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- 15. 1515Confidential © 2014 www.youtube.com/watch?v=41DflcblJz8
- 17. 1717Confidential © 2014 http://humanapi.co/
- 22. 2222Confidential © 2014 http://www.mindfully.org/Technology/2004/Creativity-Machine-Thaler24jan04.htm
- 23. 2323Confidential © 2014 Version B, the one with the bottom pop-up, increased home listings by 26.6% at a 95% confidence rate. http://whichtestwon.com/
- 24. 2424Confidential © 2014 www.bbc.co.uk/news/business-21640347
- 30. 3030Confidential © 2014 http://archive.ncsa.illinois.edu/Cyberia/NumRel/EinsteinTest.html
Hinweis der Redaktion
- So step one means facing your fears: plugging into the matrix and using your data But where will the data come from? I get enough reports already… Drowning in data…paralysed by it It doesn’t seem to be very useful – just lots of numbers What if it shows we’re not successful?
- The truth is that it’s easier than you think to get started, if you know where to look and there’s someone doing the looking. Here’s a little example I pulled together using a data source we all have access to – social media buzz data. 69,751 mentions of vacuuming on Twitter, in the english speaking world, over the last 3 months 11,793 of vacuuming mentions which also include the words “bug” or “spider” That’s a possible 17% of all vacuuming conversation online being about vacuuming up spiders so you don’t have to touch them. Fear of them crawling back out etc. This may not be a buying criteria for a vacuum cleaner. These people may not be in the market for one. Philips may not want to be associated with spider imprisonment. But this is an opportunity, one of many A bit random for sure – but have you ever had this thought? Would a focus group have uncovered this insight? A survey? I’ll put money on a piece of social media content using this theme outperforming the average by a significant margin. The process for uncovering this insight was partly manual and partly automated. An analyst noticed one or two people talking about this and thought it was funny. They created a search using the right keywords and then noticed the significance.
- The truth is that it’s easier than you think to get started, if you know where to look and there’s someone doing the looking Here’s a little example I pulled together using a data source we all have access to – social media buzz data. 69,751 mentions of vacuuming on Twitter, in the english speaking world, over the last 3 months 11,793 of vacuuming mentions which also include the words “bug” or “spider” That’s a possible 17% of all vacuuming conversation online being about vacuuming up spiders so you don’t have to touch them. Fear of them crawling back out etc. This may not be a buying criteria for a vacuum cleaner. These people may not be in the market for one. Philips may not want to be associated with spider imprisonment. But this is an opportunity, one of many A bit random for sure – but have you ever had this thought? Would a focus group have uncovered this insight? A survey? I’ll put money on a piece of social media content using this theme outperforming the average by a significant margin. The process for uncovering this insight was partly manual and partly automated. An analyst noticed one or two people talking about this and thought it was funny. They created a search using the right keywords and then noticed the significance.
- So what’s the playbook, the process – for starting to use data as a creative tool To gain insight on consumers, deploy creative marketing that engages or persuades them, testing it, measuring it – in one fell swoop?
- Importance of asking the right question. 42 & Douglas Adams. GIGO Increasing need to both fit the brief and make a creative leap that sets you apart. Role for data= finding the right questions. Why have sales of imported chocolate eclipsed those of local? (Rom) Why are our rooms empty for 4 hours a day? (Art Series Hotel)
- And there’s all these new sources of data out there that can act as a springboard for a whole new world of questions. Emerging sources of data – No longer just research and purchase data. (Human API. Hue) Application of all that data – (Formula E) Ideas that create data – Sometimes you need to bake data collection your your idea itself. (Disney RFID) Adding metadata – Borrowing data from elsewhere. (War Memorial)
- Human API – every new piece of hardware brings with it new data
- Formula E – teams with most social buzz get a boost in their real life race car in the real life race
- Disney MagicBands – personal location & payment data to the tune of a $1bn investment in data For visitors it means faster payment and a more seamless experience in the parks – everyone can book rides months in advance and turn up to be first in the queue at your time slot For Disney it means knowing what food restaurants should serve, when to add more staff to rides, when to have more characters wander around the park, and an opportunity to communicate with visitors after they leave based on their personal experience at the park
- Some small data about how people mentioned pizza over the course of they year showed a spike on valentines as those depressed without dates decided to stay home and order a pizza instead So we created a Tinder account for Domino’s
- Excellent use of learning algorithm + human personal stylist to manage personalisation at scale
- 99.9% of data produced is useless to creative process. So where do you find the real innovation opportunities? Answer: around the edges. Outlier data is the most interesting. (Mercury) Embrace problem data that makes us uncomfortable. Being daring and original with data. ‘Discomfort is the only sure sign that you are really exploring the foggy future that lies ahead’. (Barclaycard).
- Perihelion precession of mercury was an outlier that led to discovery of relativity by Einstein All the evidence pointed against his theory except for the one blip that proved it
- Our data showed BC customers didn’t know the details of their own contracts, they didn’t read the paperwork So we did away with the fine print, got to the point And once they were engaged we presented just the key information in an infographic at the bottom
- In practical terms, if you wanted to start harnessing data tomorrow, you need a process.
- Getting people to mobilise around data and turn it into action Means telling stories with it This can’t be done with just performance vs. KPIs You need a strategy that data optimises in real time
- Shameless plug This is what we do Turn strategies into data stories that are suddenly measurable and optimisable at every level (hue) And if you make them beautiful, people will share them (MINI) And if people want data and feel comfortable using it (and everyone’s using the same figures!), you’re halfway there
- Thanks