Hello!!Mark Brill !

@brillthings!!

[please make some big data]!

What  the  hell  is  this  guy  looking  at?  The  World  or  something?  

This  picture  was  trending  on  Twi8er  earlier  this  year  and  it  pre8y  much  sums  up  mobile.  The  default  mode  is  that  we’re  on  our  smartphones.  The  odd  one  out  is  the  guy  who  is  just  looking  at  the  world.  

-  Phone by your bed?!-  Check it first or last thing?!-  Share your phone with anyone?!

Another  way  to  understand  mobile  is  to  think  about  your  own  usage.  It  is  always  there,  always  on  and  a  highly  personal  device  that  is  rarely  shared.  

All of this means is that mobile is generating vast amounts of data. And as we become even more mobile that’s set to explode. This year, mobile is set to overtake desktop usage globally, although in some countires such as India or China that’s already happened. !

More photos sh`ared than Facebook – 400m per day  

More messages sent than SMS – 64 billion per day  

Mobile  is  also  a  fast  changing  landscape.  Here  are  two  examples  of  a  current  shiE  in  usage.  

comScore, US, April 2014  

It’s also happening in social, where it is now pretty much a mobile channel …  

2 x more shares!3 x more active!Facebook, 2013, (reported by TechCrunch)  

And mobile users are more active than desktop, generating yet more big data through likes, shares, Tweets or updates.  

1.67  

This number is interesting in the world of social and big data …  

By analysing messaging data, Facebook have found that two people will send an average of 1.67 messages per day, shortly before they start a relationship.!h8p://www.hashslush.com/facebook-­‐new-­‐relaIonship-­‐guru-­‐town/  

How much is your !data worth?!

Jacopo Staiano, University of Trento, 2014"

This is an interesting experiment by an Italian academic. A virtual market was created for mobile data where users placed bids. It’s useful to see that location and call data was valued the highest. It tells us what matters most to consumers when it comes t data,  

Active | Passive!

We can split the type of data from mobile into two types. ‘Active’ is data generate through social media or as a registered user. Few people realise how much passive data there is though. It includes app analytics, location data or other background activities such as phones sniffing out WiFi.  

Attribution!

There aren’t many great examples of brand use of big data in mobile. This, though, is a good example from M&S. They are able to attribute their mobile (and for that matter, social) activities by linking registered users to their M&S cards and can use big data to track spending and therefore the ROI of each channel.  

Passive Data!

The operator marketing message channel make use of passive data, such as roaming on handsets, to identify target audiences for brand campaigns.  

Presence  Orb  

Presence Orb used passive data from smartphones automatically searching for WiFi signals. They installed units in recycling bins in the city of London. By grabbing mac address they were able to track users as they moved around the city.!Although there are some great brand benefits, there was something of an outcry about the system and it was withdrawn from the City of London.  

Being Useful!Perhaps the best thing brands can do is to consider big data as a means to deliver a better service, and be more useful to customers. The following examples show how big data from mobile devices has been useful in developing economies.  

In Kenya, the movement of phones around a network has informed the movement of people and therefore mosquitos. This allows them to identify the optimal areas for a vaccination programme.  

Elsewhere in Africa, big data on mobile phone top ups has been used to identify areas of wealth and poverty. It has also helped identify unexpected areas of wealth suggesting high levels of corruption in those places.  

In Haiti, Swedish researches were able to track phones entering the disaster area and those that had left. By doing so they were precisely able to measure the number of people affected by the disaster.  

What’s Next?!

And after mobile comes connected and wearable devices. With the proliferation of these new forms of computing more data will be generated. Think of the life logging trend as an example.  

However, we need to take care with this. Google Glass for example generates a vast amount of passive data, including eye-tracking. !!http://www.dmamobileblog.org.uk/2013/07/24/google-glass-a-less-private-future/  

Maybe we can flip the idea of big data around. Here’s an example where the considerable computing power of smartphones can be harnessed to do good. Whilst we are asleep, this app processes medical data to help fight disease as part of a large grid computing system.  

Mobile data is powerful.!It is also personal.!

Understand your users, gain trust and be transparent.!

Mark Brill!@brillthings!mark@formatie.com!