Platt Perspective on Business and Technology

Monetizing social networks and the valuation of social media connectivity – 10: putting the puzzle pieces together

Posted in macroeconomics, social networking and business by Timothy Platt on March 9, 2012

This is my tenth installment in a series on the valuation of online social networking connections, and more generally of online social media connections (see Macroeconomics and Business, postings 42-47, 49, 51and 54 for parts 1-9). In earlier series installments I have successively looked into a variety of issues and factors that would go into evaluating the actual, realizable value of social media connectivity for a business, with much of that centering on a more recent measurement innovation, the social media influence score.

I have looked at issues of demographics and whether a high score social media connector and influence reaches the right target audiences to be able to make a positive difference. I have looked at issues of scale and the size of the social media influence score, but also of valance and whether that influence is positive, negative, neutral or mixed – and in what way and under what circumstances and in the context of which social media channels and venues pursued, even when a social media influence is potentially positive and for the right target audience. My goal in this posting is to step back and look at how all the pieces to this puzzle do and sometimes do not fit together. And in that, I would posit what I would argue to be a simple and direct truth.

• There is no simple, easy to measure and apply magic bullet for determining and establishing a positive connection to the marketplace for any business or organization, that can simply be applied to any business and any marketplace according to a single formulaic implementation.

Marketing cannot simply rely on any one single measure or metric, or succeed from simply finding the spokesperson with the highest score and applying them like a bandage. In this I directly challenge some of the marketing hype that surrounds each newest and greatest as we move from eyeballs to sticky eyeballs and on to the next new and the next – currently pursuing the social media influence score.

• Every one of these metrics carry real value – but only when applied in a carefully considered way and with real understanding as to their limitations as well as of their potential strengths.

That, I add, applies to social influence scores as much as it does to its next best thing predecessors and I can state with some measure of certainty – it will apply to the next metrics to come along too. They all have to be understood and used in context and in concert with a full range of other tools, if they are to offer real value.

Given that large caveat, what would a best metric of social media and social networking connectivity look like in a business context? A partial answer to that is that it would connect the specifics of context to replicable and even standard frameworks of measurement and scale. And one proof of value is that it would offer fresh and otherwise unrealized insight into the specifics of the business, its customers and potential customers and the markets they would meet in. And, it would do so in such a way as to support comparisons with other businesses and their successes, and even across the boundaries of distinct markets.

• There is no single magic bullet metric, however, so the best alternative to finding and using one would be to intelligently make use of a tool chest of individually more limited metrics with social media influence scores only one of them – and with older metrics and even ones like eyeball counts used where they genuinely offer value, there in determining the baseline of how many people have at least seen a business web site as a starting point in determining its effectiveness.

I am going to finish this posting and this series at least for now, by stepping back and putting the entire issue of social media and social network monetization in a larger context. This type of data collection, sifting and sorting and analysis has to be conducted in much the same way as would be needed in determining the valid monetizable value of any other actionable business intelligence when moving beyond the ad hoc in building a richly information-based marketplace, or on a larger scale, an information economy. In this, data and processed intelligence that specify and clarify social media and social networking value simply comprise one of many possible slices of the overall pool of available business intelligence per se.

You can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 9: who speaks for whom?

Posted in macroeconomics, social networking and business by Timothy Platt on February 29, 2012

This is my ninth installment in a series on the valuation of online social networking connections, and more generally of online social media connections (see Macroeconomics and Business, postings 42-47, 49 and 51for parts 1-8). I have been posting on the general topic of social media influence scores, and the value of having members of social media-connected communities with high scores serving as spokespersons. And as a part of that I have discussed some of the basic parameters that would go into making a spokesperson’s influence effectively serve as a source of positive, negative or neutral value to a business or other organization. One of the basic assumptions that I have kept in place and unexamined through this has been that of selection and influence that an organization would have over its spokespersons and that is the topic of this installment.

In this regard I note as a starting point that with the advent of web 2.0 and the directly participatory interactive web, anyone and everyone can and should be expected to share opinions online and about essentially anything. That can mean posted and shared direct reviews and with numerically scaled evaluation scores and both on a business’ own online sites, or through third party and neutral sites such as Yelp. That can mean less-structured and unstructured feedback and review commentary and through friends’ Facebook walls, Twitter feeds, blogs, and a growing range of other venues. But whatever the venue, as soon as interactive features are made with options for others in the business’ outside community to read this shared commentary, social media influence: positive and negative becomes an important issue. And in general, businesses and organizations might be able to reach out and at least seek to influence the people who have influence regarding them with more significant voices. And they can respond to recurring and virally marketed messages. But that is all they can do, barring directly challenging messages shared that reach and surpass a threshold of libel or slander as being knowingly false and intentionally and even calculatingly harmful.

