Ride-hailing firms are moving towards attaining the ‘holy grail’ of mobility. This is the reason why ride-hailing firms are also investing heavily into service enhancements, besides looking at geographical growth. To achieve this, they are investing heavily to understand the socio-economics of human mobility across cities through data analytics (DA) and Machine Learning (ML).

The Goal of Ride-Hailing Firms

DA & ML have become the most sought-after capabilities among ride-hailing firms. In the existing ride-sharing model, firms like Uber, Grab and DiDi are using consumer data for supply positioning, customer classification, acquisition channel effectiveness, customer relationship management (CRM), as well as optimization of marketing spends.

Meanwhile, the emergence of the internet of things (IoT), low-latency networks such as 5G and smart wearables with distress sensors will help ensure rider safety, which still remains a major concern. Over time, the target is to make these systems so efficient in terms of availability, service, security and affordability, that it reduces the primary need for owning a car at all.

However, the goal is much larger than achieving higher efficiencies within the existing services that they offer. The data of millions of movements from place-to-place each day will drive numerous mobility trends. And though user data will likely stay within the geographical boundaries due to regulations, human mobility trends will open new service avenues and revenue streams. This diversification is a well-thought-out vision of short, medium and long-term goals.

Synergizing Opportunities

Ride hailing firms are investing heavily in businesses such as food delivery, bike-sharing, infotainment, electric vehicles (EVs), autonomous vehicles, and even flying taxis. While the majority of firms are keeping themselves invested in short-term opportunities, exploration of medium and long-term opportunities requires significant investment and is therefore confined to better funded firms such as Uber and DiDi.

Local and regional firms have focused on short-term opportunities (such as food delivery, bike sharing, infotainment, etc.). Expansion into food delivery services (through organic and inorganic expansion) is a natural step for them, which follows in the footsteps of UberEats.

Apart from food delivery, another immediate opportunity is infotainment and location-based advertising. This includes access to on-the-go music, video streaming, weather, news, social media, etc. An infotainment service along with location-based advertising requires minimal investment and it can be a significant opportunity for incremental revenue. It can also help bring down the cost of ridership in emerging Southeast Asian and African countries, in which cost has been an obstacle to consumer adoption.

• In India, Ola has done well with OlaPlay service – as not only riders, but also drivers enjoy its infotainment services that are provided at a minimal cost. It also helps them reduce fatigue while driving.
• A US-based start-up – Vugo, specifically developed an advertising platform for ride-sharing applications.

 Uber and Didi Aim higher

Global ride-hailing firms such as Uber, DiDi and Grab have deeper pockets and they’re aiming higher with a long-term vision for mobility services.

Uber’s initiatives provide a good indication of its intended development path:

• Uber is currently negotiating with regulators to establish location-based advertising.
• Uber is exploring opportunities to enter the logistics market in North America. Other ride-hailing firms are expected to target the logistics sector in the medium term.
• Incentivizing driver partners to switch to electric vehicles. While this is difficult for drivers due to the limited range of EVs, it gives Uber valuable information about the performance and cost structure of operating EVs. This will be key as it develops its autonomous car ambitions.
• The company has already been very active with autonomous car testing in California and Arizona, though not without serious incident.
• Uber has also stated its intention to launch a flying-taxi service by 2023. Some automotive original equipment manufacturers (OEMs), technology firms, and organizations like NASA are also contemplating the idea of elevated transportation.

Similarly, China’s DiDi Chuxing is marching towards the same goal. While the company remains invested in ride-hailing firms (such as Grab, Lyft, Ola, 99, Taxify, and Careem) across the globe, it aims to address the needs of the future of mobility:

• In April 2018, the company confirmed the launch of its food delivery service.
• In February 2018, it teamed up with 12 automakers to create an electric-car-sharing platform. This is important as China is the biggest car market globally.
• Didi has also invested heavily in artificial intelligence (AI) research labs in Beijing as well as Silicon Valley, for analytics-driven smart transportation solutions.
• The company is already running several tests on autonomous driving in Silicon Valley in the US.

Ride-sharing firms are partnering to create an ecosystem that supports various parts of the value chain. For example, firms such as Qualcomm, Intel and Nvidia have played a significant role in creating the required technology and establish the connectivity standards. Similarly, automotive OEMs and tier-1automotive component suppliers are supporting the vision. Over 50 companies have received permits to test self-driving cars on public roads in California as of May 2018. This makes it the most concentrated autonomous vehicle testing site.

Apart from above, various other firms have been pursuing the autonomous cars technology aggressively.

• For instance, the Netherlands-based HERE Technologies is leading HD mapping needs of the autonomous mobility, while leveraging the AI technology, along with other automotive OEMs and Tier I component suppliers. It offers self-healing maps, which crowd-source sensor data for updating the maps continuously.
• Similarly, Google’s Waymo – the only firm with Level 5 autonomous vehicles on road, has leveraged sophisticated AI-powered neural networks to leap ahead of others in the autonomous race.
• Among OEMs, General Motors has envisions to commission a network of autonomous Chevrolet vehicles offering ride-hailing services. The initiative recently also witnessed infusion of $2.25 billion by Softbank’s technology focused vision fund.

Nevertheless, while the development of self-driving cars (and the fantasy of flying taxis) is enticing, there remain many hurdles to their widespread adoption – many of them regulatory. The vision of future mobility will need global tech behemoths to work closely with automotive OEMs, as well as government regulatory bodies.

The Uber’s and DiDi’s of today are planning to totally transform themselves in the coming decade, intertwining their existence through numerous aspects of people’s daily lives. Ride-hailing is just the start. Their aim is to serve a much larger purpose, which is far beyond commuting from point A to point B.