Is all that Data making you fat?
In Iowa Knee-high by the 4th of July means they are expecting a bumper crop of corn. Now I enjoy an occasional corn-on-the-cob as much as the next BBQ-goer, but corn probably isn’t top of mind when it comes to my all-time favourite food groups. And yet it’s everywhere in pretty much everything we consume.
It has been estimated that there are 45,000 items in the average American supermarket and that ¼ (more than 11,000) of them contain corn. Whether it’s used as a sweetener (high-fructose corn syrup — HFCS), a preservative (citric acid) or a golden colouring (xanthan gum). There’s a very good chance that any processed food label you read will have some corn-derived ingredient in it. Non-food items aren’t exempt either, from toothpaste & cosmetics, right down to the shine on the magazine that catches your eye at the checkout (Pollan, 2006).
This is ‘industrialised food’, is part of a chain that stretches from farm gate to fast-food outlet. Where the provenance of your food is complex or obscure. There were a couple of key plays that led the humble corn cob to industrial giant. First breeders figured out how to restrict reproduction — the biological equivalent of a patent. A boom in post-War synthetic fertilisers (re-purposing surplus explosives-making ingredients) enabled farmers to grow vast quantities of corn without depleting the soil. Then a spike in 1970’s food prices saw a change in subsidies (farmers were paid USD$0.50 a bushel of corn) (Pollan, 2006). Corn supports agribusiness, leveraging cheap ingredients into high profits. Corn is cheaper than sugar, so HFCS replaced it as a sweetener in soft drinks in the 1980s. Corn stripped to its building blocks and reassembled is now the source for most food additives. Which sadly for most of us means that the cheapest calories in the supermarket tend to be the unhealthiest.
In my last blog Spice Wars — a lesson for our digital economy? I talked about data as a commodity and the colonisation of new markets in order to obtain a monopoly on the ‘raw material’ — personal data.
But a raw material in and of itself isn’t that useful. So just how do you take this new globalized ‘raw material’ and make it ‘value-add’ for different types of usage? We are now in an age of industrial data, where data is used as a commodity, re-formed and re-shaped into other types of products.
Netflix is a master at this. The largest provider of commercial streaming video programming in the US
Netflix doesn’t know merely what we’re watching, but when, where and with what kind of device we’re watching. It keeps a record of every time we pause the action — or rewind, or fast-forward — and how many of us abandon a show entirely after watching for a few minutes
(www.salon.com How Netflix is turning viewers into puppets)
Netflix is using its Big Data to drive a creative strategy, to commission programmes, to select lead actors and directors and to predict audience size. It means advertising becomes cheaper as the target audience has already been identified.
Through our algorithms we can determine who might be interested in Kevin Spacey or political drama and say to them, ‘You might want to watch this. (www.salon.com How Netflix is turning viewers into puppets)
In one slightly disturbing headline this week we were told that 75% of the world’s most popular websites track users (up from 5% 18yrs ago). So what data are they tracking, how and what are they doing with it? Oftentimes websites use third-party trackers whose code tracks your online behaviours. The data collected by third-party brokers is then sold on to others.
In the online world, this type of targeting is now commonplace. Advertisers use all sorts of data to target their messages to specific types of users, including financial and demographic information, context and location, and users’ previous behaviours.
(Digiday, How Has Advertising Lived Up to ‘Minority Report’?)
Every wondered why a casual search for new winter jacket on Google sees you bombarded with clothing company ads the next time you are reading an online news site?
In a 2016 context, Pokémon Go is the game du jour. A spectacularly successful augmented reality game — players to walk around looking through their smartphone cameras, waiting for them to show an image of a Pokémon superimposed onto the real world they are standing in. The aim is to capture 150 different varieties of the ‘creatures’ with a phone gesture. The game has been a sensation (the games market worldwide grossed $6bn in May 2016), putting 25% on the value of Nintendo (The Guardian view on Pokémon Go: augmented merchandising). Not bad for a ‘free app’ with in-app purchases of extra items and features. But that’s really just the tip of the Pokémon iceberg. When the game launched in Japan last month it had a launch partner tie-in with McDonalds that will see its 3,000 plus fast food restaurants across Japan become gyms for would-be Pokémon collectors.
