Hippo has raised $109 million to date, including a $25 million Series B earlier this year. Co-founder and chief executive officer Assaf Wand declined to disclose Hippo’s valuation.
Wand, who co-founded the startup in 2015 with Eyal Navon, said he spent 14 years imagining the technology that would become Hippo, inspired by his father’s career in the antiquated insurance industry.
Hippo co-founder and chief executive officer Assaf Wand.
“I was born into insurance,” Wand told TechCrunch. “Now, the entire real estate ecosystem is changing and the industry is massive. We are getting a crazy good challenge. We think the sky’s the limit with this thing.”
The Mountain View, California-based company officially launched to consumers in 2017. It plans to use its latest investment to fuel the growth of its product, which sells home insurance plans at lower premiums. So far this year, Hippo has expanded into 10 new states and says its sales have grown 30 percent month-over-month since January.
“Hippo has set the bar for the future of insurance with its fully automated, proprietary policy management and proactive underwriting,” Felicis managing director Victoria Treyger said in a statement. “Insurance is the next big sector to undergo the dramatic transformation of customer experience and improved risk management enabled by access to real time data. We see Hippo’s current growth rate and efficient automated policy management system as just the beginning of driving this transformation.”
Treyger will join Hippo’s board of directors as part of the round.
The insurance industry is indeed undergoing a dramatic transformation as a result of technology companies targeting the sector, which are part of a relatively new category of startups dubbed insurtech.
According to PitchBook, insurtech startups have raised nearly $6 billion in venture capital funding since 2012. This year alone, companies in the space have brought in a record amount of capital at $1.8 billion across 94 deals.
Whether or not the hype for the emerging category will continue into 2019 remains to be seen.
Lyft, the transportation on demand company that is heading to a $15 billion IPO in 2019, is racing ahead with its autonomous vehicle plans. TechCrunch has learned that it is acquiring the London-based augmented reality startup Blue Vision Labs and unveiling its first test vehicle with Ford to advance its vision for self-driving cars.
While the integration of Lyft’s autonomous technologies and Ford’s hardware is impressive, perhaps more meaningful is the company’s acquisition of Blue Vision Labs, a startup out of London that has developed a way of ingesting street-level imagery and is using it to build collaborative, interactive augmented reality layers — all by way of basic smartphone cameras.
Blue Vision will sit within Lyft’s Level 5 autonomous car division headed up by Luc Vincent (who joined the company last year as VP of engineering after creating and running Google Street View).
The startup and its staff of 39 (everyone is joining Lyft) will also become the anchor for a new R&D operation in London or the San Francisco-based company, focused on that autonomous driving effort. Level 5 is stepping up a gear in another way today, too: Lyft is unveiling a new vehicle that it will be using for testing.
Blue Vision has developed technology that provides both street level mapping and interactive augmented reality that lets two people see the same virtual objects. The company has already built highly detailed maps that developers can now use to develop collaborative AR experiences — it’s like the maps of these spaces become canvasses for virtual objects to be painted on. Over time, we may see various uses of it throughout the Lyft platform, but for now the main focus is Level 5.
“We are looking forward to focusing Blue Vision’s technology on building the best maps at scale to support our autonomous vehicles, and then localization to support our stacks,” Vincent said in an interview. “This is fundamental to our business. We need good maps and to understand where every passenger and vehicle is. To make our services more efficient and remove friction, we want their tech to drive improvements.”
People familiar with the acquisition tell us Blue Vision was acquired for around $72 million with $30 million on top of that based on hitting certain milestones. Lyft has declined to comment on the valuation. Blue Vision had raised $17 million and had only come out of stealth last March, after working quietly on the product for two years. Investors included GV, Accel, Horizons Ventures, SV Angel and more.
This deal is notable in part because this is the first acquisition that Lyft has made to expand its autonomous car operation, which now has 300 people working on it. At a time when many larger companies are snapping up startups that have developed interesting applications or technologies around areas like AR, mapping, and autonomous driving, there may be more to come. “We are always evaluating build versus buy,” Vincent said when asked about more acquisitions. But he also acknowledged that it is a very crowded field today, even when considering just the most promising companies.
