Glossier launches its first spin-off brand, a line of Instagram-friendly ‘dialed-up’ beauty extras

Glossier, known for its line of understated makeup products and a cult-following of millennial Instagrammers, is getting colorful with the launch of its first spin-off brand, Glossier Play.

The company — led by founder and chief executive officer Emily Weiss, who built the nearly $400 million business from a makeup blog called Into The Gloss — has raised a total of $92 million in venture capital funding from top-tier consumer investors Forerunner Ventures, Index Ventures and IVP. Stitch Fix founder Katrina Lake and Forerunner founder and general partner Kirsten Green, are among the company’s board members.

Weiss introduced Glossier in 2014 as a clean-skincare and natural beauty advocate. Today, the direct-to-consumer business boasts a growing line of barely there makeup, designed to mimic Weiss’s own subtle, au naturale vibe. The launch of Glossier Play, inspired by 1970s’ nostalgia, is its first foray into bright colors, glitter and, in the brand’s own words, “dialed-up extras.”

Glossier Play’s initial line-up of “extras” includes colored eyeliners ($15), highlighters ($20), multi-purpose glitter gel ($14) and the “Vinylic Lip” ($16). Customers can purchase “The Playground,” a set that includes each of the new products, for $60.

The advertising campaign for the Instagram -friendly line will be led by none other than Instagram star Donté Colley, as well as pop musician Troye Sivan. The new line and future spin-offs will help Glossier compete with beauty incumbents, Estée Lauder and L’Oréal, for example, in a market estimated to be worth $750 billion by 2024.

Glossier, headquartered in New York, counts 200 employees, meager in comparison to its nearly 2 million — and growing — social media following. The company surpassed $100 million in annual revenue in 2018, it tells TechCrunch, and acquired 1 million new customers. In total, Glossier retails 29 products across skincare, makeup, body, and fragrance.

The company won’t be introducing additional brands this year and clarified it is not a brand incubator.

Galaxy S10 takes the ‘best smartphone display’ crown

As you may have gathered from our review of Samsung’s Galaxy S10, it’s a very solid phone with lots of advanced features. But one thing that’s especially difficult to test is the absolute quality of the display — which is why we leave that part to the experts. And this expert says the S10’s screen is the best ever on a smartphone.

Ray Soneira has tested every major phone, tablet and laptop series for many a year, using all the cool color calibration, reflectance and brightness measurement and other gear that goes with the job. So when he says the S10’s display is “absolutely stunning and Beautiful,” with a capital B at that, it’s worth taking note.

OLED technology has advanced a great deal since the first one I encountered, on the Zune HD — which still works and looks great, by the way, thank you. But originally it had quite a few trade-offs compared with LCD panels, such as weird color casts or pixel layout issues. Samsung has progressed well beyond that and OLED has come into its own with a vengeance. As Ray puts it:

The Absolute Color Accuracy on the Galaxy S10 is the Most Color Accurate Display we have ever measured. It is Visually Indistinguishable From Perfect, and almost certainly considerably better than your existing Smartphone, living room HDTV, Tablet, Laptop, and computer monitor, as demonstrated in our extensive Absolute Color Accuracy Lab Measurements.

The very challenging set of DisplayMate Test and Calibration Photos that we use to evaluate picture quality looked absolutely stunning and Beautiful, even to my experienced hyper-critical eyes.

Make sure you switch the phone’s display to “natural mode,” which makes subtle changes to the color space depending on the content and ambient light.

And although he has enthused many times before about the quality of various displays and the advances they made over their predecessors, the above is certainly very different language from, for example, how he described the reigning champ until today — the iPhone X:

Apple has produced an impressive Smartphone display with excellent performance and accuracy, which we cover in extensive detail below. What makes the iPhone X the Best Smartphone Display is the impressive Precision Display Calibration Apple developed, which transforms the OLED hardware into a superbly accurate, high performance, and gorgeous display, with close to Text Book Perfect Calibration and Performance!!

High praise, but not quite falling all over himself, as he did with the S10. As you can see, I rate smartphone displays chiefly by the emotional response they evoke from Ray Soneira.

At this point, naturally, the gains from improving displays are fairly few, because, to be honest, not many people care or can even tell today’s flagship displays apart. But little touches like front and back sensors for ambient light detection, automatic calibration and brightness that take user preferences into account — these also improve the experience, and phone makers have been adding them at a good clip, as well.

