Over the past few decades, innovations have been focused on the digitization of analog services, business models and optimization of user experience. Digital banking, payment wallets, online shopping, ride-hailing, video conferencing, social networking, mapping, etc. come to mind. Yet nothing feels fundamentally different, as there has been little focus on reimagining the core logic behind how we structure the services that fuel the current state of the economy. Innovations that cause a shift are few and far between.
Looking at the next decade, there is a new wave of tech innovation on the rise — 5G, IoT, autonomous vehicles, decentralized finance, digital currency, smart cities and even the metaverse — which will play a pivotal role in redefining how we consume, connect, collaborate and create. While companies, and even countries, are busy building their own solutions within silos, I believe we are all missing out on a central cohesive force that brings it all together.
How new cities are imagined, micro-towns are planned and even international borders are drawn is undergoing a radical change. Decentralization and the advent of nonstate-backed global currency vehicles along with access to the latest tech are enabling a move from a centralized economy to decentralized and fully self-sustaining micro-economies. This will totally change how businesses are built and customers are served.
Micro-location and hyper-local data are going to be critical for the success of this new paradigm. From my past experience creating a startup in this space, this will start with accuracy and precision in mapping, addressing and how we structure location-based data and move toward real time, dynamic routing and self-healing maps. As the location-based economy spanning from e-commerce, food delivery to mobility is experiencing exponential growth right now, in my opinion, the industry is still limited by legacy technology providers.
This brings us to one of the most important nuances of last-mile delivery applications: point of interest (POI) data. POI is a specific location on a map that someone may find useful or interesting. It might be a food truck, a salon, a restaurant or a tourist attraction, as well as ordinary places like post offices, schools, grocery stores or parking lots.
Google is the global market leader in providing mapping-based solutions for individuals and businesses. In 2018, the Google Maps platform split into Maps, Routes and Places. For all three, you get $200 worth of services for free each month (provided you don’t exceed the monthly limit.) But to most businesses, like ride-hailing and last-mile delivery applications, Google charges approximately $5 per 1,000 requests. The same goes for geocoding, or converting addresses to and from geographic coordinates. Static and dynamic street view might cost anywhere between $7 and $14, respectively, per 1,000 requests each and so on. For consumers, though, Google Maps has a perception of being a free service because the usage limit is enough for most of us.
Here comes an interesting nuance: All these businesses using Google Maps API services to optimize routing and provide faster deliveries not only pay Google but also generate valuable POI data points. The riders and the drivers while delivering and driving also mark the closest parking spots for a specific location, elevator utilization, shortcuts for bike riders and so on.
Although Google’s paying customers generate this highly monetizable data, Google still owns the data. For this reason, some entrepreneurs might be considering stepping up to create another option or partnering with mapping tech providers that allow the usage of a map and for companies to own the POI data they generate.
Imagine a world where all of us as users could contribute POI data and get rewarded for the same. For example, consider if there was a map store where a foodie could publish the best dishes on food trucks in California and could earn a financial consideration for the same.
However, where there is an opportunity, there are challenges. Although POI data is widely used across a variety of industries and applications, there are no legal standards for formats, models and identifiers in place. This often leads to incompatibility among POI datasets produced by various vendors and may require a humungous effort before they can be integrated and used. For instance, a city guide and a navigation tool might have dissimilar priorities when deciding what POI to include and what sort of information about the said POIs to gather.
To overcome this challenge, it can be helpful to try to find complete POI profiles or to integrate several POI datasets with overlapping points so that you can have all the information you might need.
I came across UNL, which I now am an advisor for, a company that is standardizing the way hyperlocal data is stored, managed and shared across platforms. UNL organizes location and POI metadata into UNL geocells to create semantic and spatial relationships between different landmarks and points of interest. All data updates are published on the map in real time and embedded in search and routing.
what3words is another upcoming digital geocoding system. But instead of being limited to addresses, it lets individuals identify any location that’s three by three meters, or 10 by 10 feet, in size. It also assigns every square a unique name made up of three words, so you can access a location by typing either the three words or the traditional address of the location.
These types of new technologies might be some of the missing elements that the metaverse needs to become the experience and service engine for the next generation economy.