Smart Money Says Lyft a Winner in Autonomy

Ridesharing, more specifically, the fate of Uber and Lyft, is at the top of the potentially disrupted list as autonomy approaches. Both of these companies will need to make the leap to autonomy whether it be organically, through acquisition, or by partnership. simply put these companies must adopt autonomy to survive. Recent news of CapitalG leading a $1B investment in Lyft is a key endorsement that Lyft will have a future in an autonomous world as the platform for on-demand self-driving vehicles. Uber’s fate, however, appears more in its own hands, given it is developing its own autonomous systems, and the partnerships that Uber has inked to date tend to be on the manufacturing side (Daimler, Volvo, Tata, and Toyota). While Uber is still in the running, our money is also on Lyft.

CapitalG, Alphabet’s late-stage venture fund, has not disclosed how much of the round they account for. Despite a CapitalG spokesman saying otherwise, this investment is about much more than making a profit for Alphabet. As Google navigates the impossibly complex landscape of companies vying for leadership in ridesharing and autonomy, they are making sure they have a strong presence in each possible outcome of the booming technology.

GV, another venture arm of Alphabet that invests in much younger companies, made a $258M investment in Uber in 2013 predating the Waymo IP theft allegations). On top investments in of both ride-sharing giants, Alphabet’s own Waymo is largely considered a leader in self-driving systems. We see this strategic investment as a strong confirmation of Google’s conviction in the future of self-driving cars, and the concept of fleet services. In our Auto Outlook, we detail the rise of both autonomous vehicles and fleet ownership, predicting fully autonomous cars to outnumber drivers and cars owned by fleet services to outnumber personally owned cars in 2036.

The investment brings Lyft’s valuation north of $11B, almost 50% higher than last round. While Lyft remains roughly 1/7th the size of Uber, a large influx of cash should strengthen their competitive efforts, allowing them to expand internationally, and to build out their platform for self-driving cars. While Lyft does not have any aspirations of developing their own autonomous systems, they have positioned themselves as the platform for on-demand autonomous cars in the near future. With Lyft’s open platform, automakers can plug self-driving cars in to a network of drivers that make nearly 1 million rides per day (growing at 25% per year), and smooth the transition to full autonomy with a Lyft “driver” behind the wheel. While Uber, who hopes to develop self-driving technology in-house, is embroiled in legal battles, Lyft has made countless partnerships with both automakers and self-driving tech companies. Their list now extends to Waymo, NuTonomy, Drive.ai., Ford, GM, and Jaguar. The next chapter in the race to autonomy will likely be a Lyft IPO. Stay tuned.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

iRobot to Play Leadership Role in Home Robotics Space: Introducing 5-Yr Model

Special thanks to Austin Bohlig for his work on this note. 

Today we’re rolling out our iRobot 5-year model, joining Loup Ventures’ Apple and Tesla model coverage. We feel it’s important to write on iRobot even though it’s a small company, $2.1 billion market cap, because iRobot will likely play a leadership role in the evolution of the home robotics space over the next decade.

Due to advancements in robot functionalities and lower costs, robots are quickly becoming a common technology in our homes. These domestic robots are systems used to perform household chores such as vacuuming, mopping, and mowing the lawn. While home robot adoption has accelerated in recent years, penetration rates remain low and we foresee the highest growth still to come.

Leading the domestic robot charge is iRobot (IRBT), which is the industry leader in robotic vacuums and wet floor (aka mops) products. Driven by iRobot’s robust robotic engineering expertise, as well as brand awareness, we believe iRobot will be the leading provider of home robot technology for the next several years. Given iRobot’s leadership in robotics, a space we spend a lot of time working on, we’ve developed a 5-year model for the company (here).

Domestic Robot Market Inflecting

We estimate that 5.0M domestic robots were sold in 2016, which is up 24% from the prior year, and the total market value grew 23% to $1.4B. While iRobot does not compete in all domestic robot categories, they do lead the largest (vacuums) and fastest growing (wet floor) markets. The robotic vacuum market accounts for the largest percentage (70%) of domestic robot spend. In 2016, 4.1M robotic vacuums were sold, up 18% year/year, and the market value grew by 20% over that same time to ~$940M. The faster sales growth was driven by faster growth among higher-end systems. The global robotic vacuum market has grown ~18% per year since 2012, but only accounted for ~21% of total vacuum spend in 2016. Given penetration rates remain low, we believe there is plenty of room for multiple double-digit years of growth to come.

