Action Metrics

With this line of work we would like to solve the problem of quantitatively measuring the effectiveness and impact of a marketing or advertising campaign. There are two complementary approaches that require further development:

    • Measure the criticality of the network to determine "best" period for
       launching campaign".
    • Measure the effectiveness of a campaign at penetrating the social network.

A major goal of this work should be to develop and validate various metrics using data from blogs, Google trends, YouTube, sales data, etc. Finding clever ways to measure the response of the system with combinations of probes.

Several proposed projects are discussed below:

Basic Questions
What is the efficiency of ads campaigns? How to design better? How to manage in real time (or near-real time) and steer complex social systems, commercial sales, reputation branding, etc?

YouTube Data (ongoing)
Using the currently existing database, many studies could be launched to investigate our ability to develop "action metrics". One example would be to use data on existing movie trailers compared to box-office figures to see what predictive power is contained in the dynamics of YouTube data.

Google Trends (new)
Can we extract exponents from data on Google trends that allows us to measure the effect of a marketing campaign?

Blogs (new)
Try to combine data from blogs and other online "chatter" to measure the effect of a marketing campaign (see The predictive power of online chatter)

Individual branch tracking (new)
How do you know which members of your social network are spreading your message? Here is an example (based on a YouTube video for illustration) of how to achieve this. Upload identical video content to "N" distinct URLs. Send a unique URL to each of the "N" people in your social network. Track the "N" resulting timeseries and then reconstruct them from each of the branches.