Traditional applications of big data may have been aimed at improving operations based on internal assets but a recent survey by The Economist Intelligence Unit (EIU) indicates that enterprises are shifting towards more market-facing initiatives using external data.
According to a report by The Economist Intelligence Unit, the rise in computational power and new data sources are allowing enterprises to experiment with “offensive moves” instead of confining themselves to internal operations. The report was based on a survey 300 executives in enterprises with more than US$500 million revenue.
On the offensive: Utilising big data for competitive analysis
The survey sheds light on an extremely noteworthy growth in interest in big data applications external to the company. Half of the respondents indicated that a competitive use of big data analytics – such as price optimisation, monitoring of competitors’ products and brands on social media and market share analysis – was of highest priority to their company.
This is a significant shift in how businesses use big data. No longer are they focusing only on “first-generation” internal applications of big data such as inventory management or streamlining of operations like customer service. There’s an element of self-defence to this approach, where businesses think that that smart usage of data could not only prevent them being left behind their competitors, but even help them seize the competitive advantage.
A case study: Providing competitive intelligence with consumer data
DataSpark’s own services offer a prime example of such competitor-facing initiatives. Leveraging the subscriber base of Singtel, Southeast Asia’s largest telco and coupled with their own GeoAnalytics solution, DataSpark is able to provide businesses with competitive intelligence about their own customers as well as those of their competitors.
This could be in the form of physical locations of consumers, their demographic profiles including age, gender, their place of work and residence, or even the travel patterns of locals and foreign visitors.
Whether it’s a service provider trying to understand their strongest catchment areas or areas overlapping with a competitor’s customer base to win over brand switchers or an event organiser looking to gauge movement patterns of crowds, DataSpark provides actionable insights across divisions such as marketing, sales and product development to optimise operations and identify new business opportunities.
For example, a 2014 study of 50 shopping malls in Singapore ranked the top 10 malls by footfall in the following order:
These rankings as well as other data like average time spent in malls and number of foreign visitors broken down by country provide valuable insights for retailers to make better business decisions like operating hours, new store openings and staff resourcing.
At the same time, DataSpark understands the responsibility that comes with possession of such data and ensures privacy of customers by anonymising and aggregating the data before analysis.
As more enterprises seek new ways of using big data for market-facing initiatives, DataSpark’s role as a trusted provider of competitive intelligence will become more crucial than ever.
For more on how big data is being used by businesses for newer applications, get in touch with DataSpark today.