Part 2 of NexTargeting Webinar: Building Audience Insights

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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