A sponsor can create “gyms” — where Pokémon can be battled or trained by gamers — at their retail store or locations, a move that could drive real-world traffic and potential sales to their business
(TechCrunch, Pokémon Go will launch in Japan tomorrow with game’s first sponsored location)
This isn’t just a Japanese phenomenon, for a spend of just NZD $130 the Christchurch City Council purchased some Pokémon Lures (where businesses pay to have Pokémon show up at their premises) which increased foot traffic to their New Brighton Market by 500–1000 people (RNZ, Businesses pay to lure Pokemon Go fans).
But what about the data? When you download the app, the standard T’s & C’s allow the game to collect your email address, IP address, the web page you were using before logging into Pokémon Go, your username, and your location. And if you use your Google account for sign-in and use an iOS device (unless you block it) access to your Google account. It also may share this information with other “third parties” to conduct “research and analysis, demographic profiling, and other similar purposes.” Other location-based apps like Foursquare do similar things (Buzzfeed, You Should Probably Check Your Pokémon Go Privacy Settings).
As companies go from product-driven marketing campaigns to ever more personalised and niche offerings, they can only craft these by knowing more and more about us. So rather than out-bound mass market campaigns, companies are using our in-bound contact with them and the data that produces to create the ‘next-best-offer’. Where that data is partial or non-existent they can purchase data from third party brokers. One of the newer technologies in this area is Beacon Technology
Beacons employ Bluetooth low-energy (BLE) wireless technology to pinpoint the location of customers in stores and other places and to deliver messages to their mobile devices. Specifically, a beacon emits a BLE signal that a retailer’s or other company’s app on a smartphone coming within range of that signal can pick up on (www.forbes.com Beacon Technology: The Where, What, Who, How and Why)
In this way customers are authenticated which means a ‘tremendous customer experience’ — your hotel room key is a beacon, you can be offered a seat upgrade at the stadium and an airline can track your flight connections. It also means the retailer can gather even more data about you.
In the industrialisation of our food chain we saw ownership through patents, technology advances enabling increased supply, cheap product undercutting more expensive alternatives and more and more creative ways to utilise the cheap product components in ‘value-adding’ activities.
A similar set of factors have grown up around data usage. Standards and patents are the lifeblood of innovation in the global knowledge economy, enabling data transfer, knowledge exchange and interoperability (Ernst, 2014). Cloud computing, cheaper storage and increased digitization mean that there is ever more data and keeping it and using it is also cheaper than ever before. By moving to a knowledge economy we are in a constant flux of high-level information between ever-changing partners (Memmi, 2015).
To go back to our corny beginnings, before industrial food we had pastoral food. It was labour intensive and didn’t scale. Your local greengrocer knew you by name, asked about your family and knew you had a weak spot for in-season asparagus. Now your supermarket swipes your loyalty card, knows where and when you shop, your average spend and every item you buy, in order to provide you with enticements to spend more.
One reason why less sophisticated consumers may not be benefiting as much as they could from big data is that they often lack knowledge about how businesses are using their information; they are dispersed, unorganized and uninterested in exercising their democratic and political rights. They lack the ability to respond to marketers’ unfair or deceptive information collection and use practices.
(Kshetri, N., 2014, pg. 1142)
Next time; what are the implications for privacy when there are no boarders and when we have no knowledge of aggregation routines which take our raw data and use it in other ways? Should we concerned about this and are we even aware of the trade-offs?
References:
Ernst, D., Lee, H., & Kwak, J. (2014). Standards, innovation, and latecomer economic development: Conceptual issues and policy challenges. Telecommunications Policy, 38(10), 853–862.
Kshetri, N. (2014). Big data ׳s impact on privacy, security and consumer welfare. Telecommunications Policy, 38(11), 1134–1145.
Memmi, D. (2015). Information technology as social phenomenon. AI & Society, 30(2), 207–214.
Pollan. M., (2006) The Omnivore’s Dilemma: A Natural History of Four Meals. New York. The Penguin Press.