Consumer awareness for robotics is increasing, and as households begin to adopt this technology they are becoming more comfortable with other forms of robotics, such as wet floor products and lawnmowers. While both these markets only account for 5% and 25% of domestic spend, respectively, both are expected to see 20%+ annual growth through 2025. Over the next 10 years we anticipate the entire industry to see double-digit unit growth annually, and by 2025 believe 26.5M domestic robots will be sold, which will equate to a $5.7B market opportunity. See our domestic macro model here. While iRobot is well positioned in the vacuum and wet floor markets, we believe the company’s industry leading robotics expertise will unlock for them opportunities in other domestic markets.

iRobot’s Dominance Puts Them In a League of Their Own

To date, iRobot primarily competes in the robotic vacuum and wet floor sub-categories; however, as shown in the graph below, they control 60%+ share in each of these markets. Over the last couple of years, increased competition has been the biggest risk to iRobot’s robot vacuum business (which accounts for ~90% of all home robot sales) with companies such as Dyson, Samsung, Ecovacs, and Shark Ninja entering the market. Yet, iRobot continues to exceed expectations and experience strong revenue growth over the last several quarters. As we highlighted in a note following the company’s Q2 results, we believe the company’s continued success shows the perceived threat from competition is overblown and, more importantly, indicates that developing a highly functioning robot is difficult.

Furthermore, the competition is targeting the sub-$500 robotic vacuum market, but as the industry data above shows, consumers are shifting towards iRobot’s higher-end Roomba 900 series products, which retail for $700 – 900. We believe iRobot has established themselves as the go-to premium robotic vacuum brand. Competitors will likely struggle to compete in this area of the market. More competition may even be a net positive for iRobot because it will continue to increase consumer awareness. Given all domestic robot markets are significantly under penetrated there is plenty of room for more than 1 robot company to flourish. While iRobot has not yet seen the increased competition in the wet floor market, we do anticipate more players to enter the space as the market opportunity grows. Similar to the vacuum space, we anticipate iRobot will maintain its leading position.

Many New Products To Come – Robotic Lawnmower in 2018 Likely

Since iRobot sold off their defense business in 2016, the company has been fully focused on bringing automation to the home. In the near term, we anticipate iRobot will continue to introduce new Roomba and Braava products that improve on performance, battery life and other unique features, such as Wi-Fi capabilities. However, iRobot is one of the most innovative robotic companies in the world, and we believe there technology is transferable across several robot domains.

We expect iRobot to introduce a robotic lawnmower in 2018. While the company has not disclosed when the product could be available, they have indicated they are pursing it. We believe iRobot will hint at introducing a lawnmower over the next two earnings call, and introduce a robot lawnmower in the Spring of 2018. This is not an “if”, but more of a “when” they will introduce a robotic lawnmower; if not in 2018, a 2019 launch is very likely. Due to the average North American lawn being too large for a robotic lawnmower to cut efficiently, iRobot will likely target Europe and APAC countries for which the technology is better suited.

5 Year Outlook

We expect iRobot to ship 3.5M total units in 2017, which is up 22% over the prior year. We expect 3.1M or ~85% of units sold will be Roomba vacuum cleaners, which is an acceleration of 19% from the previous year. While the remaining ~15% will be in the form of Braava products, this category is beginning to see meaningful momentum as the company continues to contribute higher marketing dollars around this product line. We believe the company will sell ~464k wet floor products in 2017, which is up 50% year/year. Looking longer term, we believe both Roomba and Braava categories will see robust growth over the next several years. Driving catalyst in both categories will be increase consumer awareness and strong robot adoption in both domestic and international markets. Furthermore, we believe the company will introduce a robotic lawn mower in 2018. While it will take time for this category to be material to the story, eventually it will be another positive tailwind. As it relates to the P&L, we believe the company will see 20%+ revenue growth through 2020, due to strong demand for many products across the company’s portfolio. However, we believe iRobot will continue to see stronger demand for their high-end systems, which will drive ASPs modestly higher through 2019. This coupled with modest operating leverage, iRobot will experience 25%+ operating income growth through 2022.

