Platt Perspective on Business and Technology

Social media demographics as a possible challenge to the Pareto principle, in online market dynamics 2

Posted in social networking and business, Web 2.0 marketing by Timothy Platt on August 21, 2013

This is my third installment to a response that I have been developing, to a question raised by a reader. My first part to this was offered as a reply to a comment appended to my posting: When Information Becomes Cheap and Ubiquitous Attention Becomes Rare and Costly, and I then followed up on that with a Part 1 separate posting that this one serves to continue. And my goal in all of this is to share some thoughts on how the Pareto principle is applied when modeling online commerce, and on what is automatically assumed when this is simply taken for granted.

The Pareto principle, as a reminder, is also often called the 80-20 rule where some 80% of all online business goes to some 20% of all same-marketplace vertical e-commerce web sites. And in practice it is often observed that a particularly stringent form of this rule can be in place in e-commerce with as much as 90 or even 95% of all online business in a vertical going to as few as 10 or even just 5% of the competing sites. I have discussed something of the dynamics of this process and of the mechanisms in place that would lead to this type of business transaction bottleneck. And I have also noted the danger of simply taking expected principles and rules, and practices based on them for granted – as disruptively emergent competitive offerings that successfully challenge them can undercut other businesses that rely upon them. That cautionary note applies to rules such as the Pareto principle as much as it does to any other automatic business assumptions. So I have written about an ongoing need to know what is being assumed and why, and to always keep at least some room for doubt that our assumptions might not universally hold and for all time – and even if the argument behind their applicability seems very sound. Assumptions simplify and streamline and can lead to greater efficiencies, when empirically validated. But they carry their own risks too.

• Know what you assume and why and under what circumstances and with what constraints and parameters of applicability.

And this brings me to a lead-in for the body of this posting that I added to the end of Part 1 of this short series. I raised the possibility that the processes and dynamics of social media and of viral marketing that comes from it might change the marketplace dynamics that lead to a version of the Pareto principle being followed. And to put that into operational context, I also noted that the Pareto principle as generally stated has its own underlying assumptions and that one of them is that the marketplaces and communities that it predictively models are simple and unstructured and certainly statistically at the consumer level.

• The Pareto principle assumes that marketplaces and communities of consumers in them are simple and effectively unstructured.
• Individuals differ and in many ways, but for purposes of this model and its marketplace, and consumer based analysis, when people are looking to purchase a gas barbeque grill, or a shirt, a book or music CD or essentially any other type or category of product or service, their individual differences blur into statistical insignificance when you look at overall marketplaces and at overall cumulative consumer behavior.

To take what follows out of the abstract, I would cite a working example of how a consumer-based marketplace and customer community can develop significant purchasing decision-biasing structure. And I will then at least briefly note how this can impact upon competitive position and for statistically significant numbers of businesses in a vertical – and how this fact might be capitalized on as an emergent business strategy by entrepreneurs who see this.

We have all come to see the internet and cyberspace as existing, in a fundamental sense, outside of our normal geographical spatial frameworks. We go online and as long as products can be readily shipped to us, it does not matter where we place an order to geographically, or where that order is actually shipped to us from. This only, generally, becomes a problem if some step in this system of processes breaks down. For this example, I am going to impose some significant geographic structure. The products in question are very, very perishable and need to be delivered virtually immediately if they are to be competitively fresh in this marketplace. And assume that this is an otherwise low-overhead business that smaller businesses can compete in and where economy of scale would not push them out. Need for immediately local sourcing plays into that, as much as do lower fixed operating expenses and overhead. Pizza delivery companies, florists and others count in their ranks a mix of large operations with widely distributed local operations that can be franchise-based or wholly owned and operated by the parent company. But these market verticals also support large numbers of smaller and more entirely locally based and operated businesses, that market themselves as members of their local communities and to consumer bases that value that.

If you look at this overall market space without regard to geographic localization and strictly in terms of the larger business competitors in it, and then look to see how many distinct business-owned web sites or phone-in systems capture what shares of the overall business traffic, you see a more widely distributed business success rate. The most effectively competitive individually capture less business than a straight Pareto distribution would predict and more businesses capture a significant fraction of the overall business and certainly when compared with the business activity levels attained by the top businesses in that vertical. Statistically, as noted in Part 1, the distribution of business performance levels shown, becomes flattened and more platykurtic.

This is a simple and even a simplistic example as geographic distribution is fairly obviously an important factor here, and local businesses can be expected to do well and to collectively account for a significant share of overall business completed – and certainly given the popular importance for so many communities to buy local. But I add that any significant marketplace partitioning or structuring factor is probably going to look fairly obvious – once it is explicitly pointed out.

• No one business might specifically gain special marketplace advantage by spotting a marketplace opportunity defining factor that would spread out the performance curve here,
• But a successful business might easily find itself slipping in its overall performance and competitive effectiveness, and find itself unable to identify any specific competitor whose success could tell it how or why,
• And because it does not see that there are crucial marketplace forces that its business model fails to address.

Here, consider the larger multi-outlet competitor that fails to see a rapidly and significantly emerging trend where its customers, and its now former customers are pursuing locally produced and locally owned instead.

As a final thought here, I stress that this has turned into a discussion that is a lot more about retaining competitive strength and marketplace position, than it is of breaking out of the pack to gain dramatically better standing there.

I am going to conclude this discussion here, though I am certain to return to issues raised in it in future postings. Meanwhile, you can find this and related postings at Social Networking and Business 2, and also at Social Networking and Business and Web 2.0 Marketing.

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