White Paper



Real-Time Location Analytics: Use Cases

By Sajith Ravindra
Associate Technical Lead, WSO2

1. Introduction

Today, enterprises are looking for innovative ways to digitally transform their businesses - a crucial step forward to remain competitive and enhance profitability.

Refer to our white paper on a platform digital transformation to get a deeper understanding of what digital transformation means to your enterprise.

There are key technology enablers that support an enterprise’s digital transformation efforts, including smart analytics. Other technologies include

Within smart analytics, real-time insights and real time analytics help organizations to gain the business intelligence they need for digital transformation.

From a business perspective, it can offer many potential benefits to an organization such as

  • Enabling better customer experiences by using location and contextual data
  • Creating radically new data-based products for your business
  • Making more informed decisions in complex scenarios
  • Carrying out effective monitoring and analysis
  • Detecting even the smallest change and trigger immediate action
  • Extending your solutions to analyze the past, present, and the future

This white paper will focus on the business benefits of a real-time location analytics solution for large as well as small organizations in any industry. We first explain the concept of real-time location analytics and how organizations can benefit by incorporating such a solution; it will discuss some use case example that demonstrate how this solution helps to minimize costs, increase revenue, and mitigate risk.

2. Real-Time Location Analytics - An Overview

Organizations are often inundated with thousands of data streams that contain geographical and location-related data; however, only a fraction of these organizations possibly exploit the potential of this data in terms of the valuable insights it could provide. Meanwhile, some organizations are aware of the potential benefits, but often struggle with the complexities related to analyzing this data due to the sheer volume, the variety of channels they come from, and the challenges in correlating disparate data streams. To this end, a real-time location analytics solution can help organizations to derive meaningful insights in an efficient way by analyzing large amounts of data and deriving valuable information that can help enterprises to make business decisions.

A comprehensive real-time location analytics solution can put geographical/location data to good use by extracting valuable insights. What this means to an organization is that it enables them to take proactive actions to enhance their business operations while making it possible for them to learn from past events and make more efficient and accurate business decisions. State-of-the-art, real-time location analytics tools can help enterprises handle the complexities related to data in a more transparent manner; it can transform massive amounts of rudimentary data into powerful insights, which in turn can be converted to executable actions.

3. The Key Advantages of Real-Time Location Analytics

Location and geographical data often conceal many useful insights, and extracting this information can help an enterprise to optimize their business processes and increase profits with better management of resources. For instance, sensors, such as GPS tracking systems attached to vehicles in a fleet emit data on its location periodically. Location analytics can transform this periodic location information to detect congestion, predict delays, detect idle vehicles, suggest alternate routes, spot violation of transportation rules and guidelines (e.g. speed checks), and identify the most profitable routes/regions. Similarly, many other enterprises operating in various domains can leverage real-time location analytics to analyze location/geographical data that’s available to them and extract useful and actionable insights to refine their business operations.

From a business perspective, such a system can streamline an organization’s operations and improve efficiency, add value to its products/services and give them an edge over competitors, and eventually improve revenue. Some common business benefits and how they can be achieved are as follows:

Minimize cost with improved business process: Real-time location analytics enables an organization to monitor their resources closely in great detail. This allows the organization to manage their resources optimally and minimize wastage. This will minimize the costs of running the business.

Foresee risks and mitigate them: The advanced monitoring capabilities in real-time location analytics can help you to reveal unforeseen circumstances that are not apparent and that would hamper the effective execution of business processes if not handled efficiently; detecting such undesirable events enables taking corrective actions promptly to minimize damage. For example, by monitoring the driving patterns of a given vehicle, you can detect driver fatigue and instruct the driver to take rest immediately to avoid an accident.

Increased revenue with advanced business intelligence: If an enterprise knows where your customers are coming from and what happens when they come into your premises or when they use your services, the enterprise can formulate better marketing strategies to meet their exact requirements. This is done by understanding the customers better by characterizing their behavior and needs more accurately. For instance, when a shopper enters a mall, you can gather information like the specific shops he/she goes into, where they spent a majority of their time, and how often they visit the specific mall. This information will help the mall as well as individual shops to correlate such data of all shoppers to understand their shopping trends, and better align their business strategies.