Bottom Line

We believe that adoption of robots within in the home is quickly approaching an inflection point as more consumers are looking to automate daily household chores such as vacuuming, sweeping, mopping, as well as mowing the lawn. Driven by iRobot’s robust technology expertise and strong brand awareness, we anticipate iRobot will be the leading provider of home robot technology for the next several years.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

The Rise of B2C CRM & Personalization: Retailers Combat Convenience

Written by guest author Carlos Castelan, Chief Strategy Officer at Conlego. 

In The Future of Retail, Loup Ventures laid out a vision for the future of retail amidst the continuing consumer shift from offline retail shopping to online.  To combat the shift towards pure convenience, and provide an enhanced in-store customer experience, retailers have started implementing business-to-consumer (B2C) customer-relationship management (CRM) programs to more effectively tailor product offers and services to its customers and drive traffic to their brick-and-mortar locations.

Traditionally, CRM systems and programs were utilized by large companies to manage sales cycles into other businesses (B2B sales).  However, retailers and consumer-focused companies have started to adopt the technology to better understand purchasing habits and interactions to improve customer engagement.  At some retailers, this personalization and data-capture is taking place through loyalty programs or branded credit cards but others are expanding these programs to better serve customers daily through a complete purchase profile.

A great example of CRM in the form of a loyalty program is Nordstrom’s which expanded its loyalty program in 2016 to include all customers (i.e. non-credit card holders).  Loyalty members earn points towards vouchers so long as they provide their phone number – which acts as their ID number.  With a profile and Guest ID/phone number, associates can easily view a guest’s purchase history so, for example, a customer can easily make a return without a receipt or associates can identify the customer’s size in a brand (if they purchased that brand before).  It’s not hard to imagine a future state where there’s a rich database the company can pull from to deploy evolving artificial intelligence (AI) and, at a meta-level, better predict buying trends and, on a personalized level, understand when its best customers walk into their stores and how to best cater to them.

These CRM programs and personalization are rapidly expanding, particularly among higher end retailers that focus on high-touch customer service.  A recent example of a company that is implementing a CRM system is lululemon athletica.  As laid out by one of its executives, Gregory Themelis, lululemon seeks to better understand the engagement consumers have with their brand across three levels: transactions, sweat, and engagement.  In this sense, lululemon is seeking a more holistic understanding of the customer (vs. just understanding sales/transactions).  Through data and being “informed” by it (vs. being driven by data), lululemon will be able to better engage customers by tailoring the right level of personalization along with creating seamless marketing across all channels.  lululemon is taking a much more brand-oriented approach to drive customer engagement through a personalized one-on-one experience to build a community.  In the CRM and personalization model, it’s easy to understand how a retailer, such as lululemon, could add more value to its customers in the future by sharing personalized suggestions (workouts, restaurants, etc.) to drive brand affinity and subsequently drive traffic and sales.

Whether it be through the implementation of loyalty programs or pure CRM, personalization is a concept that retailers and consumer brands are adopting to drive traffic to their locations and enhance the customer experience.  In a world that has come to value convenience, personalization and high-touch service is a way for these companies to continue to differentiate themselves and, in the future, use AI to predict customer behavior and serve them even more effectively.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Don’t Underestimate the Importance of 3D Mapping for Autonomy

As you drive down the road, you make countless subconscious micro-decisions and calculations built on past experience. You know what 40 mph feels like by observing how fast the trees are passing by, how hard you can hit the brakes to comfortably slow down at a traffic signal, and that you should coast down a steep hill to avoid speeding. Even if you are on an unfamiliar road, driving experience has built foundational expectations and awareness, so that you are not hurdling into the unknown waiting to react to situations that arise. In the case of autonomous vehicles, however, these decisions are made by software. Simply adding sensors like LiDAR and cameras to a vehicle allow it to perceive its surroundings, but, on their own, would fail to enable a safe ride. Enter 3D maps – a critical element of autonomy that is often overlooked.

