part 2 of nextargeting webinar: building audience insights
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Building Audience Insights part 2The Progression to Findings
Presented by Marc RossenDirector of Media Strategy and Analytics, [x+1]
February 10, 2011
Before we start:Before we start:
System requirementsSystem requirements
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Our Agenda TodayOur Agenda Today
Agenda
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Webinar #1
Understanding the value of data and building a value framework that leads to actionable business results
•Actionable data•The role of context
•Findings •Insight •Action
Use our new framework to build an effective audience analysis
•An approach to building audience insights•Looking at the detail to derive tactical value
Web
inar
#2
Review from Webinar #1
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• Don’t get overwhelmed by the data you have available• Take stock of your data set• Bring context with your data by looking at all actionable
data together• Paint a picture to define the problem you are solving• Assess your findings, derive insight, and define your
actions
Take Stock, Assess, Derive, and Define
Step one entails building our base set of actionable data
Actionable Data
Finding
Insight
Action
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Putting our framework in action
Taking a step back, we now understand:•The value of using multiple data points for context•How we build a value framework to derive insights that lead to action to improve performance
We are now ready to put our framework into action to build audience insights
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Audience insights are built by defining what makes your
customers stand out
What we are left with is defining characteristics that can paint a picture of who your customers are
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Your Customers
The Internet Audience
These characteristics allow us to understand why performance trended the way it did and how it can be
repeated
Our CPA trend continually declined throughout the campaign as we optimized based on audience insights
9Source: DFP
AudienceOptimization
Audience Optimization
DMA
We then find audience characteristics that best describe your best customers
We find actionable data by isolating the attributes that drive
performance
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Attribute Tool Set
Income Class
Income Producing Assets (IPA)
US Region
Ideal customers defined by:•GeoData•Internet connection speed•Internet browser•Computer Operating System•Income Producing Assets•Income Class•Social Life Stages•Presence of Children•Home Owner•Gender
By aggregating data into multiple points we bring performance into
context
We use multiple characteristics to define individual groups of your customers as each segment represents a different affinity to your product
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People who live in Massachusetts, Florida,
Georgia, South Carolina, California,
and Pennsylvania
Elite, High, and Moderate IPA
Wealthy Income Class
Audience Segments aggregate multiple
characteristics
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The client has 36 discreet audience segments across
GEO, Income, and IPA
Audience Segment
Moving from Actionable Data Moving from Actionable Data to Findingsto Findings
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Moving from actionable data to findings
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• We have identified the right data attributes
• We have brought context to the data attributes by applying multivariate approach
• Now we dive into each data attribute to indentify why it drove performance thus identifying the findings which will eventually lead us to insight
Step two entails using our data to build findings
Actionable Data
Finding
Insight
Action
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Looking at the attribute level performance we can better
understand what drove performance
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DMA
Income Class
Income Producing Assets (IPA)
US Region
Variances exist in state performance however regional trends are not
apparent
Midwest and midatlantic states are not well represented for this audience
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Urban centers drive performance
The client’s customers seem to be situated in urban geographies
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Income trends middle to upper income
It’s clear that our client is attracting wealthier individuals
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IPA trends are strong to middle and upper audiences
While the client’s audience indexes high with the $250K + audience, the $50-$100K audience produced the highest index. This suggests that the $50-100K audience is the sweet spot for customer acquisition
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The campaign reached an older population
46-55 age brackets represent the largest audience for the client
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Customers are predominantly home
owners
The client’s audience greatly over indexes to home owners
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There is no strong evidence whether children are present in the audiences
home
“With Children” slightly skews positive however this is not strong enough to conclude whether
children are present in the home
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Insight to ActionInsight to Action
Moving from findings to insight and action
• We have identified the right data attributes
• We have brought context to the data attributes by applying multivariate approach
• We have identified findings that describe certain data attributes drove performance
• Now we will take our findings, translate them to insights, which lead us to our final step of action
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Step three entails using our data to take insights to actions
Actionable Data
Finding
Insight
Action
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Step Three – Insights that drive action
By taking stock of your findings you can derive actionable insights
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Finding Insight Action
State and DMA level data drives campaign performance
Coastal states and urban core DMA drove the most significant lift
Future campaigns should focus targeting older consumers on coastal locations and urban cores with middle upper wealth class
CPA decreased for Income and IPA data
Middle Upper to Upper class consumers predominantly drove performance
The campaign reached older people who look like home owners
Older homeowners were reached by the campaign targeting
Takeaways for you todayTakeaways for you today
Three things you can do today
Take a campaign that recently ended and bring all your data into a spreadsheet
1. Define your actionable data:• What values changed dramatically over the life of the campaign?
• Conversion rates? CPA? Frequency? CPM?
2. Build your value pyramid• Take your actionable data and bring context to it to assess findings• Derive your insights from findings• Define the actions your would have taken
3. Build a case study of your work and socialize it within your ___organization
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Reach out. Learn more.
XplusOne.com
Facebook.com/XplusOne
Twitter.com/XplusOne
XplusBlog.com
LinkedIn.com/company/x+1
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Thank youThank you
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