“I don’t have a crystal ball but arguably there are quite a few players today, including big tech, startups, OEMs and car makers. There are well over 100 [strong] companies in the space and there is bound to be some consolidation.” Lyft earlier this year also inked an investment and partnership with Magna to integrate its self-driving car system into components it supplies to car makers.
But it also might face other pressures. The company counts Didi and GM among its investors, and both of these companies are making their own big strides in self-driving technology and each has inked deals to have more partners using that tech, in part to justify some of their own hefty investment.
Lyft, of course, will hope that acquisitions like Blue Vision will give it more leverage, and make it one of the consolidators, rather than the consolidated.
Blue Vision’s use of smartphones to ingest data to create its street-level imagery and mapping is crucial to Lyft’s quest for scale. In effect, every Lyft vehicle in operation today, with a smartphone on the dashboard, could be commandeered to become a “camera” watching, surveying and mapping the roads that those cars drive on, and how humans behave on them, using that to help Lyft’s autonomous vehicle (AV) platform learn more about driving overall.
In the race for data to “teach” these AI systems, having that wide network of cameras deployed and picking up data so quickly is “game changing,” said Peter Ondruska, the co-founder and CEO of Blue Vision.
“The amount of data you have affects how much you can rely on your system,” Ondruska said in an interview. “What our tech allows us to do is to utilise Lyft’s fleet to train the cars. That is really game changing. I was working on this for eight years and you have to have a lot of data to get to the right level of safety. That is hard and we can get there faster using our technology.”
Lyft up to now has really concentrated its business presence in North America, and so this marks at least one kind of way that it is expanding on the other side of the pond. It opened its first European office in Munich earlier this year, a sign that it’s looking to this part of the world at least for R&D, if not to expand its business footprint to consumers, just yet. Vincent declined to comment on whether Lyft would get involved in autonomous trials in London, nor whether it would expand its transportation service there.
Another key area that is worth noting is that Blue Vision’s “collaborative” VR, which lets people look at the same spot in space and both see and create interactive, virtual figures in it, could be used by Lyft either to help drivers and would-be passengers better communicate, or even help passengers discover more services during a journey or at their destination.
Peter Ondruska, the startup’s co-founder and CEO, [said] that Blue Vision’s tech can pinpoint people and other moving objects in a space to within centimeters of their actual location — far more accurate than typical GPS — meaning that it could give better results in apps that require two parties to find each other, such as in a ride-hailing app. (Hands up if you and your Uber driver have ever lost each other before you’ve even stepped foot in the vehicle.)
Blue Vision isn’t the only company working to develop these virtual maps for the world. Startups like 6d.ai, Blippar and the incredibly well capitalized and wildly successful AR technology developer Niantic Labs are also building out these virtual maps on which developers can create applications. Indeed, Niantic’s Pokemon Go game is the most successful augmented reality application to date.
Large media companies have also been investing building content for these platforms, and investors have poured hundreds of millions of dollars into startups like 6d, Niantic, Blue Vision, and others that are building both software and hardware to usher in this new age of how we will, apparently, all soon be seeing the world.
The development of these new platforms will go a long way toward ensuring that more useful applications are just around the corner, waiting for users to pick them up.
“One of the reasons why AR hasn’t really reached mass market adoption is because of the tech that is on the market,” Ondruska told us earlier this year. “Single-user experiences are limiting. We are allowing the next step, letting people see the right place, for example. None of that was possible before in AR because the backend didn’t exist. But by filling in this piece, we are creating new AR use cases, ones that are important and will be used on a daily basis.”
Airwallex, a three-year-old fintech startup focused on international payments for SMEs and businesses, is putting itself on the map after it raised an $80 million Series B round.
Based of out of Melbourne, but with six offices in Asia and other parts of the world, Airwallex’s new funding round is the second largest financing deal for an Australian startup in history. The round was led by existing investors Tencent, the $500 billion Chinese internet giant, and Sequoia China. Other participants included China’s Hillhouse, Horizons Ventures — the fund from Hong Kong’s richest man Li Ka-Shing — Indonesia-based Central Capital Ventura (BCA) and Australia’s Square Peg, a firm from Paul Bassat who took recruitment firm Seek to IPO and is one of Australia’s highest-profile founders.