3.1 Sample Use Cases

3.1.1 Fleet Management

Fleet management is a great example of how real-time location analytics can be utilized to reduce the expenses and risks of a business. GPS tracking devices attached to vehicles in the fleet can emit its current longitude and latitude with some other additional attributes, such as a timestamp. A fleet management system can collect raw location data over time and analyze them to improve internal operational efficiencies and boost productivity, which in turn can translate to a significant reduction in transportation and staff costs.

The main challenges faced by an enterprise that capitalizes on fleet management include the lack of knowledge on the exact location of their fleet, unfavorable activities carried out by drivers that cannot be tracked, inability to optimize vehicle and fuel usage, the lack of visibility of prevailing circumstances, whether in the air, at sea or on land, and the inability to perform predictive fleet maintenance.

An efficient fleet management system, as depicted in Figure 1, will help administrators to track operational expenses, such as vehicle maintenance, and budget for those expenses accordingly. It also enables you to monitor and track any misuse of company-owned vehicles by drivers. When you own and manage a fleet of vehicles, you control what goes on behind the wheel. Whether you install GPS tracking systems to monitor your drivers, or setup a check-in/checkout system for using the company’s vehicles, you ensure that the drivers you put behind the wheel follow your rules and maintain driving excellence. With all these monitoring capabilities, an organization can continuously enhance their business operations while foreseeing any risks and take proactive actions to mitigate them.

WSO2 Stream Processor (WSO2 SP) is an open source stream processing platform. It can ingest data from Kafka, HTTP requests, message brokers and you can query data stream using a “Streaming SQL” language. With just two commodity servers it can provide high availability and can handle 100K+ TPS throughput. It can scale up to millions of TPS on top of Kafka. WSO2 Stream Processor (SP), with its complete set of features, can help you to develop a fleet management system to match your needs. It comes with a geospatial toolbox that can be used to detect unruly driving patterns and send notifications to administrators through SMS or email, track and find vehicles that are within a given geographical area, etc. The geo dashboard feature can present this information on a geographical map that will help you to easily oversee your fleet.

Transport for London (TfL), Amazon Web Services, and Geovation hosted a public hackathon recently on how software can be used to help them better manage their resources and traffic. The competitors were provided with historical data on the various aspects of fleet and transportation and access to a data generated network of SCOOT traffic sensors deployed across London. The solution developed by the WSO2 team was selected as the winning one. This solution was developed within two days and contained features, such as predicting travel times, and suggested best routes from one stop to another. It also consisted a visualization component that displayed information on a live map of the city of London. For more details about the solution, refer to this blog post.

The key components of a fleet management system

Figure 1: The key components of a fleet management system

3.1.2 Proximity Marketing

Proximity marketing uses beacons and mobile infrastructure to locate customers and collect data about their movements. We can use this movement data to analyze their behavior and patterns in order to enhance their shopping experience by providing them suggestions on what they might need. This enables organizations to highly personalize their offerings based on the context of individual customers, instead of pushing out random product offers via text messages or emails to a mass audience. This highly increases the chances of a customer purchasing goods as their now offered with what he/she was probably looking for.

Location analytics can help to identify the indoor location of their customers and track their motion within the store. With location analytics, it’s possible to identify patterns in customer movements and shopping patterns of each customer individually. By mapping customer locations and motion patterns against product placements within the store, you can market the products better by performing activities, such as discovering the most attractive products in the store, and sending an 'offer of the day' when customers are within a certain radius of an electronic billboard, provide offers related to specific products of interest to a given customer, suggest other products relative to what the customer is looking at right now, or offer coupons based on customers' previous purchases.

Furthermore, analytics will generate advanced and informative statistics, such as where customers spent most of their time within the store, how long on average a customer stays in the store, how long it takes a customer to find an item, etc. These statistics will be useful for store managers to refine and redefine business and marketing strategies.

