People Data and the Future of Marketing – ClickZ Live Chicago 2015

My notes on People Data and Its Impact on Marketing
by Shawn O’Neal, Unilever

Economies of scale = competitive advantage

The space we are in today (data & analytics and what it does for marketing) is game changing.

Economies of scale – large amounts of market share & purchasing power to leverage costs

started 250 years ago – spinning
Jenny (created sweatshops)

1950’s to 1980’s economies of scale was still the big thing, but then something change.

Disruption – Google, amazon.com, uber, airbnb – scale isn’t made of pure assets any more.

Big problem for companies isn’t other big players, it’s the little guys.

What are the implications for Competitive Advantage?

What is People Data?

• The Data itself – both social and individual
• Everyday analytics
• Everything that enables us to harness it for use

Big data has always been around. It’s just using data effectively.

What does it mean for Marketing?

• Everything will be SIGNIFICANTLY smarter, faster, better  …and cheaper!
• When can we tell whether the ad worked?
  • Used to be six months. Marketing would have an annual budget and annual plan.
  • If it takes you 18 months to innovate, you’re behind the curve.
  • Now we can tell in real time.
  • If you don’t see a spike in social, it isn’t happening and it isn’t working. It’s not actually driving sales. Social is an indicator, not the driver.
• How can we make ads work better?
  • Right Message to the Right Person – RELEVANCE
    • untargeted ~ 1 in 1000
    • pet owners ~ 4 in 1000
    • Dog vs Cat Owner ~ 40 in 1000
  • Unilever spends $6 billion in media
    • moving to targeted advertising can increase ROI 40 times

• Can we predict what message to send?
  • Sales-based analysis (ice cream is mainly purchased on on the weekend – Friday/Saturday/Sunday)
  • Conversation is happening in social before the purchase happens.
    • ice cream purchases not only happen when it’s warm, but also when the weather is bad and people stay indoors
    • put the media in front of the prospective customers when they’re talking about the purchase (it’s going to rain this weekend, better get some ice cream).

• Can we predict ‘Life Moments’? (It’s easier than you’d think.)
  • Arranged Marriage / Falling in Love
  • Engagement
  • Wedding
  • First Child
  • Own Home
  • Child’s Marriage

• How many pieces of data do you need?
  • Decoding – 403 septillion Coded Combinations
  • Breaking the Nazi codes
  • Only need a handful of specific events.
• It’s not big data, it is specific data
  • Someone who is moving – a sea of conversations and signals
    • “check-in” at Ikea
    • geo-location
    • new relationships on LinkedIn
    • Birth Data / Basic demographic
    • Social/Search – “help” / “mortgage rates”
    • BUYING A HOUSE!
• Can we predict the next big trend?
  • Look at search to predict big trends
  • Food trends start in the US and then follow a specific pattern by country overseas, based on when food shows start showing in those areas.
• Pre-Test? Post-Test? Why?
  • ‘Live’ Digital Ad Testing
  • Repeatable model for testing creative content on the social platforms in real-time
  • Just Do It!
• Can we use Call Centers for insights and more?
  • Before – agent captured information
    • reason code
    • product name
  • After – voice to text captured information
    • packaging
    • product
    • etc.
• Is True Programmatic Theory or Reality?
  • programmatic buying is a system that places all of your inventory of media automatically
  • Axe Romeo Reboot Trailer
    • 4 Target segments
    • 11 scenes (6 variable)
    • Variations in music, content (violence, sexual, romantic and location)
    • Results constantly measured and targeting refined
    • 100K variations
• The Future of Marketing?
  • campaigns are dead
  • use themes based on people data
• The future of competitive advantage
  • fast-change
  • systems and organizational structures that are actually built to do change, not to perform a specific function
  • don’t make contracts longer than a year – shelf-life for new technologies is 6 months