Determining the success of  social networking by real dollar amount generated will be difficult, and expecting financial tools to give a gain or loss determined by dollar amount ill-advised.  This is particularly because of the fact individual variables for alternate projects are not being tested to currently interact with social networking.  Also, social networking is a communication tool.  The problem with trying to determine ROI for social media is you are trying to put numeric quantities around human interactions and conversations, which are not quantifiable, to an extent.   If financial tools must be generated by a measurement of click through’s, or social networking membership rates, they are in infant stages and will be made according to online presense combined with relative advertising techniques.

I recently presented a list of measurement tools to determine ROI for social media for some company executives to review.  Since the industry I’m in heavily relies on membership as a main, if not only, source of benchmarking for successful ad campaigns; the following statistics are heavily weighted on new membership being a advantageous measurement tool.

I first wanted to increase online brand equity as an increase in our index in Google Insight.  Since no initial investment besides human resources was required, I had to develop this plan with free tools.  Google Insight represents 65% of search data, and considering the volume that Google searches, I figured it was a good start to increase online brand equity.  We were currently listed at a 3 in our total industry index in our metro area…not good.  To moniter non-financial returns, we are hoping that our Google Insight index increases with our social networking presense online.

Secondly, I wanted to measure the return of our social networking proposal and the increase it will lead in conversation across the web. We can look at Facebook comments, likes, twitter  reposts, twitter mentions,  or youtube subscribers (as well as mentions across blogs and other sites with more advanced tools).

Conversation among Facebook.

Total Facebook Comments + Total Facebook likes + Total Facebook Messages/Current FB Membership = Facebook Conversation

Example:  5 + 8 + 2 / 400 = 3.75%

Conversation among Twitter

Total Twitter Reposts + Total Twitter Mentions+ Total Twitter DM’s/Current  T Membership=Twitter Conversation

Example: 30+15+2 / 600 = 7.83%

Aggregate Social Network Conversation

Facebook Conversation %+ Twitter Conversation %/ 2 = Total Social Networking Conversation.

Example:  .0375 + .0783 / 2 =5.79%

If we determined a current alpha of zero from past membership numbers and product information with no conversation on the web, then the result of the total social network conversation can be used to develop whether or not the results of our investment has a return that exceeds the assumed risk (i.e.  human resources invested)  to relate to increased membership or products purchased over past data.

Finally I wanted to give an idea of how to track financial data to give us an impression of what type of return we were generating.  For new membership, by visitors driven,  we will need to calculate the number of unique visitors to our web site from one of our four social media sites.  This will give us the ability to track the amount of increased traffic to the amount of new memberships we have received.

Yearly Social Networking Referal Rate = Referal from Twitter + Referal from Facebook + Referal from YouTube + Referal From Wiki / Total Unique Visitors (From Google Analytics results)

Example:  1800 + 1200+ 360 + 480 / 49000 = 7.7%

Yearly WebSite Advertising SN Number = Social Networking Referal Rate x Web Site Ad Referal Total

Example:  7.7% x 54 = 4

Avg. Social Networking New Membership Number = New Membership Rate – Avg. New Membership Number

Example:  If we had 49 new members and the average for month is 40.

49-40  = 9

This average social networking number assumes that membership is fairly static.  During regression analysis I found that the standard deviation for this monthly new member total is around 13.8.  This is obviously involves variations that would be innacurate for testing.  If the Average Social Networking Number is used it is important to have very little deviation, or a much higher more significant population.

Social Networking Conversion Rate =  Avg. SN New Memberships or Realized SN New Memberships/Unique Visitors From Social Networking

Example:

If we have 40 new memberships and 65 new members added to our Social Networking campaign we can conclude that the Social Networking Conversion Rate would be:

40/65 = 61.5%

Obviously this does not represent conversion from social networking to memberships.  However, since individual statistical variables are not accounted for, the original 61.5% will be a benchmark in which we can compare the SN conversion rate to in the future.  If SN new membership increases with the same significance as our new members, than the stat will be helpful.

These are a few examples of specific company ROI tools that I think will be beneficial.  It seems as if I were given the task of computing ROI for early e-mail, faxes, and phone conversations.  Communication with our customers is essential for healthy successful business.