The full potential of location-based data is realised when it’s married with other sources, write Mu Sigma’s Vibhav Agarwal and Saumil Agrawal.

Imagine you are en route home from work and looking forward to that weekend when you can splurge on shopping – maybe a new pair of shoes – when, just as your car passes the brand outlet, you receive a text message that says, ‘Special discount: 20% off  shoes… today only’.

This could prove to be a perfectly-timed offer. Or you might just wonder, ‘How on Earth did the retailer know my whereabouts and shopping patterns?’

The answer lies in location-based analytics.

It’s a widely known fact now that location data is disrupting the way companies are looking at their consumers. Right from targeting marketing to identifying the next outbreak of crime, both private and public sector organisations are leveraging the power of location data to derive insights and take very specific actions. Now, more than before, it’s important to understand what makes this data so powerful and how companies can leverage this to their advantage.

The pervasiveness of mobile devices aided by high-speed internet has led to what is called the ‘mobile revolution’. The widespread usage of mobile devices such as smart phones, tablets and phablets has made it easier for internet companies to access users’ location data through technologies such as GPS, Wi-Fi and cell tower triangulations.

A number of popular wearable devices such as Google Glass, Nike’s FuelBand and other sensor-based mobile applications are contributing to the variety and volume of data in a big way. In addition, social media channels such as Facebook and Foursquare allow consumers to identify their location and remain connected at all times.

Telecom service providers employ ‘mobile LBS’ to track the location of users within a wireless network using internet-aided geographic information systems (GIS) from mobile devices and GPS enabled vehicles. By working closely with telecom companies and leveraging location data from sources such as mobile devices, social media, retail POS and demographic data, marketers can engage more effectively with their customers in real time.

Though knowing where your customers are and how they move is useful in itself, its true capabilities are revealed when it is married with other data elements, either captured internally or procured from an external source. What data you merge this with will depend on the question you are trying to answer, for example:

1. Can I provide custom recommendation to my customer based on where his friends visit? (social network data),
2. can I stock the right type of inventory which caters to my customer’s taste and preferences? (purchase behaviour), or
3. can I provide real-time promotion, which has a high likelihood to convert, to my customer when he/she enters my store? (browsing behaviour, one of many)

Note that the use of location data is not restricted in its use to target just your own end customer. Data captured internally can be supercharged with the location data and sold to other companies who can in turn leverage it for internal consumption. For example, retailers are interested in knowing who visits their stores, when they visit and how often – but they may also be interested in where a customer goes after he/she visit their store.

They may also be interested in how far they traveled to arrive at the store and the demographics of the location they stay. This will give them a deeper understanding of the customers’ behaviour and purchase patterns as well as what motivates or dissuades them in the long run. Marketers can also reach out to their existing customers’ circle of friends and acquaintances, thereby marking their potential future customers.

Data integration enables businesses to profile their customers extensively by closely monitoring and predicting customer behaviour. Valuable insights from customer data can be used by marketers to improve customer experience through a much more targeted and personalised approach. In short, it is all about staying relevant in real time by providing the right customer, with the right offers at the right time and in the right way. It would be a win-win situation for both marketers and customers.

However, data integration does not complete the picture. As with any technology, while there are obvious benefits, there are also challenges that need to be anticipated and duly addressed. There needs to substantial investment for the technology and analytics to remain valuable and sustainable in the long run. The enormous amount and variety of data generated over time will be overwhelming.

Additionally, collecting, storing, processing and enriching this data for analytics will require the right environment with suitably skilled professionals who not only have the technical know-how but also possess the right business acumen to derive actionable insights and contribute to business growth. Relevant systems employing a wide variety of techniques such as machine learning, text analytics and predictive modelling need to be established in order to extract relevant insights from location data. One of the more important issues that warrant attention in this regard today is the matter of data security. With all the diverse customer data being generated in diverse forms and at a break-neck pace, the question of importance how this data is utilised by those who wield the power.

A company that decides to implement a strategy to leverage location data needs to use the right framework and process to identify the right opportunities to pursue. It is very easy to get lost in the process and go down a rabbit hole with no end in sight. This framework will be different for different companies – depending on the industry that they operate in and the importance to maintain compliance around customer privacy in that industry.

Many companies across the globe have successfully begun to harness location data to enhance their customer experience, be it for providing location-based marketing offers, discount coupons or even weather alerts. When it comes to the power of location-based analytics, marketers have only begun to scratch the surface of customer satisfaction. In the future, location-based data can be successfully utilised for a variety of purposes such as incident prevention, delivery services, personal security, traffic management, crime analysis and more. There can be a cross-pollination of ideas across a wide number of industries, where the best business practices can be seamless applied for highest returns.

Vibhav Agarwal is a decision and data sciences professional, and Saumil Agrawal is an associate, at Mu Sigma.