Part 2 of NexTargeting Webinar: Building Audience Insights

Building Audience Insights part 2 The Progression to Findings Presented by Marc Rossen Director of Media Strategy and Analytics, [x+1] February 10, 2011

Before we start: System requirements Please press *6 to mute your phones If you use this OS You can use these browsers Windows XP SP2 Internet Explorer 8, 7 or 6 SP2 Windows Vista Internet Explorer 8 or 7, Firefox 3.5.7, Firefox 3.0.6, Safari 4.0.4, Safari 3.2.2 Mac OS X v10.5.8 Safari 4.0.4 Full system requirements available at http://office.microsoft.com/en-us/live-meeting/microsoft-off

Agenda 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 Webinar #2

Review from Webinar #1 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

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

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 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 Source: DFP Audience Optimization Audience Optimization

We then find audience characteristics that best describe your best customers DMA We find actionable data by isolating the attributes that drive performance 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 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 The client has 36 discreet audience segments across GEO, Income, and IPA Audience Segment

Moving from Actionable Data to Findings

Moving from actionable data to findings 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

Looking at the attribute level performance we can better understand what drove performance 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

Urban centers drive performance The client’s customers seem to be situated in urban geographies

Income trends middle to upper income It’s clear that our client is attracting wealthier individuals

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

The campaign reached an older population 46-55 age brackets represent the largest audience for the client

Customers are predominantly home owners The client’s audience greatly over indexes to home owners

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

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

Step three entails using our data to take insights to actions Actionable Data Finding Insight Action

Step Three – Insights that drive action By taking stock of your findings you can derive actionable insights 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

Three things you can do today Take a campaign that recently ended and bring all your data into a spreadsheet Define your actionable data: What values changed dramatically over the life of the campaign? Conversion rates? CPA? Frequency? CPM? 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 Build a case study of your work and socialize it within your ___ organization

Reach out. Learn more. XplusOne.com Facebook.com/XplusOne Twitter.com/XplusOne XplusBlog.com LinkedIn.com/company/x+1

Part 2 of NexTargeting Webinar: Building Audience Insights

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Part 2 of NexTargeting Webinar: Building Audience Insights

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