To put this into perspective, let’s consider an example. Joe, a regular customer at Walmart, walks into a store. By detecting his mobile device within premises, the store manager will know that Joe has returned to the store. The store manager has access to his purchase history, so he can send Joe a message to let him know of any new offers or items he might be interested in. The store’s automated system can also track his movements within the premises and display specific adverts he might be interested in when he approaches an e-billboard. In a nutshell, Joe has a better shopping experience while the store can actively promote items that match his interests.

WSO2 SP can analyze data generated by various sources and correlated them overtime. Therefore, data streams generated by customer mobile devices and beacons placed in the store can be fed into WSO2 SP and this data can be correlated and joined to extract information that will give a broader and clearer understanding on what the customer needs and his/her shopping patterns.

To further understand this with a real-world example, refer to our customer story on how Eurecat enriched their customers’ shopping experience by using location analytics.

Use of analytics for proximity marketing

Figure 2: Example of the use of analytics for proximity marketing

3.1.3 Analytics in sports

When it comes to sports that involve moving players and objects, location analytics can be used effectively to enhance team performance and improve the way the game is played by having better insights into how each individual player performs, how the players interact with each other, and how well the team executes their game plan. With the increased availability of technology, low-cost sensors, efficient and powerful hardware, and high performance processing engines, teams are increasingly looking at technology as the next competitive advantage over their rivals.

For instance, a football club can incorporate location analytics to monitor individual players closely and determine if they are performing at their full capacity by monitoring statistics, such as average speed, distance covered in the game, etc. If the player is exhausted, the manager can immediately call in a substitute. Apart from the performance of individual players, the synergy of the team is crucial to stay ahead in the game, and real-time location analytics lets you correlate and join streams of data generated by individual players and objects such as the ball. By correlating these data streams, you can gain a deeper perception of interaction between the players and monitor the overall team’s performance and all aspects of the game in realtime.

This video is a demonstration of a solution that was developed using WSO2 Complex Event Processor (WSO2 CEP) (WSO2 CEP now available under the name WSO2 Stream Processor) to analyze a game of football. Each player, the ball, and the goal posts have sensors; these sensors emit location data with a timestamp and sensor identification and WSO2 CEP receives and analyzes this data in realtime to produce various stats, like average speed of a player, distance each player has covered, number of shots on target, ball possession, etc. It also detects events such as offside, goals, and failed passes and tackles. Finally, this information and statistics are presented in a live dashboard that updates in realtime. Refer to this presentation for more details.

4. Conclusion

Analytics use to be a term reserved for data scientists - a word heard by many, but understood by a few. This is no longer the case. Enterprises that do not reap the benefits of analytics will soon be edged out by their competitors. With data being a key component in any business today, enterprises are forced to look for new ways to analyze this data and gain insights into their business. Thus, in today’s business world, analytics has become vital to improve customer experience, increase market reach, optimize budget spend, enhance business processes, and find and eliminate anomalies. All of these eventually translate to improved revenue for any business.

This white paper explained in detail how a real-time location analytics solution can help organizations to analyze large amounts of data real-time and derive insights that will help them make better business decisions. Ultimately, it will benefit the organization by helping it to minimize costs, increase revenue, and mitigate risk.

It’s clear that streaming analytics is widely applicable for location analytics in large as well as small organizations. It can also be used for specific solutions and use cases in other industries as well. Refer to our white papers that cover other industry solutions for more details:

  • Retail
  • Banking & Finance
  • Smart Energy Analytics
  • Social Media Analytics
  • QoS Enablement
  • System and Network Monitoring

With the pace at which the world is transacting, analytics that are computed as batches will no longer be relevant. The current need is to perform complex analytics in real-time so enterprises can act on them before the opportunity goes by. Streaming analytics is a perfect fit for this role as it can receive multiple types of data from multiple sources, correlate them, process them, and provide meaningful insights all in a matter of milliseconds. Irrespective of the industry, streaming analytics can create a winning strategy for your business.

If you found these use cases helpful and/or applicable to your organization or have similar use cases, we’re happy to further discuss your requirements and take you through a demo. Please contact us and we’ll get in touch.

For more information on WSO2 Analytics solutions please visit wso2.com/analytics-and-stream-processing/solutions/.

For more details about our solutions or to discuss a specific requirement


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