Why retail should buy into 'Big Data'

Retailers should embrace big data and analytics to help eliminate the guessing game. Why speculate about what customers want, when the trends and numbers can tell you exactly what's in vogue.

These days an organisation must have information if it wants to improve customer experience.  It needs feedback from customers and it needs internal, operational information if management is to fully understand how service delivery affects the customer experience, performance and future behaviour. 

Finding raw data to work with shouldn't be a problem.  These days there is a proliferation of customer experience channels generating vast amounts of data.  Every call to the contact centre, every service request, every visitor to your website and every time a product is shipped contributes to the store of available data.   The difficult part is bringing all this data together in a way that facilitates analysis.  This is where Big Data comes in.
Big Data is a relatively new concept and there are many definitions, but how we describe it is this:  Big Data analytics is the process of examining large amounts (volume) of data of a variety of types (big data) to uncover hidden patterns, unknown correlations and other useful information. Used in real time, (velocity) such information can provide competitive advantages over rival organisations and result in significantly improved customer experience leading to increased revenue.
Perhaps the simplest way to think of it is data mining on steroids.  It occurs at a massive scale, peering into the data accumulated across every arm of the organisation.  Big Data analytics combines data from customer relationship management databases, contact centres, web site visits, service systems and more to enable analyses in ways previously thought impossible. 
The potential rewards from tapping into all of this data are substantial. For example, within months of the Commonwealth Bank beginning to search its Big Data for patterns relating to fraud and financial crime, the organisation had improved its ability to identify cheque and Internet fraud, increased fraud detection efficiency, and significantly improved its reduced fraud loss-to-turnover ratios.
At eBay, Big Data is used to improve the experiences of around 180 million active users by optimising searches to deliver more relevant results. It identifies commonly requested features to help narrow the results, and caters for commonly misspelled words. 
In the US, the department store chain, Target, uses Big Data to reach specific customer segments with special offers and promotions. (Mind you, sending coupons for baby and pregnancy-related goods to a teenage girl before she'd had a chance to inform her parents of the impending bundle of joy may not have been such a good idea!)
There are some basic requirements
If you plan to embark on a Big Data strategy you will need to have people with both mathematical modelling and computer science capabilities. And these people are hard to find. You will also need to assemble a cross-functional team which can have access to the right data.  This may involve navigating a way through departmental silos.  
The other key requirement is a knowledge of the technologies involved. You will hear a lot about Hadoop, Cassandra, Apache, Teradata, SAS and many others you will never have heard before.  Navigating your way through the layers of Big Data applications may require external advice. 
Most importantly you will need to align your Big Data plans with business objectives to ensure the information you derive has business value. 
But do remember, Big Data is best used for answering questions you didn’t know you had.
Enterprise feedback management

Creating a mechanism for the ongoing collection of customer feedback should be the starting point for any customer experience improvement program.  This is best achieved using enterprise feedback management, a process defined as: the systematic collection, storage and use of customer feedback data that covers all customer interaction channels at the customer level, to enhance business objectives and overall profitability.

In 2012, a study by Fifth Quadrant found that approximately $90 million is spent on customer experience research every year in Australia.  It amounts to a staggering ten per cent of revenues for the total market research industry.  Yet only 78 per cent of organisations have a customer experience feedback program in place.
Imagine how much better the customer experience would be, and how much closer relationships could become, if more organisations decided to really listen to their customers; if they established enterprise feedback management programs that sat alongside and fed into big data mining programs.  
We've entered an era in which consumers hold the power.  Rather than simply accepting whatever products, prices and conditions their local retailer can offer, they are using the weight of their numbers and technology to redefine the rules of engagement. Organisations that wish to compete need to cultivate their relationships. We have to be smarter in the way we communicate, more precise and more targeted in our engagements.  It's not hard to see that soon, success will rely on an integrated customer analytics strategy that puts quality data in the hands of decision makers. 

Dr Catriona Wallace is the CEO and founder of Fifth Quadrant

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