and operators to strengthen and become more cooperative as scooters transition from a perceived recreational vehicle to an essential part of the urban transportation grid. This will include dramatic, data-informed improvements in protected infrastructure for both cyclists and scooter riders.

Second, we should anticipate that e-scooter technology will continue to develop around two key pillars: safety and sustainability. This applies as much to the form and functionality of the vehicles themselves as it does to the daily operations that manage them. Longer lifespan, improved battery performance, increased durability and enhanced diagnostics will be the benchmarks by which we measure this progress.

Finally, we should anticipate that, as the data from hundreds of millions of annual rides continues to accumulate, our understanding of urban mobility needs will become much clearer and more nuanced. Urban planning decisions will be able to be made based on street and hour-specific needs, identifying potentially dangerous areas and taking low-cost, high-impact actions to remedy them.

If current trends continue, and there’s every reason to believe that they will, the time it takes to add another half-billion e-scooter rides to the global total will very soon shrink from four years to less than one.

Squarespace is adding a new monetization option for websites built on the platform: Member Areas, where businesses can charge for access to exclusive content.

Chief Product Officer Paul Gubbay said that particularly in the midst of the pandemic, businesses on Squarespace “want to experiment with different ways to make money.” They can already use the platform to sell products and services, and even to schedule appointments, but with Member Areas, “We allow you to sell your expertise, to sell your content.”

That could, of course, mean an online publication that wants to paywall some of its articles, but it could also mean a chef who wants to charge for access to cooking videos and recipes, or a fitness instructor hoping to make money from online classes.

Group Product Manager Kimberly Lin showed me how Member Areas are integrated into a Squarespace website, allowing the website owner to assign different access requirements to different pages — some could require a recurring membership fee, while others require a one-time payment and still others can be free with registration.

Squarespace also supports different membership tiers, as well as publishing member-only podcasts and newsletters. Site creators get access to CRM data on each of their members, with plans for more segmentation tools in the future.

Squarespace is making this available as an add-on to the core website building platform, with pricing starting at $9 per month. Gubbay emphasized the “simplicity” of adding these features to an existing Squarespace website, making it easy to put “anything you want” behind a paywall.

Lin also said that by integrating with the website builder, Squarespace can offer page protection that’s “truly secure,” because visitors can’t circumvent it by simply tracking down a paywalled URL.

As an early success story, Gubbay mentioned a jewelry merchant on Squarespace who started scheduling sessions where she gives design advice, then created Member Areas with videos and other jewelry-related content.

“First and foremost, we want to make sure we have product-market fit,” Gubbay added. “But I think what we’re going to be interested in doing as we move forward is helping people understand that, guiding them to the parts of the platform where they become a multi-modal seller.”