Airwallex handles cross-border transactions for companies that do business in multiple countries using international currencies. So it’s not unlike a Transferwise-style service for SMEs that lack the capital to develop a sophisticated (and expensive) international banking system of their own.
The service uses wholesale FX rates to route overseas payments back to a client’s domestic bank and is capable of processing “thousands of transactions per second,” according to the company. A use case example might include helping a China-based seller return money earned in the U.S. or Europe via Amazon or other e-commerce services, or route sales revenue back directly from their own website.
Airwallex CEO Jack Zhang (far right) on stage at TechCrunch Shenzhen in 2017
China is a key market for Airwallex — which was started by four Australian-Chinese founders — as well as the wider Asian region, and in particular Australia, Hong Kong and Southeast Asia. With this new capital, Airwallex co-founder and CEO Jack Zhang said the company will increase its focus on Hong Kong and Southeast Asia, whilst also extending its business in Europe (where it has a London-based office) and pushing into North America.
Product R&D is shared across Melbourne and Shanghai, while Hong Kong accounts for business development, compliance and more, Zhang explained. However, Airwallex’s locations in London and San Francisco are likely to account for most of the upcoming headcount growth planned following this funding. Right now, Airwallex has around 100 staff, according to Zhang.
The company is also aiming to expand its product range, too.
The firm is in the process of applying for a virtual banking license in Hong Kong, a third-party payment license in mainland China, and a cross-border Chinese yuan license. One goal, Zhang revealed, is to offer working capital loans to SMEs to help them to scale their businesses to the next level. Airwallex is working with an undisclosed partner to underwrite deals in the future. Zhang explained that the company sees a gap in the market since banks don’t have access to critical data on clients for loan assessments.
More generally, he’s bullish for the future despite Brexit and the ongoing trade war between the U.S. and China.
“The trade war gives the Chinese yuan a lot of vitality, and we’ve seen more demand in the market. China’s belt road initiative has really taken off, too, and we’re seeing the impact in many many of our payment corridors,” he explained. “Business has been booming, especially as traditional offline SMEs start to move online and go from domestic to global.”
“We want to be the backbone to support these new opportunities for businesses,” Zhang added.
There’s a new world of lab-grown replacements coming for everything from the meat department in your grocery store to a department store near you.
Lab-made leather replacements will soon join vegetable-based meat replacements on store shelves thanks to startups like Bolt Threads, which today announced that it would join companies like Modern Meadow in the quest to bring vegetable-based replacements for animal hides to market.
Earlier this year, the Silicon Valley-based Bolt Threads raised a $123 million financing to expand its business beyond the manufacture of spider silk which had brought the company acclaim — and an initial slate of products.
The announcement today of its new product, Mylo, is the first step on that path.
The first bag will be available at the Victoria and Albert Museum’s Fashioned from Nature exhibit, open to the public on April 21st in London.
In an interview with Fast Company last year, McCartney discussed her commitment to sustainability. “I don’t think you should compromise anything for sustainability,” McCartney told the magazine. “The ultimate achievement for me is when someone comes into one of my stores and buys a Falabella bag thinking it’s real leather.”
While Bolt Threads is licensing its technology from Ecovative Design, Modern Meadow is choosing to develop its own intellectual property for growing a replacement leather.
Taking a different path to its California-based competitor, Brooklyn’s Modern Meadow model is going for a mass market while Bolt Threads is more bespoke.
The East Coast company partnered with the European chemical giant Evonik — and has raised over $40 million dollars from billionaire backers like Peter Thiel’s Breakout Ventures and Horizons Ventures (financed by Li Ka Shing — one of China’s wealthiest men) — along with the Singaporean investment giant, Temasek.
