Big Data is certainly no longer a new buzzword. In fact, this term has been circulating online for years and has been associated by many more with data collection than with the opportunities that data analysis brings. On the occasion of last week's Big Data Marketing Day at the C3 Convention Center, I would like to share my interest in this topic in the form of a small, not only fact-based but slightly philosophical contribution.
First, a definition of Big Data according to Gartner: < Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.
Data is the new oil
The collection and evaluation of data today follows the same principle as 100 years ago during the oil boom. The aim is to tap into as many sources as possible to generate profit. Just look at Google, Facebook or its acquisition of WhatsApp for $19 billion. This acquisition clearly illustrates the value of data. The goal is to evaluate a multitude of touchpoints and use the resulting data to create behavioural forecasts and subsequently derive new products and services. It is not without reason that the market research institute Gartner concludes that by 2017, marketing managers will be spending more money on technology than CIOs. According to Gartner, over 64% of companies surveyed stated that they were already investing in data analysis or intended to do so within 12 to 24 months.
From Big Data to Blockbuster
It is therefore not surprising that the BBC's British miniseries "House of Cards" became a huge hit with Netflix. Netflix excels at data analysis and, based on this evaluation, acquired the rights and built and won a new edition on data analytics. The days when intuition and creative work alone were the path to success are over – the future lies in Data Driven Marketing. A multitude of data (personal, anonymous, socio-demographic, Open Data) is brought together and analysed with the help of complex algorithms. These then enable personalised content, are deployed cross platform and cross device, increase penetration and encourage purchase incentives to boost conversions.
For those who might be a little puzzled, here's a small example. I visit an online shop which already offers me different products on the landing page than it does my friends, perhaps because I live in an area with higher purchasing power and access it on a screen with Retina resolution. Current offers in this shop are no longer based on the rigid output of data that is manually created and played out from the CMS, but rather they are dynamically displayed based on my interests, devices used, previous searches and current trends. Every shop owner, offline and online, knows that display space is limited. However, if you have the opportunity to equip the "shop window" according to the customer's interests and preferences, this naturally significantly increases the CTR and, if you do not make too many mistakes, also the conversion. Facts that Florian Lüft was also able to confirm at Big Data Marketing Day based on his experiences.
So, by now, no one will be surprised that House of Cards on Netflix does not just have one trailer, but hundreds. Fans of Kevin Spacey see trailers with him as the main character, while female viewers predominantly see the female characters. Hundreds of meta tags and the ability to track every action precisely enable Netflix to accurately analyse its almost 60 million users and provide them with the programmes they want to watch. If you would like to read another exciting article on Netflix and Big Data, I highly recommend the Wired article – Big Data Lessons from Netflix.
Individualisation as the A and O of the future
Let's take the online shop as an example again. We know from Google that a search never yields the same result for two people. This also happens in the shop, for example, through the individualized appearance and behaviour of the storefront. For instance, the options for faceted search (order of filters) adapt to my purchasing behaviour, prices are dynamically generated based on demand and surfing behaviour. The payment option I have used before is highlighted. If I abandon the purchase process and leave the shop, I receive precisely targeted advertising for retargeting on various networks, newsletters with individualized content, or SMS messages are sent to me. This depends on the desired intensity of penetration, although one should not test the customer's patience. Everyone can imagine the possibilities that still lie dormant here. Whether one approves of this or not, we will get used to it and perceive it as normal, much like impulse buys at the supermarket checkout.
Dynamic Pricing instead of Traditional Pricing Models
Firmly established pricing models are being overturned, whether in print media, billboards, or on the web. T-Systems, for instance, developed the product Motionlogic. This platform provides interested parties with anonymised movement data of its users for a fee (in Austria, this service will not be available until 2015 at the earliest). What has been happening in Great Britain for years through a consortium of several mobile network providers in this sector is still in its infancy here. Coupled with socio-demographic characteristics, such services can display visitor flows, traffic volumes and potential bottlenecks almost in real time. Not to mention the application areas when linked with other data. For example, in the future, it will be possible to assess how many people walk past a billboard or a shop window, their age structure, their purchasing power, and advertising can be flexibly adjusted accordingly.
Therefore, pricing models for outdoor advertising or print media will undergo a change. Previously calculated with fixed rates based on circulation and reach, in the future, billing can be based on almost exact visual contacts. This allows advertising spaces on displays to be booked in real time based on forecasts or the sudden appearance of target groups (real time marketing, real time bidding, programmatic buying are buzzwords to mention here). This change will probably lead to dumping prices and the disappearance of pricing models and some providers in a first step, but will regain a certain stability through premium offers and the possibility of auctions.
Data Protection and Misuse
Some of you will now certainly cry out and ask what has become of data protection. It is not only about data protection, but also how companies handle our sensitive data and what guidelines they are given. Yes, of course, rules are made to be broken. But it is primarily up to us. Every day we disclose huge amounts of data. Be it through our loyalty cards, phone calls, emails, at various supermarkets or coffee shop chains, through the multitude of social networks that we sometimes use carelessly, or purchases we make with credit or debit cards.
Media Literacy Required
It is more important than ever to know exactly what happens to the data you disclose about yourself. There are a multitude of possibilities regarding data misuse. Starting from unauthorised advertising calls to the takeover of an (online) identity (admittedly, a truly extreme case). The social aspect becomes problematic in the medical sector. Here, data misuse can lead to a multi-tiered healthcare system, an insurance company refusing a contract to a customer based on their sexual orientation, interests, or occupation, or offering it at extremely high conditions. In the digital world, information exists forever; it is not simply forgotten or misplaced. Politicians are more challenged than ever to prepare their citizens through education for the opportunities and protect them from the dangers that this technological change brings. Unfortunately, our politicians always react instead of acting. However, we must not rely on others, but educate ourselves and achieve maturity in this digital world.
Big Data as a Springboard to a Better World
But not only to address the potential in marketing and present the risks, I would also like to discuss the ecological and socially valuable applications of Big Data. Big Data is an opportunity to protect humanity from disasters, make life safer, and minimise crises. Flu epidemics can be detected early, ensuring sufficient vaccine supply in the region. Transport routes and capacities can be optimised, thus saving fuel and consequently CO2. Autonomous vehicles can safely chauffeur us around by evaluating a multitude of data. The course of a hurricane can be predicted, and people brought to safety in good time. Physical laws can be checked, climate forecasts modelled, or new particles found with the help of the LHC CERN.
How do you feel about Big Data? Collecting and evaluating data, yes or no? Do you actively protect your data by selectively disclosing information or encrypting your communications?
