DV 2016: Customer Data - The New Value Exchange

Let’s Talk About
Customer Data

Three Types of Data
First-Party Second-Party Third-Party
What you know
from your
customers
Shared data
about your
customers
Generated on
other platforms
and websites

Why it’s important
In many ways, our ideal customers are harder to reach
online today
 54% of users don’t click on banner ads due to distrust
SOURCE: BannerSnack
 Ad avoidance continues to increase, up 41% in 2015, to 198M
SOURCE: PaidFair

Why it’s important
And the traditional ways in which we reach them are
becoming limited
 Bot-driven advertising fraud will cost brands $7.2B in 2016
SOURCE: Association of National Advertisers and White Ops
 Viewability rates are flat, click thru rates flat
SOURCE: comScore; DoubleClick

We must truly connectProduct Story Trust

And create experiences

There’s a new balance of
power here

Let’s Start with Third-Party Data
And let’s meet me!
 I’m Adam (hi!)

 I’m Adam (hi!)
 I have 362 data points collected about
me across Lotame, Bluekai, V12 and
other data providers
 I need to tell you something about me…

 I am a women 27% of the time
 I have 2-3 kids
 I live in Tennessee
 My family of 5 earns $2,000 over the
federal poverty level
 I like Yoplait yogurt, boating and board
games

 I have 2-3 kids
 My family of 5 earns $2,000 over the
federal poverty level
 I like Yoplait yogurt, boating and board
games

I probably browse sites browsed by women
 I have 2-3 kids
I have a nephew?
I’ve been to Nashville?
 My family of 5 earns $2,000 over the federal poverty level
Maybe a shared computer once?
 I like Yoplait yogurt, boating and board games
Ya lost me…

Let’s Talk About First-Party
 This is what you know about your customer…
actually know
 Most of us* take this for granted
But let’s stop calling it that!

What’s the customer
trying to say?
Typical Scenario:
• Target visitors who start to purchase but
abandon

With a Data Layer
in place…
Signal:
• “Sort by price”
Intent/Context:
• To purchase, but might be price sensitive
Action:
• Promote travel packages, offer discount
code or credit card offer

With a Data Layer
in place…
Signal:
• “Refundable”
Intent/Context:
• Might need to change trip
Action:
• Promote travel insurance, ticket change
offer or other upsells

This is the only thing that’s
unique to your business.

And if we do this right, we can
build a lasting, valuable profile

It’s a relationship

This is your relationship

In our personal relationships…
 There’s always someone:
– Hotter
– Younger
– Funnier

It’s a relationship that endures

The same happens with your business
 There’s always another
competitor that’s:
– Cheaper
– Has better messaging
– Has a better design
– Got your same product
– Stole your ideas

Customer Relationship data is
your most valuable asset

So where does your data go?

Two
thoughts on
working
with your
vendors
“The question of what you want to own
is actually the question of how you want
to live your life.”
Marie Kondo, The Life-Changing Magic of Tidying
Up: The Japanese Art of Decluttering and Organizing

#1 Reward Openness
 Consumers are changing their behaviors and preferences at a rapid pace
 Marketers (and their vendors) need to be agile
 Vendors need to embrace importing data from other solutions
 Vendors need to work together, around you and your customers

#2 De-Risk Your Implementation
 Tag management reduces the amount of time to implement a technology
- But we still buy the same way
 Test the vendors that work for you
- If the same vendors worked for every company, there would be only one
marketing cloud
 Two ways this works:
- Concurrent A/B split test vendors (such as retargeting technologies)
- Crawl/Walk/Run implementations to test functionality and lift

Summary
 Respect the relationships you have with your customers…
… by honoring the data you have
 This about Andrew Jones’ “What If” idea to design your customer data
 Supplement where needed, but start with What If
 Turn your vendor relationships into partnerships

Thank You
For Being a Part of #DV16

DV 2016: Customer Data - The New Value Exchange

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DV 2016: Customer Data - The New Value Exchange

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