Basically, with this posting I throw open to the crowd the entire issue of influence scores, and evaluating the impact of these metrics becomes a statistical and even demographic level analysis balancing positive and negative impact – plus analysis of the impact of outlier high influence score commentary participants.

And I add here, that favorable commentary from supporters can have negative impact and unfavorable commentary and even from strident detractors can come across as neutral at most in impact, and even where by the numbers those participants appear to have high influence scores.

• It is not just what is said in commentary, review and feedback but how it is said that counts.

I write that point with a specific consulting client I have worked with as a working example. This is a nonprofit that offers computer technology training to help members of underserved communities find new jobs and start new careers. And some of the favorable feedback shared with them through their organization’s Facebook wall, while very positive and praiseworthy in intent, has been off-putting for how it is written. I am not just referring to typos and spelling errors here, but to use of curse words and slang, that does not put either the writer or this organization in a good light. That is potentially positive influence that loses its positive impact and certainly for potential donors who might review this Facebook page when making their donation allocation decisions. At the same time, this organization has had to deal with negative reviews, shared through sites such as Yelp – and they did not come across as credible for how they were written either. This organization has control over which wall postings it would allow to stay up on its own Facebook page, but like any other business or organization it has very little control over what would show that addresses it on other Facebook pages, or on third-party sites such as Yelp.

• Organizations do not in general in any way “own” their spokespersons or their voices or opinions or how those views are expressed.
• They can and should know what is out there that reflects upon them, positively and negatively.
• They should respond where and as appropriate.
• And the most important influence score coming out of this is going to be the cumulative, aggregate score and its message, as influenced, perhaps by those high-impact, high influence score outliers and their messages. That includes the impact of spokespersons and hired spokespersons as it overlays and contributes to the more general and community wide conversation.
• And even a well-respected spokesperson with an articulately stated, catchy positive message can be lost in the flow of a less positive virally shared message and the collective impact of numerous individually low influence social media participants.
• So looking across this and the past several preceding installments in this series, social media influence scores are not a magic bullet, and understanding them and developing a response calls for a detailed and nuanced analysis and of what the overall message is, where it is shared online and how it is presented.

I am going to finish this series at least for now, with a next and final installment in which I will consider issues of the monetizable value of social media influence scores when taking the fuller array of factors that I have been discussing into account. Meanwhile, you can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 8: social media diversity and where a high influence score represents influence

Posted in macroeconomics, social networking and business by Timothy Platt on February 23, 2012

This is my eighth installment in a series on the valuation of online social networking connections, and more generally of online social media connections (see Macroeconomics and Business, postings 42-47 and 49 for parts 1-7). I have been analyzing and dissecting out the details as to what an influence score is and what it measures as a metric of monetizable value. In Part 7: objectivity and influencing from a genuine voice I discussed the valence, if you will, of social media influence where it can be positive and supportive or negative and damaging, or neutral in value even when of seemingly significant scale. Here I turn back to the issue of scale and amplitude, and my focus of discussion is going to be on what that means. As a foretaste, I note that a social networker might have significant reach and social media influence in some venues but little if any in others – and even when just considering a single high value target market and its audience demographics.

I would start this discussion by raising some fundamental questions, starting with a set of issues related to the target audience that a high-influence-score networker and communicator might connect with:

• What social media venues and outlets do members of a target demographic use, and with consistent and even demographic-defining reliability and consistency? Here, I include social networking and sharing sites like Facebook and LinkedIn, short message sharing sites like Twitter and instant messaging tools, blogs and other personalized web site-like venues with the interactive features they can include, online crowd sourced and related review and opinion sharing sites and more. Where do these people go when they reach out to connect online?
• What do they look for and do there? This is a crucial question, as many if not most social networkers and social media participants come to develop preferences and assumptions as to the types and nature of the connecting that they will participate in, that will vary depending on where they are online. Meshing message type and topic, and level of seriousness to the venue that it is to be shared through, and that to audience members and their preferences is important if a high influence score is going to translate into high positive influence value. This becomes particularly important where such sharing is public and publically visible, as is the case when posting to a Facebook wall. And if you as a high influence score spokesperson post content to your wall that the people you are trying to influence will not read or respond to – because they don’t go to Facebook for that stuff, this has consequences too.

Now let’s consider this from the perspective of the high influence social media connector.