Both companies are examples of how animal husbandry is being replaced by technology in the search for a more sustainable way to feed and clothe the world’s growing population. It’s a population that’s demanding quality goods without sacrificing sustainable industrial practices — all things that are made possible by new material — and data — science along with novel manufacturing capabilities that show promise in taking things from the laboratory to the heart of the animal industries they’re looking to replace.
This is a pattern that’s not just happening in fashion, but being replicated in food science as well.
How quickly the change will come — and how viable these alternatives will be — depend on them scaling to meet a broad consumer demand. One purse in a museum show isn’t enough. Once there are hundreds of handbags on Target shelves — that’s when the revolution won’t need to be televised, because it will already have been commercialized.
Big data is an expansive umbrella with startups of all stripes squatting under it. Even as the most successful and powerful data miners of the modern web are undoubtedly the dominant consumer platforms — Google, Facebook, Apple and Amazon in the West, and China’s WeChat in Asia — whose vast digital empires yield them both quantity and quality of data to use as they please.
Yet these tech giants aren’t generally in the business of sharing their data holdings to help others — unless you want to pay them to target digital advertising on your behalf.
Which is where Atomico-backed startup Teralytics spies its own big data opportunity. It’s built a platform selling analytics services to customers such as government agencies and transport companies that want to understand complex problems relating to human mobility — so analyzing things like transport pressure points, or considering the optimum location for a new road, or even monitoring urban air quality without the need to deploy CO2 sensors.
The European startup has been building its analytics platform for around four years at this stage, working in semi stealth up to now to put its core tech in place, while also delivering projects with early partners and customers, such as the air quality monitoring example cited above.
The original idea for the business was spun out of ETH Zurich university, sparked by a conversation one of the co-founders had with a local telco which was looking for help analyzing commuter data on behalf of the government.
Co-founder Georg Polzer says he and his co-founders ended up sleeping in the company’s data center as they worked to write code to come up with the answer to the problem — though he notes he’s past the point of personally pulling coding all-nighters himself now.
“Back at ETH we were doing a lot of data analysis and by living in Zurich, working in Zurich we got exposure to a Swiss telecom company,” he tells TechCrunch. “I got into a conversation with a person there, who mentioned the Swiss government wants to understand how long people travel across the country, to leave their home and reach their destination during the day, and that person at Swisscom said can you help us? And we said sure, we can do it. And with this project we started the company.”
Teraltyics has raised around $44 million to date, telling TechCrunch it’s taken investment up to a Series C level, and amassing a team of 65 people working out of headquarters in Zurich and offices in New York and Singapore. Along with Niklas Zennström’s Atomico fund, investors include Swiss VC firm Lakestar and Hong Kong-based Horizons Ventures.
Its current go-to-market proposition is focused on analyzing human mobility and behavior to meet the changing needs of urban planners and transport providers — sitting under another techie umbrella: smart cities.
“Big cases that we’ve either worked on or are working on include things like how can a large transit network operator minimize the amount of money they spend on operating it whilst at the same time providing a better service to citizens,” says incoming CEO Alastair MacLeod, who brings a background in telcos to help with the startup’s next steps ramping up commercialization of its platform. “We also work with long distance operators on what should their capital plans look like for the next ten years.
“But it’s all centered around… the large topics of what’s happening to urban environments and what’s happening to transportation as new modes of transport come on stream. It’s just a huge and mushrooming area and we play directly into that space, helping inform the current providers on how they could do better. But also helping them think about what comes next.”
Polzer points to disruption already happening in the transport space as ride-hailing providers like Uber push into cities and station-free bike sharing startups like Ofo proliferate. While also noting larger changes looming — such as electric and autonomous cars — which promise to even more radically reshaping urban infrastructure in the coming years.
Cities will need powerful analytics tools to understand and response to these changes, he argues.
“There’s a whole technology shift happening in how we move around, and how we organize cities, and this shift needs to be understood and modeled and designed right — and the right decisions need to be taken,” says Polzer. “And I think we really can play that key role to help shape this wave of change.”
Every single mayor I talk to says can you please help me understand the effect of Uber and Lyft on my city.
“Every single mayor I talk to says can you please help me understand the effect of Uber and Lyft on my city,” he adds. “These are questions they have. It’s very, very much on their minds.”
