Thanks to Nikhil Gupta for helping us out with this blog!

Key Takeaway:

In this blog, we will discuss how you can use to analyze Irys mobility data for different use cases by overlaying it on top of your internal data. The data is collected & curated from geolocation signals using millions of connected devices worldwide. We also did some data-cruncing to show you mobility insights during the lockdown period in Bangalore, India.

What is external data and why should you care about it?

Often, internal data that is genearted and owned by the company (like customer’s transactional data, user events data on websites or apps, vehicle sensor data, data from workforce apps) doesn’t provide the complete picture, especially for companies that are expanding in newer locations or for those who don’t possess rich internal data.

External geospatial data streams refer to data that can be found and collected from external sources. These might be publically available or are collated and sourced by various organizations.

Why Mobility Data?

Human mobility plays a great role in uncovering human behavior patterns and individual habits. Human mobility can help to have insights on spatial distribution on movements, creation of user personas, use of public transportation, level of walkability, and pollution emission in a region. The data sources of human mobility data are GPS data, cell tower data, and WiFi data.

“How people move and where they go tells you about who they are.”

Why is irys's external data useful and why should you use it?

Source: Unsplash

To work with human mobility data, we turned to Irys — a location intelligence company that specializes in transforming human mobility data into powerful insights for businesses. Irys has one of the largest corpuses of anonymized mobile GPS data spanning hundreds of millions of devices across 150 countries.

Mobile GPS data is the gold standard for mobility data due to its excellent coverage of device behavior and high location precision. This makes it ideal for capturing the intricate dynamics of places and people at varying resolutions. Irys uses sophisticated models to extract information that describes everything from the small (single store or city block) to the large (big populations, neighborhoods, cities, and even countries).

Here are examples of how customers across different industries leverage this data:

  • Property Valuation: Real-estate buyers use property insights to assess the potential performance of new deals and acquisitions.
  • Benchmarking Retail Performance: Brick-and-mortar retailers use retail traffic to understand how their locations perform against the industry and competitors.
  • Targeted Advertising: Marketers ingest visitation data to identify and target consumer segments based on the types of places they visit.
Source: Unsplash

The applications are endless, and we were very excited to work with Irys and explore new applications in logistics and planning for our customers.

  • Expansion: Irys data is useful for any kind of expansion. Whether it is a ride sharing company looking to set up a new station, or a cloud kitchen company looking to open a new center or a bank planning their new branch.
  • OOH Advertising: This data is also useful for out of home advertising (to pinpoint locations of setting up bilboards) on the routes most traveled.
  • Sales & Distribution: The data collected from smartphones is a good proxy for penetration is that area along with economic growth. Often, FMCG and real estate companies use it to identify the areas they need to do more targeted sales.

Locale- Irys Console and Insights

In this section, we want to show you some interesting insights that we got after after lots of data crunching. We were able to pull off a console which shows how people move across the city of Bangalore, India.

The data spans the entire month of March 2020 and shows how subtle changes have occurred in the city, right after India went under lockdown n 24th March.

Locale console view for irys data. Left panel shows different metrics, the bottom timeline shows the changes in the metric over time and the map shows us the intensity of the metric in different areas, indicated by color.

A bird’s eye view of the console is enough to spot the huge dip in the number of people moving across the city. As evident from the timeline, there was a sudden drop in the number of people moving on 22nd March, then a spike on 23rd March and then a final dip from 24rth March onwards. But what was so special about 22nd March?

It was the same day when the PM asked billions of Indians to stay at home under a short campaign, popularly known as “Janta Curfew”. Following this, the lockdown was announced on 23rd of March to be in effect from 24rth March onwards. But what can your business take away from this? Let’s find that out by looking how lockdown affected industries and daily business operations.

Bengaluru before lockdown. Console

Let’s filter to a week before lockdown. With around 18k unique people across the city, the average distance which they travelled was roughly 3kms. Also, the map makes it very clear the left part of Bengaluru is not active as the right one.

Now, let’s see how a week after lockdown looks like.

Bengaluru after lockdown. Console

At a glance, we can see that total unique people moving across the city has become half to ~9k and the average distance which they cover has become one third to 0.9kms. Also, certain parts of the city have seen a drastic fall in the total number of people moving in and out of those areas.

A closer look at the highly dense areas reveals another interesting thing about the change.

Left: High activity areas in Bengaluru before lockdown | Right: High activity areas in Bengaluru after lockdown

Most of the activities post lockdown confined to the upper right area or Bengaluru east, although the intensity is still very low compared to the pre lockdown period.

If you are a decision-maker, you can now see what areas are badly hit and define strategies to make each area of the city more accessible. Certainly, lower bengaluru seems to be hit badly or has movement restrictions in those areas.

So, if you do deliveries, you can make use of this insight to plan your delivery partners to comply with regulations, improve ETAs by factoring in reduced traffic, etc. For a ride hailing company, this insight means now you can allocate resources into the right hotspots where people really need to move.

How uses external data to power their analytics?


One of the biggest challenges of external data is that it is difficult to find and access for teams everywhere. From the time they start searching for data, find the right vendors, test samples, go through the legal and finance process—it takes four-six months.

At Locale, we’re making it extremely easy for you to access and enrich your internal data with external data in minutes, not weeks or months. From our data marketplace feature, you can quickly select datasets and experiment with the ones that are the most relevant to you.

The best part is that the data will already be cleaned and processed in our marketplace module and we do the heavy lifting for you. What’s more, you can access this data at an extremely granular level—at least 10 times more granular than traditional ward-level data. This helps you make more targeted decisions for your business and get better returns on money spent on sales, marketing or other activities.

If you want to know more, check out Website or reach out to me on LinkedIn or Twitter.