Detailed, 3-dimensional, continuously updated maps are essential to true widespread adoption of self-driving cars. This is what separates a system that needs to be overseen by a human focused on the road, and one where you can fall asleep and wake up at your destination. While it is technically possible for a car to navigate an unfamiliar setting without a digital map, the information that 3D maps provide is critical to building the trust necessary for widespread adoption of autonomy. Maps effectively teach a self-driving vehicle the rules of the road. The car’s AI can learn the mechanics of driving like a human, but the map introduces things like bike and HOV lanes, speed limits, construction zones, train tracks, and pedestrian crosswalks. Maps also ease the burden on the car’s computers by giving them foresight and adding redundancy to its understanding of the situation it faces.

Civil Maps CEO, Sravan Puttagunta explains, “Radar and cameras cannot always recognize a stop sign if pedestrians are standing in the way or the sign has been knocked down. But if the map knows there is a stop sign ahead, and the sensors just need to confirm it, the load on the sensors and processor is much lower.”

Reducing the load on the car’s computing power must be considered, because a fully autonomous vehicle could produce as much as a gigabyte of data every second. By building an accurate and up-to-date, digital representation of the world around us, a car is able to process this data in conjunction with the data created by its sensors to create a safer, smoother, and more reliable driving experience. Maps allow a vehicle to see into the future – further than human drivers can see – anticipating instead of reacting to changes in their environment.

Maps allow a vehicle to see into the future – further than human drivers can see – anticipating instead of reacting to changes in their environment.

Maps are an important aspect of vehicle-to-vehicle (V2V) communication as well. Using maps as an extension of a car’s sensors requires a reliance on other cars for input information. This presents us with the consortium conundrum that we wrote about here. In the realm of V2V communication, where it does no good to ‘out-communicate’ the competition, we believe company collaboration would be beneficial, if not a requirement. Maps that are shared through a single cloud-based platform are updated frequently, adding exponentially to their utility. The minute details of roads are constantly changing – construction zones, fallen trees, or damaged roads are all things that must be mapped and updated to reflect current conditions. This can be accomplished using the cameras and sensors on each car including some element of automated Waze-like crowd sourcing from the vehicles, too. As a vehicle drives, its sensors are constantly comparing their inputs to the map. When a discrepancy is detected, it is corroborated by other vehicles and changed in the cloud, so every car in the network is up-to-date. Take, for example, the scenario pictured below.

Here, there are three layers of safety that come from V2V and mapping. As the black car drives by the wreck, it observes a discrepancy in its map and relays that message. The cars involved in the accident share their location and that their speed is zero, and the car blindly approaching the wreck knows to avoid its current lane and switches lanes accordingly. Sensors alone, which have limited range and therefore reaction time, would not have been able to detect and prevent a collision.

Navigation apps like Google Maps provide more than enough detail to find your way from A to B, but these maps are only able to locate your car within a margin of several meters – 3D maps must be accurate within centimeters. They must show the precise location of all street signs, lane markings, curbs, and even deep potholes that should be avoided. Moreover, if we want autonomous vehicles to be able to take us anywhere, we have to have detailed maps everywhere – and there are more than 4 million miles of roads in the U.S. How do we tackle such a monumental task? This question has provoked the attention and innovative efforts of a host of companies.

Lvl5, a startup from former Tesla and iRobot engineers, aims to crowdsource mapping data with their app called Payver. While not all cars are equipped with cameras, nearly all of their drivers carry smartphones with them. By mounting your phone aiming out the windshield, you can earn between 2 and 5 cents per mile depending on whether or not the road is common or uncharted. The process, which relies heavily on machine vision to stitch together and label every fragmented video, is a logical way to build maps early on, leveraging the user base of smartphones and the sizable number of people who drive for a living for a ridesharing, delivery, or freight service.

Waymo, who has a longer history of mapping tech and a large budget thanks to parent company Google, is taking the opposite approach. In its usual ‘do everything ourselves’ fashion, Waymo is building their maps by driving around in vehicles equipped with spinning LiDAR units. LiDAR provides a much more detailed image of its surroundings than a camera, but still requires substantial human input to label each object. Labeling things like traffic lights, street signs, and buildings is tedious, but is necessary so that a car can tell the difference between a tree and a yield sign. There is also promise of automation of this process by AI tech similar to Google Lens.