So — to the really big question — where is Teralytics sourcing the data that powers its platform? How is it able to track city dwellers’ movements in such detail and link them to highly specific behaviors?
In the first instance it’s partnering with telcos whose mobile subscriber bases offer a large, rich, reliable and representative source of population data to be mined for insights, says Polzer, while also looking at bolting on additional data sources as it moves forward (integrating wi-fi network data is something it’s currently working on, for example).
But the really big data crutch here is definitely telcos — who, after tech’s platform giants, hold some of the richest and most detailed data around. Even as they also typically have more stringent regulatory strictures (vs Internet businesses) on what they can do with customers’ sensitive personal data.
And with very good reason — given they provide access to connectivity, not just individual apps and services, affording them a highly intimate overview of their users’ lives.
“The great thing about operator data is that usually in the market there are three to four operators, which always have at least 10 to 15 per cent marketshare. And if you look at other data sources, there’s just no other data sources with that breadth across the population,” says Polzer, discussing the advantage of attaching a big data business to carriers’ heavily loaded pipes.
“Also telcos, are debiased among the population; it’s very nicely distributed — this means you have rich people, poor people, young people, old people. Which makes the extrapolation much much more reliable vs if you just get data from one smartphone app which is used by teenagers in certain areas. So this data is very nicely balanced and therefore can be extrapolated out to the whole population.”
He also talks up the resilience of relying on telcos for the core data-set — given that major network operators are not likely to vanish overnight. Whereas data plays that rely on an app source, for example, might be more vulnerable to passing fads taking them out of business and cutting off the flow of behavioral intel.
Plus he argues that the national constraints of operators help bolster Teralytics against shifts in individual partners’ business decisions — by positioning the business to have additional potential data providers standing by as the nature of the telecoms market necessitates it working with “many operators across different markets”.
The startup has worked with eight different telcos in total up to now, says MacLeod, and has three “active discussions” in new markets, while also flagging a recently signed partnership with Three Hong Kong. Current customers include governments, transportation operators and companies in Germany, Singapore and the U.S. (It’s not disclosing all its carrier partners by name but — for the record — says it’s not currently working with TechCrunch’s parent Oath’s parent Verizon.)
It uses machine learning algorithms to extrapolate insights from its carrier partners’ data-sets — with key data boiling down to location information based on cell tower pings (and wi-fi data incoming), combined with clickstream data from mobile devices, which mean it can derive more granular insights by triangulating which app/website is being used at a given location/velocity — so for example, Teralytics’ platform could identify not just that a group of people are traveling around a city in cars but that they’re traveling in ride-share vehicles.
“The nature of the data is you get a lot of data points per person per day,” says Polzer. “For example, in comparison to app SDK data, you might see a person once or twice a day when that person opens the app. While we see that person, guaranteed, around 150 times a day. When you them look into the use-case we tackle — which is mobility, understanding how humans move around, which routes they take, which mode of transport they take — you need to have that path, that journey of a person. And we believe the only data that really provides that is telecom data.”
“A lot of the reasons why operators work with us is because we exactly have developed an ability to, we call it, extrapolate — so from one sub-set of the population we extrapolate out to the whole population,” he adds.
“You don’t necessarily know this individual person did that individual thing, but when you’re talking about it in terms of groups — which we do anyway for privacy reasons — you can infer patterns of behavior around how many did this sort of thing, or how many took a ride-share, which we may or may not identify by an individual brand, vs how many took some other mode of transport. But it all effectively comes from different types of data being overlaid in a fairly sophisticated machine learning engine,” says MacLeod.
Teralytics CEO, Alastair MacLeod, and co-founder Gerog Polzer
Balancing privacy concerns is clearly going to be a critical consideration for the success of the venture — which needs telcos to buy in to pump in the big data fuel, and therefore also needs their customers be comfortable with the idea that their personal data — i.e. information about where they go and what they do online — might be being shared with, for example, government agencies.