• What message are you trying to convey? I am assuming here that as per Part 7 this is a message that you can convey with a genuine voice and as a compelling spokesperson. But what is it as a core message and with any core branding included?
• What social media channels and venues would this best fit into? So for example, would this convey an effective message in 140 characters or less, perhaps with an included URL? Then it might be effective Twitter content. Would this do best with a longer format? A blog posting might be better, and perhaps with twitter feeds directing twitter users to those postings. Would a YouTube style video work best, and if so where should you place or imbed it for effective reach with your target audience, and with effective presentation of what you would share?

This posting is all about connecting the dots, and about reaching out to the right people in the right ways and in the right places, where a message can be effective and where a target audience for that message would be receptive. And spokesperson influence score is a mutable variable across multiple factors that go into determining that.

I have been peeling back potential assumptions about influence scores in this and the past few series installments, and I will turn to one more set of assumptions in the next. As a marketer or business person, you do not always get to choose your own spokespersons. This becomes important where viral marketing is considered, and it can arise in the context of high influence score networkers and social media participants as well as from the cumulative action of many individually less influential connectors. This all impacts on what a social influence score can operationally mean.

You can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 7: objectivity and influencing from a genuine voice

Posted in macroeconomics, social networking and business by Timothy Platt on February 18, 2012

This is my seventh installment in a series on the valuation of online social networking connections, and more generally of online social media connections (see Macroeconomics and Business, postings 42-47 for parts 1-6). I have been writing for the past three installments on influence scores and their potential use and misuse in market analysis, and in marketplace and customer community development (see Part 4 and Part 5 on influence scores per se, and Part 6 on some of the factors and considerations that would go into effectively using this type of tool.) I continue this discussion here, starting with a point I made but did not delve into towards the end of Part 6.

• Conveying a genuine appearance carries more weight than simply coming across as a paid spokesperson, and genuine voices do positively influence.

Quite simply, it does not matter how much influence reach a potential spokesperson offers, and whether they arrive at your business as a celebrity or as a crowd sourced high connections value networker. A high influence score can only provide value if the person holding it is seen by the people they potentially influence as being credible for any opinion or judgment they would share about your business.

Who would offer you greater positive impact in your marketing and in helping drive your sales?

1. A well-known celebrity who is renowned for their drinking and wild partying, and who has absolutely nothing in their background that would connect with what your business does or offers, or with its values?
2. That same celebrity but this time they have a positive personal reputation? It is just that in this scenario they also come across as serving as a paid spokesperson who is simply playing a role in a for-fee acting assignment and whether they use your products or services themselves or not, they are only reaching out to influence for a paycheck.
3. A non-celebrity who presents themselves with a positive image, and who comes across as a genuinely enthusiastic user of your products and/or services? And they come across as simply presenting word of their own positive experience with a suggestion that if other peoples’ experience and needs are like their own, they might find value in what you offer too. Here, the high influence score individual who would act as spokesperson might have a much lower score than the celebrity/actors have but they come across as genuine and as speaking with a genuine voice.

This set of considerations simply adds onto the list of factors that I discussed in Part 6 where I focused on level of connection to the communities that would comprise high value market demographics for the business to target for its sales efforts.

• With the wrong spokesperson for your business, their influence score might at best prove of neutral value and it might actively deter all those people reached from becoming your customers.
• With the right spokesperson, with a positive image who comes across as speaking with a genuine voice, even a more modest influence score as to size of impacted audience might offer tremendous value – and especially if, as in Part 6 considerations, their influence effectively focuses on the target demographics who could be most inclined to buy from you.

Note that I am not writing about disinterested objectivity here. Enthusiasm and even a sense of passionately intense and involved enthusiasm can in fact be contagious. I am not necessarily writing about fad buzz here either with a “cool people use this or do this” message, and add that pushing that as a message is more likely to backfire than work. It comes across as phony and certainly to people who have seen way too many celebrity pitches already. I am writing about presenting a message of being like the people reached out to.

To take this out of the abstract, consider a healthcare nonprofit with a marketing goal of raising funds in support of its mission: searching for a cure for a life threatening and life limiting disease. If a spokesperson steps forward to say they are involved in this fight because they have seen firsthand what this disease can do, in the lives of friends or family or in their own life – that can convey a powerful message. But just a clear, compelling sense of genuine concern and desire to make a positive difference in the lives of others can be enough to be quite convincing and even if the people reached out to do not know why this spokesperson feels so strongly – in this case about finding a cure for this particular disease.