Here Mapping and Mobileye have combined many of their efforts around building, maintaining, and distributing maps to become the defacto leader in the space early on. Here, owned by a consortium of German automakers, (Audi, BMW, and Mercedes-Benz) has ambitions to build a digitized version of our world that can be interpreted by autonomous vehicles and other machines with what they call an open location platform. Here has built out their maps with LiDAR-equipped vehicles and will maintain them with an extensive network of cars outfitted with Mobileye hardware. Mobileye, purchased by Intel earlier this year for $15.3B, offers a range of services for self-driving cars like sensor fusion and camera tech, but has recently been focusing on mapping. The combined result will be a comprehensive 3D map that is aggregated in the cloud and maintained in near real-time by crowdsourcing data from a network of connected cars. The maps will be sold as a service that automakers with autonomous systems can subscribe to.

Tesla has a distinct advantage stemming from the sheer number of cars they have on the road equipped with the hardware necessary to build maps (cameras, RADAR, and ultrasonic sensors). 3D mapping presents a textbook network effect and Tesla, with thousands of vehicles already in play, is in a great position to take advantage of that market force. The question will be one of communication with other cars as more automakers begin to develop and test autonomous systems.

While the method of building sufficiently detailed maps varies, their importance in the self-driving equation is almost universally agreed upon. In contrast with lively debates over the correct combination of RADAR, LiDAR, and camera sensor arrays, or countless chipmakers jockeying to provide cars with computing power, mapping seem under-appreciated and underinvested. As Mobileye co-founder Amnon Shashua suggests, there are three core elements of self-driving cars – sensing the road, mapping the road, and negotiating your position on the road. 3D maps will be a key determinant of the long-term winners in autonomy.

Thanks to Will Thompson for his work on this note.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Facebook Is Going to Muscle VR into the Mainstream

At yesterday’s Oculus Connect 4 conference, Zuckerberg outlined a goal to have 1 billion VR users. This goal is rooted in his belief that once platforms reach more than 1 billion monthly users in scale, they’re impossible to compete with. He should know, given the platforms under his control including Facebook (2B), WhatsApp (1.3B), Messenger (1.2B), and Instagram (800M). Like it or not, VR will be mainstream – and we love it.

Empowering global VR adoption. While the Oculus Go hardware announcement and Zuckerberg’s billion user VR target captured yesterday’s headlines, the bigger story is that Facebook can singlehandedly turn VR from a nascent user base today into a mainstream computing platform in the next 5 years. Facebook has the capital ($502 billion market cap and $43 billion in cash) and its founder is committed to empowering global VR adoption.  It’s important to note that VR has long been a passion of Zuckerberg, and it was reportedly love at first sight when he first used Oculus. Zuckerberg’s 1 billion VR user stake in the ground will be a motivator for start-ups, private companies, and investors. We no longer have to debate if VR will be real, now it’s a function of time.

How big is the VR Market? Earlier this year we published our VR headset market share model, which calls for monthly global VR users increasing from 100 million in 2018 to 1.2 billion by 2022 and 2.4 billion by 2025. While we’re leaving our estimates unchanged following Zuckerberg’s comments, our confidence in our VR user model has increased.

How much will Facebook spend on building out VR? We estimate Facebook will spend $36 billion on R&D over the next 3 years (2018-2020). If we assume 15% is going to VR that would imply over $5.5 billion in spending, which we see as more than adequate to accomplish it’s billion user target.

Facebook gets it, VR needs to be social. Social is not only important to Facebook’s mission, but to the future of VR. Mainstream adoption of VR will not take place with the current gaming landscape, since VR is currently seen as a luxury geek item. Instead, VR will need a social aspect before there will be mass adoption of the technology. Software features like screen-sharing, virtual lounges, project collaboration, and shared experiences like watching a movie or a sports game, allow people to connect in VR.

Oculus Go is more accessible. This headset is a step toward finding the sweet spot between mobile VR and computer-based VR. Mobile VR is easy to use but offers a diminished experience, while computer-based VR offers the highest quality experience, but is far more expensive and leaves users tied down with a cable. The Oculus Go is noteworthy not only because its $199 price point is 15% of the cost of an all-in Rift system (with a compatible computer), but because it’s easier to use, offering plug-and-play with no wires and no specific smartphone needed. While the quality will not be as rich as on the Rift, it will address the need for a middle of the road system that will undergo huge improvements with further investment as more users flood to VR.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.