I am sitting at Sydney Airport on my way to Silicon Valley, where I will be participating in a strategy project at Stanford University on the future of big data and consumer privacy. In an age where Sony Playstation accounts are getting hacked, Facebook and Google are under increased scrutiny by the EU (in particular), and someone is watching every move you make, and every breath you take via Nike Fuel and your mobile devices, big data is big business. The question is how to monetise it, and how to do it in an ethical and non-invasive way.
Here are some of my initial thoughts on the topic - feel free to add your own or comment on how you think big data will impact consumer privacy in the future.
Definitions:
For background of challenges Big Data and your Digitised Self poses (video):
Both of these retailers use big data and consumer insights for marketing purposes. Think of how your Qantas FF is linked to your Everyday Rewards Card, which in turn might be optimised for spend together with your Woolworths Qantas Everyday Rewards MasterCard. MasterCard, Qantas, and Woolworths in cahootz, all having access to various pieces of your consumer habits. This means that they can tailor ads to you via digital and traditional mail. It also means they can on-sell this info to other vendors, if you have agreed to this in your contract, or been sloppy about protecting your privacy. Data crunching enables the retailer to know that when someone starts buying Pampers, more than likely this household will also start buying more beers for home (the bloke doesn't go out for beers at the pub with his mate as often), and thus send tailored offers for Pampers and Boags in the same mailout.
Banks are data miners. McKinsey has found that certain banks have doubled the share of customers who accept loan offers, and reduced loan losses by half as a result of targeting customers more closely. Standard Chartered offers cheaper rates to its customers who have several Standard Chartered products, because it figures that the additional data about its customers will enable it to minimise its risk in its loan portfolio. Lloyd's Bank is enabling a system telling its customers how much money is in their bank accounts, but also through predictive modelling how much money will be in there once all the regular bills are paid. Bank Santander is sending out lists of potential customers to its branches each week for cross-selling of financial products, but also non-financial products from partners based on the customer data it has. Singapore Citibank offers discounts at retailers and restaurants based on the unique consumption habits of its customers, and collaborates with data crunchers in Singapore and Bangalore to ensure tailored offerings based on psychographics.
What do you do with all the big data? The key is to turn data into information, and then into knowledge / insights. Gatorade's Mission Control is a good example of this. It is worthwhile checking out this video for a view on how it visualises information from the social media data it gathers from around the world, and how this impacts how its branding and marketing department is able to reach insights from the patterns of conversations around the world. Another leader in data visualisation and insights is Shazam - the mobile app which recognises music from radio, in pubs, or nightclubs. It has now hit 2 billion downloads. It uses the data about mobile consumption patterns and searches/tags to deliver targetted ads directly to your mobile phone based on your location and search patterns - for example, it might tell you that a band that you have tagged is coming to town, and it would collect a commission by sending you to MoshTix where you can buy tickets. Even more interesting is how it sells data to music companies, agents, and third party vendors who are interested in what artists are hot, how PR or radio interviews impacts tagging in specific geo-locations, and use this data in their analytics and promotions via Shazam and other engagement channels.
An interesting infographic to dig deeper into...
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