I am going to continue this discussion with my next series installment where I will delve into the issues of social media venue and message. As a foretaste of that posting I note that conveying an effective message depends on both who is conveying the message and their credibility and reach, and on the mindset and intent of the people they reach out to when and where they are reaching out to influence. And a high influence networker and connector may be a high influencer in some social media venues and not in others (e.g. considering sites like Twitter, Facebook, blogs, LinkedIn and the host of review-related sites and social media venues out there as a partial list.) Meanwhile, you can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 6: social networking and connection strategies and the focus of influence

Posted in macroeconomics, social networking and business by Timothy Platt on February 13, 2012

This is my sixth installment in a series on the valuation of online social networking connections, and more generally of online social media connections (see Macroeconomics and Business, postings 42-46 for parts 1-5). I have written my most recent two postings in this series about a new and emerging metric that seeks to capture at least relative valuation potential that can be developed from social media connections: influence scores (see Part 4 and Part 5.) And I continue that part of this larger discussion here, at least as a starting point. My goal in this posting is to discuss how analysis of networking participant influence scores would connect to the basic social networking taxonomy model I use to outline how online social networks function as communities.

• Who does a high influence networker influence as to target audience demographics?
• What target demographics would a business most effectively market to, in promoting and advancing its products and services, leading to completed sales?
• How do the high influence networker’s audience demographics mesh with those of the business’ target marketing demographics?

If a high influence networker’s circle of influence is enriched for the types of people who the business is trying to reach, with a significantly higher percentage of its members belonging to that marketing demographic than would be found in the general public, then this high influence networker and social media participant would make an effective spokesperson and avenue for reaching a market audience – just assuming here that they positively influence others.

I outline several types of high value, high influence networkers in my social media taxonomy posting (reiterating the pertinent terms and definitions here):

• Hub networkers – people who are well known and connected at the hub of a specific community with its demographics and its ongoing voice and activities.
• Boundary networkers or demographic connectors – people who may or may not be hub networkers but who are actively involved in two or more distinct communities and who can help people connect across the boundaries to join new communities.
• Boundaryless networkers (sometimes called promiscuous networkers) – people who network far and wide, and without regard to community boundaries. These are the people who can seemingly always help you find and connect with someone who has unusual or unique skills, knowledge, experience or perspective and even on the most obscure issues and in the most arcane areas.

If a business is trying to connect with and market to a very specific single demographic and it knows what that demographic is, then a well-placed and selected hub networker who is influential there, would probably be a best choice to seek out and involve.

If a business is trying to reach new audiences, or if it is uncertain as to precisely where its best marketing audiences actually are, boundary networkers and boundaryless networkers may important here too, for the business to connect and positively involve in new directions.

For a truly disruptively new innovation it may be crucial to bring in and involve boundaryless networkers as high influence enablers – and mine the connections that come in from them for insight into what marketing demographics they would most naturally belong to.

Effectively capitalizing on the social media influence of an effectively connected hub networker who is active in the types of communities that the business would seek to market to, means a very focused return on effort made to influence and connect. Influence and efforts to connect and share information in support of a product or service on the part of a high influence social networker would be more diffused if they are also or even primarily networking out of the realistic markets for that business – but that is not a problem where the best market may be new and disruptive too.

I am going to continue this discussion with my next series installment where I will delve into the issues of what constitutes positive influence. As a foretaste of that posting I note that conveying a genuine appearance carries more weight than simply coming across as a paid spokesperson, and that genuine voices do positively influence. Meanwhile, you can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 5: influence scores 2

Posted in macroeconomics, social networking and business by Timothy Platt on February 8, 2012

The predictable, effective valuation of online connections is simultaneously one of online business’ most vexing challenges, and one of its most enticing goals. This is my fifth posting in a series on the issues that collectively comprise that challenge (see Macroeconomics and Business, postings 42-45 for parts 1-4), and my second to look into one of the newer and more promising, or at least hyped approaches currently in the market for achieving this: influence scores (see Part 4: influence scores 1.)

In Part 4 of this series I outlined some of the problems and limitations to using social media influence per se as a predictive metric for gauging marketing and sales potential. I add that the concept behind this approach does appear to offer real potential as a source of actionable marketing intelligence. How would this approach be developed in practice, to sidestep the one size fits all limitations that I have already discussed? My goal in this posting is to explore two avenues for doing that:

Stochastic and deterministic models and how probability enters into this type of marketplace model, and
• Influence scores as a tightly managed and focused component of sector-based marketing.

But before I address them, I want to go back to the basics and discuss what social networking and social media connectivity per se are in this context. And I begin by noting something that they are not, but that is frequently assumed to be true and by many if not most online participants.

• Social networking and social media connectivity are not necessarily about getting or staying in contact with friends and family. A social media influence score measures influence based on the ability to drive action in others. It is not a measure of how closely you are connected to anyone who you are measured as influencing, and it is certainly not a measure of friendship or of interpersonal relationship. For people who achieve high influence scores, most of the people they influence, they have never even heard of and it is likely that they never will, at least as individuals.

