First came 'pure play' internet companies like Amazon and eBuy, then 'bricks and clicks' came along. Today, in retailing especially, online is about the only bright spot and for most customer facing companies 'multi-channel', face to face, phone, online, mobile, is now a must.

The challenges of multi-channel are well known. Customers increasingly expect to be able to jump seamlessly from one channel to another, but actually providing this seamless experience is a massive operational and data headache. Given the penalties for failing to achieve this (basically, loss of customers) and the contrasting upsides – a reputation for service plus…

The BBC’s report Do you have the right to be forgotten online gives a really good overview of the new European Data Protection legislation, its aims to put people back in control of their personal data and what it means for consumers. “Companies can’t go foraging for data in the wild and pretend that what they find is theirs. The big idea at the heart of the new directive is that personal data is...personal’.

The report features the great new video released by the European Commission this week warning people that they could be sharing more than they…

Following the recent London Green Hackathon, the winning hacks have now been announced. It’s inspiring to see what a few ingenious minds can create over a weekend using only data that’s freely available. When organisations start releasing customer data in a portable, reusable way (for example, as part of the Government's midata programme), innovative applications will offer much, much more. The Department for Business Innovation and Skills, which is running the midata programme, supported the Hackathon to get a flavour of just what kind of innovations the future could hold.

The data used in the hackathon…

In theory, there need not be a contradiction between Big Data and privacy. If you take a medical record, bank account or individual's mobile phone location data you can remove all personal identifiers (name, address, customer number, IP address, mobile phone identifier) so that all you have is a bundle of attributes which you can crunch together to identify patterns and trends *.

Having identified a pattern or profile you can then match it back to an individual's data, to place the person in a segment, to predict what they might do next, or perhaps offer them 'people like you'…