Written by Enrique Camacho, Republished from OMNi Blog

We’re living in extremely exciting times in regards to mobility’s history and the solutions arising, from the rhythm at which innovation is happening to the way its business management is nowadays done.

Without a doubt many things are still unclear, the relationship between the user and the sought value propositions, systemic shifts across industries and the effects of new regulatory frameworks across countries. However, one thing is clear, the business decisions and operations of mobility products have a new star player: advanced analytics.

Data and quantitative analysis have been part for a long time of the fabric of the mobility industry however the requirements of this field are now higher and more sophisticated. From predictive analytics, data software as a service to scenario-modeling, these are the new cornerstones of doing business in mobility.

Mobility, a science of movement and space

Unlike other types of services, mobility due to its nature is deeply intertwined with space and the movements we make. This means that in order to understand it better and create higher and more impactful value to users with it we have to pay attention to everything that happens between point A and point B.

At OMNi since April this year alongside our fantastic Big Data team we started a pilot with the advanced location analytics tool Locale. It’s a specialized geographic data -intelligence product designed for mobility and ground operations companies.

Through a visually robust interface, a robust data processing architecture and high ease of navigation we have been able to understand geographically in great detail the use of our products throughout the country as well as its evolution over time through hyperlocal insights.

OMNiTaxi Rides – Costa Rica heatmap

One of the biggest contributions from a tool like this in the operation of our products, Taxi and bikes, has been the automation of data pipelines in order to save on what would otherwise be a highly manual and time-consuming process to use and analyse this data.

Location analytics tools like Locale bring infinite use cases for our current mobility products however there are 4 core analyses we’ve developed, historical in our company’s short history.

1. Understanding our users through location analytics

We’re actively using the aggregated location data generated by our users’ interactions with our apps in order to shape our products as close as possible to what they need, as well as categorizing our demand geographically and define action plans to expand and improve our business performance.

OMNiTaxi – Users requesting a ride – Usage patterns by day

OMNiBikes – Users starting bike trips vs OMNiSpots (green dots)

Specifically, through this data we are able to:

  1. Identify key areas to increase coverage and improve business KPIs as well as defining an expansion plan
  2. Measure impact of commercial and marketing campaigns by geographic area
  3. Define opportunities to increase our user base given geographic and time patterns
  4. Identify product fixes and improvements according to what insights suggest

2. Closing the gaps between supply and demands

One of the core missions of mobility services applications is to always achieve the highest number of rides and therefore manage the business KPIs that allow this goal. Here is where it becomes important to analyse the dynamics between supply  (our drivers)  and demand (our users) through location analytics.

Locale allows us  to compare (see image below) two core KPIs, driver idle time (which symbolizes potential available time drivers have to receive ride notifications) and places with the highest number of trip requests.

OMNiTaxi – Analysis Driver Idle Time vs Ride Demand

This comparative analysis allows us to:

  1. Define key areas to stimulate supply and demand in order to increase the number of completed trips.
  2. Drive targeted communication and marketing efforts to specific key regions, for both the driver and user base, in order to capitalize on gaps and improve KPIs.
  3. Define a gradual expansion roadmap to increase driver enrolment based on the key areas where there is low coverage but high potential for bookings.

3. Reaching operational efficiency and smart planning

At OMNi not only do we seek for our products to be commercially attractive and strategically designed but to also follow the highest operational efficiency standards and smart planning practices.

In the case of our micro-mobility product, given the bikes dockless model we offer happens thanks to an operational and logistical strategy, location-analytics-data helps us answer questions like where should we locate our bikes, how often should we guarantee these spots are re-supplied and therefore how to achieve high business traction while being cost-efficient.

Locale provides an innovative visualization feature, useful for these purposes, the nodes (yellow bubbles in image below). These nodes are automatically formed in locations where there is a high agglomeration of bike trips’ origins and destinations and its size is linked to the amount of these trips. The lines connecting them are straight lines representative of the route taken and its width is linked to the number of trips that go through the same route.

OMNiBikes – Bikes Trips Activity Analysis

This type of analysis allows us to:

  1. Determine the most important locations where bikes should be supplied to users
  2. Drive commercial and marketing efforts in areas where there is the highest bike usage potential
  3. Develop a logistics and strategic operations action plan that includes hours, days and number of bikes to constantly supply to our predefined OMNi spots as well as optimizing the location of these spots

4. More than just routes and the A to B

Finally, as part of our core mission to bring to the Costa Rican market mobility solutions with an increasing value to users we need to look into what underpins the needs users have. In simple words ¿where are our users headed when using our products?

Locale through its specialized features allows us to identify and dissect movements patterns from our users in order to best understand how our products can respond more closely to what they need.

OMNiBikes – Bike movement patterns

OMNiTaxis  – Taxi Rides Origins and Destinations  vs Activity Nodes

These types of advanced analyses help us:

  1. Identify where should we improve the geographic coverage of our services and products and define an action plan that ensures a healthy expansion and necessary reconfigurations for our presence
  2. Develop marketing and commercial efforts that respond to key characteristics of usage from our user community
  3. Improve operations and logistics that underpin our products in a way that we run products as efficient as possible

In the last few months, thanks to a close collaborative effort between our data lead, analysts and engineers along with the innovative Locale team we’ve developed countless new use cases and features in the platform, something that not even the major time differences between Costa Rica and India have been able to stop.

The new exciting tides of advanced analytics remind us once more that the high-speed technological progress demands us to become committed innovation agents on the business side as well. Luckily the geographic coordinates to get there are already in our hands.

Originally published at OMNi Blog.