Data on the couch: how analysing customers gives companies the edge
Digging for victory
It used to be that quality and price were the key differentiators but increasingly these days organisations are relying on business analytics – the methodical exploration of the organisation’s data to measure performance – to deliver competitive advantage.
The original poster child for business analytics is the Tesco Clubcard customer loyalty scheme, which has been so successful that there is even a book about it.
Launched in 1995, the Clubcard is widely cited as one of the main reasons for the supermarket chain’s dominance of the UK grocery sector.
The loyalty scheme allows the supermarket to adapt quickly to customers’ changing likes and dislikes by analysing the contents of their shopping trolleys: you are buying baby food so we will offer you a promotion on nappies; we can see you have a dog so here’s an offer on pet insurance; and so on.
The real thing
The possibilities of business analytics are endless. By scrutinising customers’ habits businesses can optimise the value they derive from them and personalise the customer experience: bank customers can be differentiated based on usage or credit risk, insurance products can cross-sold, inventory levels and delivery routes can be optimised.
Coca-Cola’s rewards scheme, for example, allows customers to collect PIN codes from all of the company’s products and trade them for points which they can then spend on rewards or entering online competitions.
Customer data is used to personalise web pages and send out exclusive offers. The company says that about 285,000 visitors a day enter seven codes per second onto the rewards site.
Of course business analytics software has been around for many years, but now the game is changing.
Time was when the limit of an organisation’s ambitions was to extract data from its various business systems and then store it in data warehouses or data marts in a wholly structured way. The data was integrated into relational databases, then the business intelligence models developed and analytics performed on a small sample set of data.
But there has been an explosion of data in the last couple of years. According to IBM, we create 2.5 quintillion (or 10 to the power of 18) bytes of data very day, and 90 per cent of the data in the world today has been created in the last two years alone.
Any forward-thinking enterprise now wants to include all the unstructured data available to it in its decision making: that means every email, RFID tag, note, blog post, colour of the web page and anything else that won’t fit into a spreadsheet.
If all this data is harnessed then the analytics can be much more refined – but the ability to manage such vast amounts can become a limiting factor.
The big IT vendors are jockeying for position
The big IT vendors all recognise the importance of business analytics. They are jockeying for position and there has been a wave of big data acquisitions.
IBM has bought a tranche of companies in the data analytics arena to “close the gap between strategy and execution”.
Most recently, it agreed this month to buy Canadian risk analytics firm Algorithmics for $387m, and last month bought UK-based i2, which provides intelligence and analytics for crime prevention and fraud.
IBM also paid $1.7bn for Netezza 12 months ago, adding the data warehousing company to a portfolio which includes Cognos and SPSS.
Similarly HP, in its shift away from commodity hardware, is in the throes of buying the UK’s largest software company Autonomy, paying £7.1bn for the pattern-recognition “meaning-based computing” company. And it bought data analytics firm Vertica in the spring.
The game is also changing because business analytics tools are becoming more sophisticated and accessible.
Doug Cutting created Hadoop five years ago after some Google technical papers showed how Google split its databases up into small chunks and spread them through lots of cheap computers rather than storing them on a few expensive machines.
Hadoop mimics this technology so that users can sift through vast amounts of data quickly and cheaply, and there are no end of start-up businesses now adopting the Hadoop method and trying to make it easier to use.
What does all this mean for the corporate IT shop?
As these big data acquisitions are integrated and vendor methodologies and sales pitches are refined, management enthusiasm for the possibilities of closely predicting the corporate future can only increase.
And we can be certain that the corporate IT shop will be asked to do more, and do it faster, than ever before. ®
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