Probing specific digital habits of your customers

One area of research we find many digital marketers ignore is utilizing research to probe on digital habits–specifically for heavy users or super fans–and comparing that to anonymized Ad Analytics data (i.e. 3rd party Behavioral data). . This can be extremely insightful for your Advertising targeting folks, and can often confirm or supplement information they receive from the 3rd party cookie information.

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Often, we find large differences between groups of web users. For example, visitors to your web site might have vastly different profiles than Facebook fans, or mobile app users, or even older email list members. Carefully matching targeted research to higher-level Ad targeting feedback can be a great way to identify lower cost (more efficient) ad inventory AND also help make ad creative much more relevant and specific to the Audience you are trying to reach.

Measure twice, Serve once! (As Ben might have said today)…

Happy Hunting!

OMMA Social Presentation: “Getting the Most out of your Facebook Data”

Thought we would upload our recent presentation from OMMA’s Social LA event this past Wednesday, October 24th (http://www.mediapost.com/ommasocial/speaker/9957/alan-edgett).

The presentation is entitled “Getting the most out of your Facebook” data, and includes tips and examples of how data helped to do better ad targeting, lower CPC’s, identify new ad properties/interests in user base, and¬†identify brand VIP’s!

Getting the Most out of your Facebook Data
 

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Measuring who and how we influence, via Social Network Analysis

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We’ve spent a good amount of time plotting our various Facebook research participants within the contexts of their Social Graphs (Social Network Analysis) relative to what responses they provide for a variety of surveys and qualitative discussions. Some interesting insights can be derived (and new “Community types” labelled) when you look at people’s friends and various “likes” vs consumption patterns.

Here we have mapped 22 communities on Fast Food preference, and identified some key node consumers. Much, much more work to be done to begin to peel apart various behavioral and demographic attributes that may also be contributing, but we like using these visual data tools to lead exploration–plus they are helpful in client presentations!

What tools are you using to visualize these types of Data Networks and Social Graphs? And, what kinds of additional attributes are you using to analyze market research patterns within Social communities?

Note: all data collection from our Facebook Market Research application PerceptionCheck (http://apps.facebook.com/getperception)

GP Aaron

 

 

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