So even if you start from the premise of carrier data being anonymized, as Teralytics says is the case here, a system could be built that tracks an unnamed user’s location and displays a trace from a street address to a commercial address and back again twice a day, for example, and the person looking at that data might easily infer they’re seeing a person’s home and workplace — and then it’s potentially very easy to re-identify that individual.
However, Teralytics claims no such re-identification risks are attached to its system because of how it’s baked privacy considerations into the design. Polzer says it’s using a variety of proprietary techniques to handle the data in a way that preserves user privacy — although he won’t go into too much detail, claiming commercial sensitivity. But says the system has passed muster with strict German data protection watchdogs, and expresses confidence it’s robust enough for any data protection regime.
One key aspect is that as well as anonymizing the data they also claim they are never linking data traces to individual identities — rather they only provide analyses based on aggregation of groups’ movements and habits. They also perform analysis of the data on site, behind carriers’ firewalls, to reduce potential security risks — so they’re not lifting subscriber data elsewhere for processing.
“We are already fully compliant with GDPR,” says MacLeod, referencing the incoming European Union data protection regulation that’s bringing in new privacy requirements for companies handling EU citizens’ personal data, as well as ramping up penalties for privacy violations.
“As an extra measure in Germany we are rehashing every 24 hours. But of course you still want to do long term profiles so we have developed a technique to actually still do that and be compliant and getting approval by the Germany privacy regulator for that,” adds Polzer.
Clearly the hope is that their approach has been sensitive enough and robust enough to entirely defang any privacy concerns, regulatory or otherwise, though a lot may depend on the perception of the mobile subscribers’ whose data is ultimately fueling these commercial insights. (Which may be why the initial go-to-market strategy is focused on a goal that can be perceived as socially beneficial — after all, which good citizens doesn’t want to live in a ‘smarter’ city?)
In the case of Telefonica Germany, one partner Teralytics will name, Polzer says the carrier is providing an opt-out for users who do not want even anonymized details about how and where they travel and which apps and mobile websites they’re looking at, to be used for third party analytics.
Though clearly not every carrier it works with might decide to offer the same choice to its subscribers.
“Of course there are some slightly relaxed rules [in some telco jurisdictions],” concedes Polzer. “On the other hand we need to invest in developing an algorithm that works outside Germany… We can’t afford building a new algorithm for every single country. And also, to be frank, we very much view GDPR as the future — we expect every regulator to, in the end, move in that direction anyway. So I don’t think we’re building a business that hopes for loopholes or depends on loopholes.”
“We build the same privacy standard into the solutions we build, regardless of what the law does or doesn’t require in that country,” adds MacLeod.
Doing advertising in an opt-out way — we don’t think that’s really sustainable in the long term.
Zooming out, to consider the telcos themselves, why do they need Teralytics? MacLeod demurs on this question, saying its partners don’t “need” it — given they do have their own in-house analytics teams — but rather the sales pitch is around strategic focus; with telcos being most concerned about optimizing their own business processes, whereas Teralytics can offer itself as the “young, fast, flexible” startup partner which can be out in the market selling services to third parties to make more of carriers’ data holdings, as well as also supporting them to drive more of their own core revenue if they wish.
The basic business model is a revenue share with carrier partners on any third party analytics deals Teralytics (or the two combined) are able to cut — though MacLeod won’t go into specifics, beyond billing the proposition as a “low cost, low risk, easy way into big data analytics” for telcos to eke more value out of their data holdings.
Polzer also points to the market constraints of telcos as a helper here — noting this characteristic means they’re not well-positioned to recoup the kind of investment needed to build a comparable machine learning analytics platform. Whereas Teralytics can invest because it can play and (it hopes) scale across multiple markets.
“A lot of the partners we’ve got now and some of the ones we’re talking to now they fundamentally believe that data is the new gold and it’s going to be the new currency,” says MacLeod. “We have value to add because we’re really good at what we do and it’s hard, especially when you consider not only the complexity of the machine learning that has to go into providing these insights, but… the privacy — this isn’t something that you can just go hire a bunch of data scientists off the streets and do it.”
