Federated Media was a company that powered the best of the independent web. FM combined ad solutions and independently authored content with the reach of a world class advertising network.
A key element of the marketing programs on the sites that FM represented, and that it independently managed, is the amplification of the independent and branded content via social networks like Twitter, Facebook, Reddit, StumbleUpon (now Mix) and others.
My responsibility, and the responsibility of my team, was to analyze the performance of our omni-channel programs and synthesize what was driving audience engagement within those high-touch, Content Marketing programs with major brands such as Dell, Intel, American Express, Gillette and L’Oreal to name a few. We did this by establishing and defining the metrics and KPI’s that would demonstrate the success/failure of programs and campaigns and then help optimize and develop insights to grow the program.
Many times, the Sales/Account team would have a spreadsheet of social activity and data points without much understanding around what was the story that the data was telling, and I took this as an opportunity to help put some rigor around it. To that point, data goes a long way to telling telling the story of what is going on in the business and understanding the trends and information sure does help. At the same time, ‘analysis paralysis’ is a real thing with all the data floating around these days. In many ways, this quote from Albert Einstein sums up the balanced approach I take with such programs:
Not everything that counts can be measured. Not everything that can be measured, counts.
Albert Einstein
Federated Media was acquired by Hyfn Media in 2013 and now operates under that name.
A Model to Measure Social Actions and Amplification
To attack this challenge, I first broke down the user experience and the different variables that impacted the experience. I also isolated what I felt were the value elements within this experience – the action or ‘endorsement’ of sharing and the value of the influencer’s audience. I modeled this approach on the methodology of the “Net Promoter Score” (which quantifies the likelihood of a person to recommend a product/service that they have used.) I took the Net Promoter methodology and applied it to the social experience and put it into a picture that succinctly sums up the model.
Quantifying The Social Model
My next step was to model this out. What were the inputs that we needed (advertising spending, natural traffic, paid traffic, amplification, author engagement, etc.)? What were the variables that impacted the value along each of the main value areas (CTR, CPC, etc.)? And finally, how does the total value generated compare to the cost the advertiser/partner was paying? What was their “Media” ROI?
As my Einstein quote notes above, there were some elements that had to be straight line averages. But my overall agenda was to evolve the model and enable it to incorporate more advanced statistics and data points. I also made it flexible enough to accommodate spikes or dips in activity, spending, or seasonality.
Content Program Reporting, Analytics, and Optimization
In addition to the above, my team’s “day to day” job :) was to manage the reporting, metrics, and optimization of our existing Content Marketing partners and clients. FM ran content marketing programs for American Express (OPEN Forum), Intel (My Life Scoop) along with a few others. My team looked beyond the simple metrics of page views, Visits and Time on Site to go further into the on site behaviors, the paths/journeys that were taken, the most popular content, and to the best of our ability – reasons why certain articles got the activity that they did. We took all of that data and developed a Reporting Dashboard template that could be customized and adjusted to each client.
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