ilive2014 presentation | casper blicher olsen - internal barriers from taking action upon data - and...
DESCRIPTION
While clients are consuming more and more data, crucial business insights get lost in a sea of pixels. In his presentation Casper will discuss how different data visualization concepts and organizational techniques can be applied to the analytical processes to better help organizations integrate actionable data best practices the influences change and create business value. iLive2014 attendees can expect to get another view on why their current digital marketing indicatives sucks, and what they can do about it.TRANSCRIPT
Barriers preventing action-oriented analytics - and how to overcome them
!Casper Blicher Olsen
v2.0
Barriers preventing action-oriented analytics - and how to overcome them
!Specialists in motivation the users online
• Digital strategies, analysis and data visualisation • Digital Marketing • Digital Analytics • Teaching & Training !
• Over 12 years experience • Nordic: Denmark – Norway – Sweden • International Clients
Barriers preventing action-oriented analytics - and how to overcome them
Barriers preventing action-oriented analytics - and how to overcome them
It’s all about the data, right? (What the statistics say)
The digital economy last year
Source: Google Internal
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All that wonderful data Today
All that wonderful data Tomorrow
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Marketers love their data!
The (Second) Evolution of Big Data
Source: Google Trends
Then came Dan Ariely… (…with his definition of big data)
Source: Google Trends
Big DataBig Data is like Teenager Sex: Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it… !!Quote from Dan Ariely
The impediments to becoming more data driven The adoption barriers organisations face most are managerial and cultural rather than related to data and technology.
Source: MIT Sloan Management Review
The impediments to becoming more data driven The adoption barriers organisations face most are managerial and cultural rather than related to data and technology.
Source: MIT Sloan Management Review
The impediments to becoming more data driven The adoption barriers organisations face most are managerial and cultural rather than related to data and technology.
Source: MIT Sloan Management Review
Research findings:
• Top-performing organisations are twice as likely to apply analytics to activities.
• The biggest challenges in adopting analytics are managerial and cultural.
• Visualising data differently will become increasingly valuable.
It takes more than one person
We might already have individual analytics NINJAS rocking data Chuck Norris style
…but the truth about the rest is something else! And much more boring.
Aligning data visualisation to your analytics processes for better data understanding
The definition of visual analytics From data to visuals to action
Visual analytics is the representation and presentation of data that EXPLOITS OUR VISUAL PERCEPTION ABILITIES in order to AMPLIFY COGNITION.
- Andy Kirk, author of “Data Visualisation: a successful design process”
The core principals of data visualisation From data to visuals to action
What this means…
The visual sense is our dominating sense From data to visuals to action
Source: astro.ku.dk/lys/synet.html
The core principles of data visualisation The visual elements
The core principles of data visualisation From data to visuals to action
The core principles of data visualisation From data to visuals to action
Color (Hue)
The core principles of data visualisation From data to visuals to action
Enclosure + Color (Hue)
The digital analytics maturity steps
Digital Analytics Maturity Framework Making analytics part of the organisation
Technology-centric, engineering-oriented
General Level
Collect
Clean
Convert
Integrate
Store
Report
Inspired by the work of Stephen Few
Digital Analytics Maturity Framework Making analytics part of the organisation
Human-centric, analytics-oriented
General Level
Collect
Clean
Convert
Integrate
Store
Report
Explore
Analyse
Communicate
Monitor
Predict
Technology-centric, engineering-oriented
Inspired by the work of Stephen Few
Digital Analytics Maturity Framework Making analytics part of the organisation
Human-centric, analytics-oriented
Business-centric, changing behaviour
General Level CXO Level
Collect
Clean
Convert
Integrate
Store
Report
Scale
Embed
Transform
Explore
Analyse
Communicate
Monitor
Predict
Digital Analytics Maturity Framework Making analytics part of the organisation
Technology-centric, engineering-oriented
Inspired by the work of Stephen Few
Defining a data-driven organisation From data to visuals to action
The Data-Driven Organisation
Illustration: Google GACP
Collect - Report
Explore - Predict
Scale - Transform
Defining a data-driven organisation From data to visuals to action
Defining a data-driven organisation From data to visuals to action
Going From Zero To Hero
Give the right people the data they can ACT on From data to visuals to action
Illustration: Google GACP
Access to tools and methodologies for better analysis and decisions From data to visuals to action
Illustration: Google GACP
Visualise Analyse Take Action!