So I start out looking at social networking and social media connections, direct and indirect in this context as a system of potential marketing leads. For businesses that seek to tap into these systems, that is the only meaningful way to view them. And I give a specific example.

• If a current, high image-value celebrity – consider the pre- and early teenage girl idol Justin Bieber, suggests that he really likes girls who wear some specific brand of makeup, that will most likely prompt girls in the demographic he influences to buy that brand of makeup – even though he does not know and has never even heard of most of the girls he is connected to through Facebook, directly as well as indirectly, and even though he will never see them, with or without that makeup on.

Note that this is a highly focused, demographic-specific example of where influence scores would hold marketing value, and an example within that of the well established practice of developing celebrity endorsements – marketing using high influence score participants before it was called an influence score.

• Marketing, and marketing that is directed in a meaningful way towards specific targeted demographics is all about probability, and about increasing the probability that members of a targeted group will favorably hear about a product or service, and act upon that knowledge by making a purchase.

This is not deterministic or even just near-deterministic, setting out to specifically sell to particular individuals as through a completely individualized marketing campaign and with an exquisitely personalized message. This is stochastic and seeks to simply improve the numbers at a demographics level. But this only works if it is organized and built around a detailed understanding of the market stratifications and groupings that are out there, and their behavioral dynamics.

• Influence score-based marketing cannot work if it is only done as a matter of indiscriminately marketing around people with high influence scores per se.
• Effective influence score-based marketing defines marketing strata and target groups in terms of specific influencers’ connectivity and influence reach.
• And that means selecting high influence score holders with care, and marketing to them as a demographic with care to enlist their support.

In this, influence score-based marketing is just another way of specifying and characterizing target groups for stratified marketing campaigns – and simply tapping into high influence spokespersons as per Klout or other scoring systems cannot consistently work.

• Think of effective influence score-based marketing as crowd sourced celebrity endorsement-based marketing.

And this brings me to my basic social networking taxonomy model and the strategies that highly connected and high influence networkers follow – and how that determines the monetizable value of their influence. I am going to turn to that in my next series installment. Meanwhile, you can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 4: influence scores 1

Posted in macroeconomics, social networking and business by Timothy Platt on February 3, 2012

This is my fourth installment in a series on the valuation of social media and social networking connections (see Macroeconomics and Business, postings 42, 43 and 44 for parts 1-3.) So far I have examined a range of measures and metrics that are used and both from the perspective of social networkers and from the perspective of businesses that seek to tap into social media to do more business. In Part 3: connecting valuation approaches I began a process of examining possible correlations between the two, and with a goal of:

• More effectively articulating how businesses can meaningfully make use of social media,
• Knowing what returns they gain on any social media investments they make.

In Part 2: a diversity of provider-side visions I wrote in part about eyeball and sticky eyeball counts and about how simply counting the page visits does not in and of itself give you actionable insight into marketing or sales effectiveness – even when you know that the people with those eyeballs are staying on your business’ web site and looking around a while before clicking away – the sticky side of eyeball counts. In Part 3, towards the end I raised the issue of a more recent social media metric: the influence score and I said that I would turn to consider that innovation next. And I begin that discussion here by making a few basic observations and by raising a question that comes out of them.

• Businesses seek out social media and online behavior metrics that can be used in successfully predicting rates of customer engagement, and that can be used to more successfully completing sales transactions.
• They seek to be able to make valid demographics level predictions so they can develop more effective marketing and sales tools, targeting the right market-level audiences the right way, and ideally they would also gain more personalized and individualized insight as well that would help them to more effectively market to specific individuals who they come into contact with.
• Sticky eyeball metrics were developed as a richer and more insightful predictive measure for this than simple eyeball counts. Quite simply, it became clear, and early in this process of developing better online marketing tools, that not all page hits or page visitors are the same, and that businesses need to understand the range of types of visits and visitors and act accordingly.
• A more effective measure of social media and online connectivity metric would offer a great deal of nuanced information about the people with whom a business at least potentially would come into contact with, and both for their potential direct engagement with the business and for their impact on others who might make purchases there.
• How do you develop a social media or online influence measure so that it offers more actual, actionable insight than the older eyeball and sticky eyeball counts do?

A number of online marketing information providers specifically offer social media oriented influence score data. Two that come immediately to mind for me are Klout (and see how they score individuals) and PeerIndex (and see how they score individuals.)

These businesses and their competitors seek to provide information and insight on who has what level of voice and influence online, and both directly and through the networks of contacts they have impact upon. So according to their metrics:

• An individual (identified as A) with a widely followed Twitter feed, a Facebook profile with a huge range of friends listed, and with a great many wall postings coming from them, and other indicators of active online interaction – and as a hub of all of this activity, would be measured as having a high influence score.
• A second person (identified as B) with a Twitter account they do not post to very often, and that does not have many followers would have a much lower overall influence score.
• But what does an individual’s influence score per se, unexamined as to the nature of their message say about anything?

