Some four years ago, I was chatting to the head of a large data company, who was complaining that he had, on average, over 80K pieces of transactional data per supermarket customer. Taken at face value, that sounded terrific. But his difficulty was in understanding what was significant and what was not, so that he and the client could identify and use the relevant data quickly and effectively. As I started speaking to more businesses, I heard this theme again and again – even Debt Collection Agencies found they just had too much data and not enough time to be able to understand how to find and apply the useful key data to improve their results and ROI.
The Three ‘V’s
Even in the few years since then, volumes of data have simply exploded – Analyst Doug Laney described it accurately as being three-dimensional – a combination of volume, velocity and variety. His terminology is now widely used.
Big Data began with consumers shopping over the internet. Businesses started to save and analyse data from clicks, searches, registrations, purchases. Of course, having collected the data, many companies were quite clueless about how to analyse and use it. But those who looked further ahead, like Amazon, were able to harness its power to gain market share against their competitors.
And the situation has developed further. More recently, consumers have discovered other uses for the web and smartphones – they use social networks where they post personal and business information about themselves, they link and hold conversations with their friends, family and colleagues, they post updates and information and photographs and music and films and videos and reviews and … the sky (or should I say cloud) is the limit. And the data they are so happy to provide is available for marketers and businesses if they’re ready to take advantage of it and can cope with its relatively unstructured nature.
Combined insight: Big Data plus traditional data
Data has always been used extensively by consumer-facing businesses to segment and target customers. But Big Data demands a more agile approach towards engaging customers, and providing a more personal or tailored shopping experience. Combining Big Data with the traditional purchasing and customer data previously used by business offers a massive opportunity to gain three-dimensional insights into consumers – whether for marketing purposes, product development, or customer service and management.
Forward-looking businesses and retailers will track an individual’s behaviour, including product or offer preferences, and model – in real time – that consumer’s likely behaviour. While the customer is shopping, the business will be able to offer appropriate upsell products, loyalty programmes and increase spend and loyalty much more effectively than any competition who fails to take advantage of the opportunity. The retailer will know when it’s safe to offer credit and on what terms; they’ll know what the consumer wants and will be able to choose how … or whether … to deliver those needs.
Big Data Benefits
And the benefits are not just limited to retailers. Telcos, media companies, utilities, energy providers; insurers and aggregator sites – Big Data allows genuine communication between provider and consumer – and the consumer is beginning to understand this, and take advantage of opportunities to “switch” providers or suppliers or retailers so that they interact with those who understand their needs and wants, and are prepared to engage with them on that basis fairly and openly.
Big Data Big Issues
As ever, Big Data has its difficulties as well as opportunities. There are concerns about data security and data privacy. And not least, concerns about the ability to analyse Big Data –reflected in the growing number of software firms who specialise in data management and analytics – growing at almost 10% per annum – which is roughly twice as fast as the software business as a whole. According to McKinsey, by 2018 as many as 140,000 to 190,000 additional specialists with deep analytical skills in Big Data may be required.
And there’s a Big Data technology revolution too – Big Data will need new and different technologies to allow efficient data processing swiftly enough for the data to be deployed effectively in realtime, such as MPP (massively parallel processing) databases, the Internet, and cloud computing platforms.
So where will Big Data go from here … interesting times! And whether you’re a marketer, a data provider, a software business, or an insight and analytics business, those who adopt an agile, creative approach to the issue will be the overall winners.
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Victoria Tuffill is a direct marketing consultant with over 30 years experience. She founded Tuffill Verner Associates consultancy with Alastair Tuffill in 1996. She is also founder and Director of Fraudscreen – a data tool that assists in the prevention of 1st party fraud. Her experience ranges across businesses including publishing, home shopping, insurance, utilities, telcos and collections.
© Victoria Tuffill and Tuffill Verner Associates, April 2012. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Victoria Tuffill and Tuffill Verner Associates with appropriate and specific direction to the original content.