No matter which flagship phone you buy today, it’s going to have a fantastic camera and screen — but if you like to see it all in black and white, read through the review and you’ll find your hopes justified.

Outdoor Tech’s Chips ski helmet speakers are a hot mess of security flaws

Sometimes the “smartest” gadgets come with the shoddiest security.

Alan Monie, a security researcher at U.K. cybersecurity firm Pen Test Partners, bought and tested a pair of Chips 2.0 wireless speakers, built by California-based Outdoor Tech, only to find they’re a security nightmare.

The in-helmet speakers allow users to listen to music on the go, make calls and talk to friends through the walkie-talkie — all without having to take off their helmet. The speakers are connected to an app on your phone.

You’re probably thinking: how bad can the security be on a simple-enough ski-helmet speakers?

According to Monie, who wrote up his findings, it’s easy to grab streams of data from the server-side API, used to communicate with the app, such as usernames, email addresses and phone numbers of anyone with an account. Monie said the API returned scrambled passwords, but that password reset codes were sent in plaintext.

Worse, it’s possible to reveal a user’s precise geolocation, and listen in on anyone’s real-time walkie-talkie conversations.

The only thing worse than the security flaws are the company’s lack of response when Monie reached out to get the issues fixed. After a short email exchange over several days, the company stopped responding, he said.

“We really like the product but its security is sorely lacking,” said Monie in his report.

It’s the latest example of many where gadget makers take little to no responsibility for the security of their hardware or software. With so many devices connected to the internet — either directly or through an app — every company has to think like a security company.

Outdoor Tech did not return a request for comment.

Can predictive analytics be made safe for humans?

Massive-scale predictive analytics is a relatively new phenomenon, one that challenges both decades of law as well as consumer thinking about privacy.

As a technology, it may well save thousands of lives in applications like predictive medicine, but if it isn’t used carefully, it may prevent thousands from getting loans, for instance, if an underwriting algorithm is biased against certain users.

I chatted with Dennis Hirsch a few weeks ago about the challenges posed by this new data economy. Hirsch is a professor of law at Ohio State and head of its Program on Data and Governance. He’s also affiliated with the university’s Risk Institute.

“Data ethics is the new form of risk mitigation for the algorithmic economy,” he said. In a post-Cambridge Analytica world, every company has to assess what data it has on its customers and mitigate the risk of harm. How to do that, though, is at the cutting edge of the new field of data governance, which investigates the processes and policies through which organizations manage their data.

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“Traditional privacy regulation asks whether you gave someone notice and given them a choice,” he explains. That principle is the bedrock for Europe’s GDPR law, and for the patchwork of laws in the U.S. that protect privacy. It’s based around the simplistic idea that a datum — such as a customer’s address — shouldn’t be shared with, say, a marketer without that user’s knowledge. Privacy is about protecting the address book, so to speak.

The rise of “predictive analytics,” though, has completely demolished such privacy legislation. Predictive analytics is a fuzzy term, but essentially means interpreting raw data and drawing new conclusions through inference. This is the story of the famous Target data crisis, where the retailer recommended pregnancy-related goods to women who had certain patterns of purchases. As Charles Duhigg explained at the time:

Many shoppers purchase soap and cotton balls, but when someone suddenly starts buying lots of scent-free soap and extra-big bags of cotton balls, in addition to hand sanitizers and washcloths, it signals they could be getting close to their delivery date.

Predictive analytics is difficult to predict. Hirsch says “I don’t think any of us are going to be intelligent enough to understand predictive analytics.” Talking about customers, he said “They give up their surface items — like cotton balls and unscented body lotion — they know they are sharing that, but they don’t know they are giving up their pregnancy status. … People are not going to know how to protect themselves because they can’t know what can be inferred from their surface data.”

In other words, the scale of those predictions completely undermines notice and consent.

Even though the law hasn’t caught up to this exponentially more challenging problem, companies themselves seem to be responding in the wake of Target and Facebook’s very public scandals. “What we are hearing is that we don’t want to put our customers at risk,” Hirsch explained. “They understand that this predictive technology gives them really awesome power and they can do a lot of good with it, but they can also hurt people with it.” The key actors here are corporate chief privacy officers, a role that has cropped up in recent years to mitigate some of these challenges.