I would argue that undirected, general measures of influence per se tell you no more as a business marketer than eyeball and sticky eyeball metrics do. A very, and even extraordinarily high-influence score celebrity who never posts or comments, or connects online in any way that by content connects with your business, is not going to have impact upon it. A lower, and even much lower-influence score social media participant who does directly address your business and products in their online voice might in practice have a much greater overall impact upon you – and particularly if their online message is spread off-line too, and to people who could realistically be your customers. And here that influence could be positive or negative.

And to stress an important point here:

• Online influence score metrics might seek to measure and include amplification effect value where a social networker’s voice is retweeted or otherwise repeated through a network by others.
• But even online, tracking the spread of influence is only going to yield lower range numbers, and off-line reach is not going to be included at all. Amplification of influence through indirect connections is at best difficult to measure or even detect.

But for this discussion, and much more importantly:

• Generic, one size fits all influence scores offer no value,
• As the only influence that matters for a business that would use this data is the specific influence that has direct impact on the business or organization itself and on its marketing and sales.

I am going to discuss this point in greater detail in my next series installment. Meanwhile, you can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 3: connecting valuation approaches

Posted in macroeconomics, social networking and business by Timothy Platt on January 28, 2012

This is my third installment in a short series on the valuation of social networking and social media connections and on the collective valuation of social networks that arise from them (see Part 1: a diversity of participant-side visions and Part 2: a diversity of provider-side visions.)

I have been discussing valuation and how social media connections are evaluated and rated for their value, and from both the social media consumer/user side and from the service provider side. And in both cases I have at least touched upon a range of measures and approaches that can be fit into two basic paradigms:

• Measures of connectedness per se, and
• Measures of monetary return from those connections.

Think of them as:

• Searches for value intrinsic to social networking and social media per se, and
• Value that can be developed from those connections but that is extrinsic to them and grounded in a larger marketplace.

(Note: I am going to separately consider online stores as they tap into and seek to find quantifiable value in social media, in a separate series installment. Here, I stress, I am only looking at the way that social media service providers such as Facebook, LinkedIn, Yahoo and Google (for their services in this arena) seek to leverage their social networks into establishing their overall monetary value.)

And I add as a qualifying note, that up to here, this posting is quite abstract so I will move to take it back to a more real-world context with an example – drawing from my own social networking and social media experience. I have a LinkedIn account that I do use. But I also have a Facebook account that I primarily set up because I was working with client businesses that were using it in one way or other – generally through their own Facebook pages. I still have it but I do not use it and I have been considering just dropping it. People still post to my wall, and I should clean a lot of that out but bottom line, mine is a moribund Facebook account – and all evidence I see indicates a very significant percentage of Facebook accounts fit the same pattern. And in fact a significant percentage of the overall Facebook community must consist of people who no longer even remember their logins to the site, or care. So let’s consider the actual monetary value to Facebook, or to any business that buys Facebook member data, or space on their profile page – directly seeking to monetize memberships. What are those member profile pages and their Facebook connections data actually worth, as predictors of future business transactions by those members, or as bases for initiating specific online transactions through placed ad links?

My point is that at best, scale of social network showing from overall site membership overstates monetizable value, and that is because all memberships and all connections to and between members are not worth the same. On one level, this simply reflects differences in social networking strategy (as I have discussed in Social Network Taxonomy and Social Networking Strategy, and in other postings available at Social Networking and Business.) But more than that, single individuals can in effect follow different strategies when connecting through different site venues, and they can and do show very different levels of active involvement for the sites that they are at least nominally members of, even if they follow the same basic strategy in principle on all of them – and even if they accumulate a significant number of direct connections-showing on all of them.

Activity going up on a Facebook wall might consist largely of what amounts to spam – content posted by a subset of active users, more or less indiscriminately on every wall they are connected to. And less actively maintained walls will accumulate this type of content and show activity that is in fact of this type. What is that worth?

• The basic monetization/extrinsic valuation assumption is that some directly, reliably knowable if not entirely known percentage of page hits, eyeball and sticky eyeball counts, etc predictably indicate entry into transaction processes that would lead to filled online shopping carts and online business completed.
• Or online activity would be viewed as a window into measuring and increasing awareness of opportunity for consumers in bricks and mortar businesses, and lead to increased foot traffic and business there, and once again in a directly predictable manner.
• But that is not true, and certainly when site memberships and profile page activity are not analyzed and partitioned according to sophisticated, nuanced models.