Of course one market that some telcos are demonstrably very keen on expanding into, based on how much they can infer about their customers, is digital advertising.
Just this week U.S. carrier Verizon, for example, announced a rewards program for its subscribers that requires them to agree to share personal data (such as their browsing habits) with its digital ad division, so expressly for marketing purposes, in exchange for the ability to earn loyalty rewards. Ergo, it’s gunning to build up an ad targeting empire — a la Google and Facebook. (And for that reason recently spent big to gobble up veteran digital ad player, Yahoo.)
So is helping carriers enhance their ability to target ads at their users something that Teralytics wants to do too?
“At the moment it’s not the focus,” says Polzer, after a slight hesitation. “Of course we are getting approached by operators about this topic, but at the moment it’s definitely not the focus.”
“And in most of the territories we operate in it’s not allowed anyway, so it’s relatively straightforward,” adds MacLeod.
Might the startup look at moving into that line of business in future — if/where regulatory conditions are favorable? “Our focus for the business is clear and it’s not that,” returns MacLeod. “The guys started out, long before I turned up, wanting to uncover insights into human behavior. And even though I’m here now, and I’m the commercialization guy, and we’re looking at other sources of data besides telco data, the intention is to build on that. We see lots of interesting big scale trends in terms of how people move around differently, how people live differently… There’s so much huge interesting stuff emerging from that that’s why we’ve placed the focus on smart cities and transportation, and the intersection of it.”
“I’d never say never to anything but I can tell you with absolute certainty it’s not our focus,” he adds. “We are privacy by design throughout so whatever we do we’ll never go anywhere near anything that breaches people’s privacy because it’s literally built into the fabric of the company.”
“Doing advertising in an opt-out way — we don’t think that’s really sustainable in the long term,” continues Polzer, when I press on how interested telcos are in growing digital advertising businesses, going on to suggest that the point at which Teralytics might apply its platform to a digital advertising use-case would be “if telco operators are able to build a meaningful opt-in base” (i.e. for individually targeted marketing).
“Which we haven’t seen in any market yet,” he adds. “I do hope and wish all the telcos luck and success in making this transformation. But I think they would have to build up a meaningful opt-in base for us to play a role there. But once they’re ready, I think we are probably the best providers of human mobility data.”
One of Teralytics’ ongoing partner conversations is “specifically about an opt-in case”, adds MacLeod. “So we’re looking at this, it’s very early stage for us. We haven’t decided to work with the partner at all — let alone whether we want to participate with that case. But for me the concerns go away around why not to do it if everybody who’s potentially is going to be targeted by a solution has positively said yes I would like to be. Rather than they haven’t got around to saying that they wouldn’t like to be.”
Whatever the outcome of that particular carrier conversation, right now, the business goal for the team at this stage of business development — several years in, with multi millions raised and what it’s pitching as a solid platform under its feet to get carriers to jump on board — is accelerating commercialization. The plan is to dial up sales and customer acquisition by building out the commercial team and putting its energy into front office ops for the coming year. Aka “it’s time to really ramp this thing,” as MacLeod puts it.
“In the next 12 months our plans are to accelerate in the markets that we have — so we’re active now in four markets already, as in we’ve got four significant live partners in the US, in Germany, in Singapore and in Hong Kong,” he says. “We are actively talking to partners that would give us either two or three territories so we will increase the geographical footprint because the platform itself is so replicable and so scalable and the way that they’ve built it, even though the nature of our relationship is slightly different it’s… not very far away from plug and play. From the day that we decide to do it it’s two or three weeks until we can be live with some insights in any market.”
“A big chunk of our platform is highly productized,” adds Polzer. “We are very flexible in the way of extracting number of subway trips vs number of car trips. One customer might come with a question: ‘how often do people take the train?’ — another customer say: ‘what happens if I reconstruct a bridge?’ and for us these might be different customer questions but the underlying analysis is the same.”
The underlying question for Teralytics’ big data play is what will mobile users say? Will they feel comfortable if their carrier decides to track and analyze their personal data for commercial gain? Providing a stable and reliably affirmative answer there may prove to be this startup’s biggest challenge.