Hirsch is spending significant time trying to build new governance strategies to allow companies to use predictive analytics in an ethical way, so that “we can achieve and enjoy its benefits without having to bear these costs from it.” He’s focused on four areas: privacy, manipulation, bias and procedural unfairness. “We are going to set out principles on what is ethical and and what is not,” he said.

Much of that focus has been on how to help regulators build policies that can manage predictive analytics. Because people can’t understand the extent that inferences can be made with their data, “I think a much better regulatory approach is to have someone who does understand, ideally some sort of regulator, who can draw some lines.” Hirsch has been researching how the FTC’s Unfairness Authority may be a path forward for getting such policies into practice.

He analogized this to the Food and Drug Administration. “We have no ability to assess the risks of a given drug [so] we give it to an expert agency and allow them to assess it,” he said. “That’s the kind of regulation that we need.”

Hirsch overall has a balanced perspective on the risks and rewards here. He wants analytics to be “more socially acceptable,” but at the same time, sees the needs for careful scrutiny and oversight to ensure that consumers are protected. Ultimately, he sees that as incredibly beneficial to companies that can take the value out of this tech without risking provoking consumer ire.

Who will steal your data more: China or America?

The Huawei logo is seen in the center of Warsaw, Poland

Jaap Arriens/NurPhoto via Getty Images

Talking about data ethics, Europe is in the middle of a superpower pincer. China’s telecom giant Huawei has made expansion on the continent a major priority, while the United States has been sending delegation after delegation to convince its Western allies to reject Chinese equipment. The dilemma was quite visible last week at MWC Barcelona, where the two sides each tried to make their case.

It’s been years since the Snowden revelations showed that the United States was operating an enormous eavesdropping infrastructure targeting countries throughout the world, including across Europe. Huawei has reiterated its stance that it does not steal information from its equipment, and has repeated its demands that the Trump administration provide public proof of flaws in its security.

There is an abundance of moral relativism here, but I see this as increasingly a litmus test of the West on China. China has not hidden its ambitions to take a prime role in East Asia, nor has it hidden its intentions to build a massive surveillance network over its own people or to influence the media overseas.

Those tactics, though, are straight out of the American playbook, which lost its moral legitimacy over the past two decades from some combination of the Iraq War, Snowden, WikiLeaks and other public scandals that have undermined trust in the country overseas.

Security and privacy might have been a competitive advantage for American products over their Chinese counterparts, but that advantage has been weakened for many countries to near zero. We are increasingly going to see countries choose a mix of Chinese and American equipment in sensitive applications, if only to ensure that if one country is going to steal their data, it might as well be balanced.

Things that seem interesting that I haven’t read yet

Obsessions

  • Perhaps some more challenges around data usage and algorithmic accountability
  • We have a bit of a theme around emerging markets, macroeconomics and the next set of users to join the internet
  • More discussion of megaprojects, infrastructure and “why can’t we build things?”

Thanks

To every member of Extra Crunch: thank you. You allow us to get off the ad-laden media churn conveyor belt and spend quality time on amazing ideas, people and companies. If I can ever be of assistance, hit reply, or send an email to danny@techcrunch.com.

This newsletter is written with the assistance of Arman Tabatabai from New York.

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Shift Technology raises $60 million to detect insurance fraud

Paris-based Shift Technology has raised another $60 million funding round. Bessemer Venture Partners is leading the round and existing investors Accel, General Catalyst, Iris Capital and Elaia Partners are also participating.

Shift Technology is all about detecting fraudulent insurance claims. There are 70 insurance companies around the world relying on its product, such as MACIF in France, Axa in Spain, and CNA and HyreCar in the U.S. And given the size of those companies, it means that Shift Technology is processing a ton of claims every day.

It’s easy to sell this kind of product, as fraudulent claims cost a ton of money. If Shift Technology can help you catch more fraudulent claims, you can spend a bit of money to save a lot of money.

The startup has already grown quite a lot since its previous funding round. They now have 200 employees, and customers all around the globe. In addition to its headquarters in Paris, Shift Technology also has offices in Boston, London, Hong Kong, Madrid, Singapore and Zurich.

With today’s funding round, the company plans to hire more people in Boston, including data scientists and developers. The company is also playing around with an automated claim-processing solution.

Shift Technology is creating a strong barrier to entry. Thanks to its huge data set, it can create an AI-powered detection model that is getting more and more accurate. A new company would have a hard time catching up.