With that, I have outlined something of the basic challenge faced. I am going to continue this discussion with my next series installment, where I will look into influence score measures, and sites like http://www.klout.com and http://www.peerindex.com.

You can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 2: a diversity of provider-side visions

Posted in macroeconomics, social networking and business by Timothy Platt on January 22, 2012

This is my second posting in a short series on the valuation of social networking and social media connections and the valuation of social networks that arise from them (see Part 1: a diversity of participant-side visions.)

I started this series from the perspective of the individuals and organizations that go online to set up online member profiles and to, for whatever reason, market their presence. In the course of that discussion I at least briefly touched upon a number of perspectives as to how online social networking connections might be evaluated as to intrinsic value from the member perspective. I will be adding a few more points to that side of this overall discussion here in today’s posting too but I am primarily going to discuss the valuation, and more explicitly the monetization of social networking from the perspective of social networking and social media sites and businesses – the platforms that individual people and other businesses connect through as members.

As a starting point for that, I ask a fairly basic question, couched here in terms of two social media businesses that are currently in the news for going public: Facebook and LinkedIn. Speculation as to their actual value is as businesses, and overtly differently from that – what they would list as being worth from a stock sale are popular topics of discussion and certainly for people interested in either social media or in the investment marketplace.

• What is a social networking, or more generally a social media platform provider actually worth, going into an initial public offering (IPO)?

In a real sense the primary goal of this posting is to discuss some of the factors that would go into determining that value, and in coming to an arguably defensible position as to whether IPO share prices, at the end of that first day of trading leave this newly public business over-valued, under-valued or realistically valuated.

Valuation decisions are often made for social media sites on the basis of levels of public involvement and participation. This basic approach in fact traces in principle to the very first attempts that were taken pre- the first dot.com bubble-burst, to determine monetary value of online business ventures – eyeball counts.

• An online business would bring in X number of visitors in an average day or week, or as measured along some other benchmark timeframe unit. This number of eyeballs measured was cited as a surrogate measure of business marketing reach and value.
• But many and even most of these web site visitors would click away and leave just as quickly as they had arrived and with no thought of actively entering into let alone completing a monetary transaction. So claiming eyeball count as a measure of business value per se would be like claiming a bricks and mortar store’s walk through traffic was a measure of its financial value as a business – when walking through its ground floor was an easy shortcut for reaching a highly trafficked subway station and most people entering did so and left with that as their goal.
• So online businesses and their marketers began touting their numbers for sticky eyeballs – the count of people who clicked into a site and stayed for a while, perhaps clicking in deeper and to other site pages before leaving.
• Metrics like these were used in setting, and hyping valuation predictions for these early online startups as they prepared for the riches of IPO status, and with founders suddenly gaining on-paper wealth. But simply counting visitors per se did not and does not translate in and of itself into determining true, valid monetizable value for an online business. Simply visiting as web site – the online equivalent of strolling through and perhaps stopping to look a bit, does not readily predict levels of monetary transactions completed or the overall value of such transactions. And this disconnect between valuation predictions based on those eyeballs and what those visitors actually did on these web sites to create actualized monetary value, was one of the core factors that led to that first big dot.com bubble burst.

Facebook has 800 million registered members (mostly with free accounts) and if it has not hit that number yet it will very soon! As Yogi Berra would say, “that’s déjà vu all over again” as eyeball count monetization comes back, and certainly for events such as IPO’s and their initial offering prices and the stock prices reached in that first trading day.

Sites such as Facebook and LinkedIn do offer premium, for-fee services and with annual ongoing costs to members for them. This translates directly into revenue streams and realized monetary value. But this is not an eyeball count per se, as much as a measure of cash register activity for the people who stop to shop. This is, however, the point where eyeball-like measures begin to translate into arguably defensible bases for determining true business valuation. And what of other realizable and directly measurable revenue streams?

These sites can and do sell advertising space on their pages. And that can and does include higher value and higher priced targeted ad placement based upon matching advertiser and product to the details of the member profile that those ads would be placed on. So a profile for a new mother who has joined online groups through the site that are oriented toward being a new mother, would have ads for baby products added into its page template, along with products that a new mother would want for herself. A young man who joined groups related to team sports would see ads related to sports equipment and paraphernalia on their profile, as would others who visited their profile page. And increased monetizable value would come from mining the details and data of those profiles and of member activity as a whole on the site. (If that new mother was a site member and logged onto the site when she visited the profile page of her sports fan brother, her targeted marketing ads might follow her there, and show on his profile page for her instead of the ads that would be targeted towards him. Ad placement can be very nuanced in this.)

