Monetizing social networks

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Social Networks are the key to viral grow and monetization of your business on the Web. To understand why, it is important we understand the work of David Reed. Reed's Law in its simplest terms, states that the value of large networks, particularly social networks, can actually scale exponentially with the size of the network. The justification for this claim resonates with the large number of possible sub-groups among the network. As network benefits grow based on the combinations of these sub-groups and the total number of many-to-many possible connections, we move beyond the one-to-one possibilities contemplated in Metcalf's Law, thus the value of the network increases as does the growth in the networks second derivative. For those of you not versed in Calculus, the first derivative is the rate of change; the second derivative is the rate of change of the rate of change. The second derivative is key to understanding how our monetization efforts are progressing, it provides us a benchmark. When a network is reaching a point of diminishing returns (the point at which the second derivative slows) it is an early indicator that problems are on the horizon. Very little has been written on this topic, but I can assure you that a company's ability to monetize any particular network or sub-component of a network is directly proportional to the applicable underlining second derivative.

Suppose your firm's revenue model is based on advertising and on average, you made a penny a click in the early years, but as your network reached critical mass you were able to drive your revenue incrementally to .05 cents a click. As your network's second derivative slows and reaches an inflection point (the point in which the second derivative turns negative), It is clear your average revenue per click will trend back down toward the .01 cent level as you experience the pain of the Negative Network Effect. In order to continue to increase the value of your network, you must find new ways to monetize your network, reigniting the positive network effect. So how do we design a business model that maximizes the network effect? Let's take a look at the process.

Monetizing Network Effects on the Web ideally requires a dynamic Web 2.0 business model with multiple revenue streams, significant growth potential, and the strong balance of revenue, expense, and capital outlay. In order to maximize your Return on Investment (ROI), you must understand the interdependencies of revenues, costs, and capital investment on your Network Model. First, let's examine some of the most common Web 2.0 revenue models.

Advertising based - Perhaps the most successful and popular business model. Well know companies like Google and Yahoo give away search and sell a wide variety of advertising options to monetize their networks.

Subscription based - Very successful model where users pay a fixed fee at regular intervals. Fees can vary by type of account such as basic or premium service level or by options such as advertising or no advertising, etc.

Syndication or Licensing - A growing model as technologies such as RSS feeds (Real Simple Syndication) and content distributors grow. The user typical pays a fee to use or resell the product. The fee charged is often driven by the type of user, i.e. non-profit, business, individual, etc.

Unit based - The user simply pays a unit price for your product or services. If you buy a book or CD on Amazon, you are making a unit based purchase.

Transaction fee -This model has the user pay a fixed fee per transaction or a percentage of the sale. If you selling anything on Amazon or eBay, you will pay a percentage transaction fee based on the sales price.

Revenue Share - A popular model when distributing items requiring large inventories like DVDs, CDs, etc. In this model, the distributor may pay the content originator a small upfront fee and then share a percentage of the actual product sales. This model helps keep the initial acquisition costs low and allows time for your network to develop and reach critical mass.

Cross-network - A new and innovative model that involves strategies such as freemiums and n-sided networks. Freemium is a term that was coined by the combining of the words Free and Premium. The idea is to give something away and acquire a lot of clients or users, then offer premium value added services to monetize this base. The concept has been used extremely effectively by firms such as Adobe, Flickr, LoopNet, MySpace, and many others. Cross-network strategies simply target complimentary but different user bases. The classic example is the demand for gaming software titles when new gaming hardware platforms are released.

Now that we know how we can generate our revenues, we must understand our Critical Cost Drivers (CCD) and how these CCD will respond as our network expands. For each cost driver, we must understand the nature of the cost- is the cost fixed, semi-fixed, variable, one-time, or recurring in nature. This understanding allows us to construct a Cost of Support (CoS) model. The CoS model identifies the relationship of each of our costs to a base unit of revenue growth in relation to a fixed, but sliding network point. The fixed network point continuously moves as your revenues move along a J-curve or similar benchmark. The J-curve is typically most appropriate as businesses initially start to spend significant money on personnel, infrastructure, inventory, systems, and marketing during the start up phase. As your network starts to grow, revenues expand in relation to costs and the curve starts to decline at a slower pace, then flatten, and eventually start to climb. Understanding these interrelationships will assist you in maximizing your networks ROI.

Once we have identified our sources of revenues, our cost, and the relationships of our underlying costs to those revenues, we must model the appropriate J-curve to ensure our CoS model is accurate. In order to do this, we start by taking a look at our revenue positioning strategy. The typical strategies include one or more of the following:

o Loss Leader - Your network utilizes multiple streams of income that individually are not all profitable, but the losers drive traffic and subsequent purchases of other profitable products and services.

o Single Product or Service - Your network relies on a single revenue stream derived by one product or service.

o Multiple Product or Service - Your network receives multiple revenues from at least two products or services.

o Interdependent Product or Service - Your network promotes one set of products or services to drive demand from another set of products or services.

Your revenue positioning strategy will dictate your anticipated timing of revenues and thus the necessary underling CoS structure. Armed with this knowledge, we can adjust our modeling based on our revenue tracking metrics. These metrics may be things like average revenue per search query, average revenue per page view, average revenue per subscriber, or some similar metric. I have simplified this for ease of communication, but in actual application, we must use complex algorithms to differentiate the "life-time" value of different types of network participants, users, or customers. These calculations are based on the relationships between the numbers and type of network members and their interaction as frequent contributors, active members, influencers, etc., it stands to reason for instance, that an active blogger offers significantly more life-time value than an inactive member. Also, a particular user's distance from an already established high life-time value user can significantly impact the value of that individual user. When I am referring to distance from one user to another, I am really talking about degrees of separation. In the late1960s, Stanley Milgram investigate what became coined "small world phenomenon." He conducted an experiment were he attempted to find connections or links between people by asked random individuals in Nebraska to deliver letters to particular individuals in Massachusetts. The basic rules were to give the letter to someone you knew who in return would give it to someone they knew and so on and so on with the objective being to get the letter delivered with the fewest connections.

Through numerous tests, Milgram found that, on average, it took five or six connections to get each letter delivered. This study provided the basis of the theory of "six degrees of separation." In the past, the initiator likely would not know anyone past the first or second connection, but with our online connections, we literally can jump the network and direct connect to the targeted party, via our existing network relationship. Analyzing and understanding these relationships and degrees or distance from our highest life-time valued is critical to maximizing the monetization of your network. As you can see, the monetization of networks is a complex task, part science, part art, part trial and error. However, by applying these fundamental strategies to your business, you greatly increase the odds of maximizing your network ROI.