Got Big Data. Now what?


Just when we were getting comfortable with established ways of gathering and analysing information to understand customer needs, Big Data has arrived to change the rules of the game. So how can Big Data and analytics help organisations transform their engagement with customers, suppliers and partners?

Added on 22 April 2015 by Mike Cooray

Got Big Data. Now what?

1. ‘Precise’ customer preferences

Big Data analytics gives organisations the ability to predict emerging trends and assess how they can be turned into profitable business initiatives. Analysing data generated through platforms such as social media and user broadcasting channels, for example, gives companies the opportunity to use predictive modelling to design new products that stay ahead of competition. This is particularly prevalent in the fashion, accessories and footwear industries where trends ‘come and go’ at a higher frequency.

The more accurate the data, the better the decisions can be. By understanding consumer preferences, organisations are better able to decide on the type of variants and product choice to offer.

2. Product Personalisation

Big Data allows organisations to personalise their products and services – a move which is seen as the Holy Grail of business. This is particularly valuable in hypercompetitive sectors where companies go head to head and need to find ways of creating clear points of difference. Companies that are in a position to personalise their market offer can consequently command a price premium.  Efforts are being made in several industries to achieve individual personalisation, including beauty and make-up, automobile, airlines and mobile phone operators.

Individual personalisation is also evident in the insurance industry. Aviva, for example, allows customers to download their Aviva Drive app, which monitors and tests their driving using GPS. The data collected from the Drive app leads to a personalised discount depending on driving performance.

3. Customised Experiences

Big Data can also be used to create customised experiences in real-time according to the situation and customer preferences. Real-time analysis provides new opportunities for marketers to engage with customers, provide a more satisfying experience and deliver ‘memorable moments’. Disney’s MyMagic+ lets visitors use RFID MagicBands as their ticket, hotel room key and credit card. By analysing the real-time data generated by visitors, Disney not only customise the visitor experience but can also develop operational efficiencies by managing visitor traffic and staffing requirements.

Real-time data analytics are used by many other organisations such as concert organisers and Formula 1 racing teams. The key is to customise the experiences that have an impact on customer engagement, loyalty and advocacy.

4. Collaborative Partnerships

Businesses can enhance their competitiveness by collaborating with partners to achieve win-win outcomes. American Express, for example, collaborates with other partners such as British Airways (BA) to provide enhanced customer experiences. American Express BA cardholders can convert retail purchases into air miles. Customers who make purchases over a given threshold receive a free annual companion voucher that can be used to buy a free flight to any destination.

These collaborations can only be successful if companies are able to capture, analyse and extract relevant data sets from clusters of Big Data effectively. The Wimbledon tennis tournament organisers collaborate with IBM and other tech sponsors to gather real-time on-court and player analytics to intensify the engagement with millions of tennis fans watching across the world.  Collaborating organisations must be in a position to share information to provide enhanced product and service bundles that customise their offer. The challenge is to use Big Data to benefit, not only by increasing sales, but also by enhancing brand equity and perceived association through customer engagement.

5. Brand Extensions

Many organisations hold large realms of data, but are unable to analyse them in a way that leads to brand extensions.  Those who can analyse internal and external data effectively can consider launching new brand extension ventures that are both profitable and strengthen their brand presence.

Organisations such as Volkswagen (VW) have not only amassed a great group of automobile brands together including Audi, Porsche, Bugatti, Scania and Ducati, but have also launched highly profitable business extensions such as insurance and financial services in addition to their core business. Over 10,000 data technicians constantly crunch Big Data at VW’s Big Data Labs to drive business growth and innovation.