It is estimated that by 2012, the number of active mobile data users worldwide will exceed 680 million, which is a whopping 900% increase over 2008.
It is estimated that by 2012, the number of active mobile data users worldwide will exceed 680 million, which is a whopping 900% increase over 2008. Shifting from basic voice and SMS usage, consumers are increasingly embracing the world of the internet on their portable devices. Consequently, mobile data now represents the key growth avenue for mobile operators.
With faster networks and smarter smartphones, there is a growing demand for new services. Application stores, social networks, and instant messaging services are added to traditional data services such as email and internet browsing, to
satisfy subscriber requirements.
As a result of this shift in usage, subscriber behaviour becomes more sophisticated and usage journeys more complex. Understanding usage patterns across these multiple services is becoming a strategic necessity for operators who wish to maximise Marketing RoI, whether it’s for acquisition, up-sell, or retention.
Marketing challenges
At an operational level, this poses heightened challenges for marketing professionals who need to:
- Optimise service pricing and handset subsidies
- Identify an optimal combination of services for each device in the portfolio
- Introduce new and innovative mobile applications adapted to the device portfolio
- Achieve dynamic campaign management via timely device metrics and analytics
To overcome these challenges and drive growth and profitability, marketers need powerful analytics and effective segmentation that takes into account the complexities of multi-service, multi-application, and multi-device environments. To achieve effective segmentation, mobile operators need to be able to link three dimensions:
- Individual subscriber profiles
- Device characteristics
- Detailed service usage information
Marketers need this information not in independent silos, but in cohesive data sets that can be analysed along any of the three dimensions. For example, marketers need to measure usage for a specific service among a specific subscriber group, with a specific device. Also, there could be a need to measure which subscribers correspond to a specific usage
pattern with a specific device.
No shortage of data
Mobile operators do not suffer from lack of data. They have access to network data, systems and billing data, and third party data, to name a few. However, to achieve this three-dimensional picture is difficult. Operators typically know how
much data each subscriber has consumed in a month, but most can’t break it down by service or application. Information from billing systems often lacks the necessary granularity to perform comprehensive usage analytics across data services.
As a solution to these obstacles, a new category of analytics is emerging based on probes designed specifically to look at all data services and to deliver segmented information straight to marketing professionals. It gives mobile operators the ability to deploy sophisticated data analysis capability within weeks (as opposed to months when using a traditional Business Intelligence approach) and with unprecedented levels of data accuracy.
Using this new approach to mobile data analytics allows operators to achieve the following:
- Device Use & Functionality Trend Analysis – creating concise visual representations of subscriber device activity and trends.
- More Predictive Analytics and Less Reporting – achieving dynamic analysis and predicting future activity versus reporting legacy data and results.
- Data & Protocol Mining – having access to detailed analysis for all data passing through the network and segmenting it into targeted categories.
The growing demand for new services has caused user behaviour to become much more complex. Understanding this behaviour, along with effective segmentation, is more crucial than ever before. The challenges that marketers face in effective segmentation can only be achieved by linking three key components: individual subscriber profiles, device characteristics, and detailed service usage information. Furthermore, utilising a probe-based approach to analytics, which is not dependent upon numerous sources of information data, will provide operators with the comprehensive analysis necessary for efficient segmentation.
Mobile data analytics is a critical piece of the data puzzle that will unlock the potential of analytics and drive increased revenue and profitability.
 | The authors are Stephen Kerwick, executive director, Marketing Science & Analytics at Neuralitic (pictured above) and François de Repentigny, director – Product Marketing at Neuralitic |
