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November 19, 2008

Optimal Marketing Strategies over Social Networks

"Optimal Marketing Strategies over Social Networks" (www 2008) is a paper written by Jason Hartline (North-Western Uni), Vahab S. Mirrokni (MIT), Mukund Sundararajan (Stanford).  It's interesting because it gives an idea of how businesses can use social networks in an effective way to sell their products.  

I think the isse at the moment isn't selling products via SN but rather going in unintelligently with the hard sell, and the spamming.  The way to sell your products and services is to find interested individuals and to approach them in a friendly, social networking way, about your stuff.  Use social networking etiquette.

They looked at influence and revenue maximization.  The buyers descision to buy the product is influenced by other buyers in the social network and also by the price of your product.  When the buyers were completely symmetric, they could find the optimal marketing strategy in polynomial time.  

They looked at approximation algorithms and used the influence-and-exploit strategy.  Basically , you give the product for free to a select number of buyers, then you use a "greedy" pricing strategy for the buyers attracted by the influential individuals in their community.  They developed set-function maximization techniques to locate the target buyers to influence.  When other buyers are influenced from others, it's called "the externality of the transaction".  When there is a positive sale, it's called a "positive externality".

We know that users with the most connections have the most influence.  However the probability of people buying the product decreases as the marketing strategy progresses.    This is why the ultimate method is to give the product away to start with, much like Tivo did.  

To start with, you approach individuals and give the itme away, the you go on to the "exploit" stage. You visit buyers in a random sequence and offer them a "myopic price" (optimal pricing for revenue based on the influence of the initial buyers and the buyers who have already bought the item).    

They used a simple dynamic programming approach to identify an optimal marketing strategy.  Because it's symetric, the order in which you appraoch buyers is irrelevant.  "the offered prices are a function only of the number of buyers that have accepted and the number of buyers who have not, as yet, been considered."  

They found that the problem of computing the optimal strategy was NP-Hard, even when there was no uncertainty in the input parameters.    Using automated things to comoute strategies also involve computing issues such as this basically, you don't have to worry too much about that right now unless this stuff tickles your fancy.

The conclusion:

If a set S of buyers have previously bought, offer the next buyer i price vi(S). Buyer is i, Vi is the value of the buyer and S is a set. Vi(S) is a non-negative number.

This price simultaneously extracts the maximum revenue possible and ensures that the buyer buys and hence exerts influence on future buyers."

There is a lot more detail in the paper and the equations are worth a thousand words as always.  Take a look if you're interested in picking at it.

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Science for SEO by Marie-Claire Jenkins is licensed under a Creative Commons Attribution-Non-Commercial-No Derivative Works 2.0 UK: England & Wales License.
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