Making the Most of Your Facebook Database

an interview with
Jeff French Founder and Chairman, Louddoor

Jeff French, Founder and Chairman of Louddoor spoke at MediaPost’s recent Social Media Insider Summit way up in beautiful Lake Tahoe.  I thought he had a lot of really interesting things to say about social media data mining so I followed up with this interview.  Louddoor’s secret sauce is that they have a 50 million strong Facebook user database that gives them terrific insights into user behavior that marketers can then leverage–I think you’ll find what Jeff has to say quite enlightening.

DN: Give me the 10,000 foot view on Louddoor?
Louddoor is the leading market research and audience targeting Platform for brands and agencies on Facebook.

DN: Tell me a bit about your Facebook user database?
Our database is 100% opt-in and represents data shared by participants in our various market research studies.

DN: Have you all been able to calculate “value per like” and if so, how?
Yes. Value per Like is different for every Page on Facebook. To calculate what a fan is worth you have to establish a control group of similarly situated customers that are not fans and compare their behavior and spending habits to a statistically relevant sample of fans. It’s important to gather a full census of your fans. If you post in the newsfeed to recruit your panel you might as well throw the results in the trash can. Everyone knows that being a Fan on Facebook correlates to higher customer value but our goal is to isolate the causative effects of being a fan and that takes a well executed double blind study. This is the data marketers need to make more informed decisions. It’s not easy to get but it can be done if you have the right partner.

DN: Why is value per like such an important metric?
Its one of many important metrics but having a Value Per Like benchmark can help a brand marketer spend on Facebook with more confidence. When you know what a fan is worth you can make better decisions all around. We’re also in the nascent stages of constructing regression analysis to better understand long term fan value. Everyday we learn something new that gives brand marketers and their agencies more confidence in Facebook Advertising.

DN: You did some interesting user modeling for Hornitos uncovering “mudders” as a passion—tell me about that process?
We conducted a detailed market research study where we surveyed over 25,000 Facebook users about their tequila consumption habits. We found an incredibly strong correlation between users who frequently drink tequila straight (shots, neat, rocks) and the various “mud race” events like Spartan Race and Tough Mudder. We used these findings to target the “mud race” audience for future activations and were able to deliver outstanding results for the client.

DN: How do you allay Facebook user concerns about privacy given all the data you’ve gathered?
First, we never share any personally identifiable user data with anyone (including our clients). We clearly disclose to our users that the data provided on our Platform will be used on an anonymous basis to construct better ad targeting and analytics algoritms for use on Facebook. Users understand that ads keep Facebook free and when you get right down to it they want these ads to be more relevant to them. Mark Zuckerberg himself puts the user experience on Facebook in front of everything else. We believe strongly that our research is improving the Facebook user experience for brands and consumers by creating more relevant ads. It’s a true win-win and we’ve never had a single user complaint regarding a privacy issue.

DN: Can you share another example of how you’ve helped marketers by analyzing Facebook data?
Audience Segmentation is a hot topic right now for our clients. Facebook recently released new functionality to let brands better target posts in their fans’ newsfeed but we are going far beyond these capabilities and using Facebook Sponsored Stories to deliver the right message to the right fan at the right time with laser precision. For example, most brands have customers that respond for different reasons. Some may be more influenced by product quality while others are discount motivated. We are able to slice a client’s fan base with this level of granularity and when we deliver relevant sponsored stories powered by this data the results are simply incredible. We are literally seeing engagement results 5-10X greater than un-targeted sponsor story units. You can’t spend engagement but it’s the first step towards driving sales and measurable results.

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