This is an important shift in perspective and approach, where these online businesses begin to monetize not the head count of members but the information they provide and information that can be developed about them from their site usage. And this can be demographics-level data that is anonymous with respect to any particular user/member. It can be information that is directly connectable to specific members and their profiles but only based on commercialized use of information that these members themselves designate as publically visible and by their choice. Or it can also include commercialization of information that members provide but that they have not indicated as data that they want publically visible, and even information that they indicate only select others should be able to see or that only the site administrators should be able to see. And this is where Facebook has gotten into significant trouble and where it has gathered some very bad press (see Facebook and the Importance of Respecting Social Contracts.)

• The most valuable, reliable ways for a social media or social networking platform online business to actually develop reliable monetizable value is for it to capitalize on the monetizable value of the member/user information it has in its systems.
• And the more comprehensibly and thoroughly they do this with offers of targeted marketing and sales opportunities, the more value they can generate for themselves as they develop channels for selling higher valued ad space and as they directly sell member data itself.
• But this creates real potential for conflict of interest with those members, and particularly as social media and networking businesses begin tapping into more intrusive and higher value data applications.

I am going to turn in my next series installment to discuss how social media consumer/user side metrics and social media service provider side metrics do and do not correlate and connect. I am going to follow that with a discussion of influence metrics and how they can be used.

You can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

Monetizing social networks and the valuation of social media connectivity – 1: a diversity of participant-side visions

Posted in macroeconomics, social networking and business by Timothy Platt on January 13, 2012

What is the value of a social networking or social media connection? Asked that way, this presents a question for which there can be no meaningful, valid answer. That is because any real sense of intrinsic value for these connections depends entirely upon the context of who would find or create that value. And that means there is real potential for asymmetry in perception of value for the different parties involved in a social networking or social media connection and relationship.

Just consider some of the participants in this:

• A participant might be a business that seeks to develop and cultivate a connected community for generating immediate sales opportunities, or as a source of longer term value from word of mouth and viral marketing.
• A participant might be a nonprofit or a not for profit that seeks to develop an involved and engaged community in support of its mission and vision.
• A participant might be an individual seeking to promote their own career, in search of job leads and opportunities or in search of clients.
• A participant might be looking to engage with others in support of or opposition to a position or action that they see as having social and community-wide importance.
• A participant might be seeking to expand their social reach, and by any of a seemingly endless range of possible criteria. Consider connecting with fellow alumni or alumnae of a shared alma mater, or fellow employees or former employees of a business or other organization. This may mean connecting together a far-flung family or other group, and as defined by essentially any criteria that might be seen as holding value by the person seeking to connect.
• This, of course is only a partial list and only claims at most to be that. And as a final example I will add that some people enjoy social networking for its own sake and simply enjoy connecting widely and to new people they do not already know.

Different participants approach social networking and social media with very different goals and priorities. And on top of that, different participants place very different levels of importance on both specific connections and types of connection, and on online connections per se.

• An open networker might connect freely and to most anyone interested in social-network connecting with them. But they might value one specific subset of their overall connections a lot more highly than others, and certainly when comparing connections to people they know well to casual-invitation connections from strangers.
• A business might rate its online connections for their value in terms of business history and the monetary value of those contacts as active, purchasing customers. Contacts who never engage with the business and who never even seem to seek to be customers would, according to this approach be viewed as of lower value as contacts than repeat-business customers. And customers who make referrals, bringing in new customers would likewise be seen as of higher value too.

Conflicts of valuation can arise where participants in a social networking or social media connection see different and even incompatible bases for determining value in online connecting. Consider a professional who social networks to meet and share ideas with people from their industry, connecting with someone who is only interested in pushing their products or services to make completed sales. That type of mismatch happens, and certainly on business oriented social networking sites such as LinkedIn, where members can feel they are being spammed at times by unwanted and unexpected sales pitches.

Conflicts can arise when different people place very different valuations on specific social connections they have or seek to have, and even within categories of connections that they in general value. Here that can express itself in terms of differences in timeliness of response, among other things.

These and other factors all go into determining how any given social networking or social media participant would set the valuation to their connections and to any activity that comes from them. And these factors and others like them – points of similarity and points of difference in approach, motivation and understanding, lead to differences and disconnects in how valuation is reached and to what value is assigned to them.

This is the first posting of what I expect to be a short series on the monetization of social networks and social media – here looking at them from the perspective of individual connections and of connections within and between groups and between people who align with and associate themselves with groups. In my next series installment I am going to step back to look at social networking and social media sites – service provider sites as one end of a continuum, and at businesses and groups that do not primarily do social media but that launch and manage their own online interactive presence at the other end.

You can find this and related postings at Macroeconomics and Business. You can also find this and related postings at Social Networking and Business.

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