Automate actions in real time From data to visuals to action
Illustration: Google GACP
Automatisation
How to asses your organisations maturity (Online Analytics Maturity Model)
Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.
Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.
Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.
Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.
Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.
Chief Marketing Officer
Digital Analyst
Marketing Manager
http://goo.gl/r7hMdH
Measure your maturity here:
Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.
Case: Kleenex
How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN
How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN
How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN
How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN
What can we learn from Kleenex’s approach?
• Applying data to support an adaptive planning process beats the best ‘guesstimates’
• If you can’t find the information you need, think outside the box
• When you have the data make sure to visualise it, and deliver it to people who can take action
• Make the case an internal success story, and get other parts of the business engaged
Case: Target
How Target applied action-oriented analytics PREGNANCY PREDICTION SCORE
How Target applied action-oriented analytics PREGNANCY PREDICTION SCORE
Source:forbes.com
How Target applied action-oriented analytics PREGNANCY PREDICTION SCORE
What did Target do, and what can we learn? • In 2002 Target hired Andrew Pole as an statistician !
• Two guys from marketing: “If we wanted to figure out if a customer is pregnant, even if she didn’t want us to know, can you do that?” !
• They were able to identify about 25 different products that were indicators of pregnancy, including items like unscented lotion, vitamin supplements, hand sanitizers and washcloths.
• Andrew was able to create a model that assigned each shopper a pregnancy prediction score based on their purchases !
• This score was then used to send out relevant coupons and advertisements tailored to each woman at a specific point in her pregnancy !• Target’s Mom and Baby department skyrocketed.
Source:newyorktimes.com
Case: The HIPPO approach
Should we optimise our website for mobile devices? Two scenarios
Scenario #1 (without data)Gut feeling
Business challenge: Should we optimise our website for mobile?
Business challenge: Should we optimise our website for mobile?
Answer: In the absence of data, the HiPPO says no!
Scenario #2 (with data)Data-oriented decision making
Business challenge: Should we optimise our website for mobile?
Answer: Yes, because 11,42% of all our visits are from mobile devices
Woot! What does this mean? Oh boy!
Our mobile traffic is equivalent to: the capacity of Michigan Stadium
Takeaways
Recommendation #1 Something to take home
First, Think Biggest Focus on the biggest and highest- value opportunities
Inspiration: MIT Sloan Management Review
Recommendation #2 Something to take home
Start in the Middle Within each opportunity, start with questions, not data
Inspiration: MIT Sloan Management Review
Recommendation #3 Something to take home
Make Analytics Come Alive Embed insights to drive actions and deliver value
Inspiration: MIT Sloan Management Review
Recommendation #4 Something to take home
Add, Don’t Detract Keep existing capabilities while adding new ones
Inspiration: MIT Sloan Management Review
Recommendation #5 Something to take home
Build the Parts, Plan the Whole Use an information agenda to plan for the future
Inspiration: MIT Sloan Management Review
The core principals of data visualization From data to visuals to action
Finally…
Don’t only think about data, think about action! A key takeaway
“Information is powerful. But it is how we use it that will
define us.”- Zack Matere, Farmer (Soy, Kenya)
- Zack Matere, Farmer (Soy, Kenya)
“Information is powerful. But it is how we use it that will
define us.”
Don’t only think about data, think about action! A key takeaway
Denmark . Norway . Sweden
IIH Nordic A/S, Lille Strandstraede 61254 Copenhagen K, Denmark
www.iihnordic.com
Mail: [email protected]: +45 6 1 3 1 4 0 0 7Office: +45 7 0 2 0 2 9 1 9
CASPER BLICHER OLSENDigital Analytics & Insights Lead
Thank you