Cadence #4 - LODR & Network Effect

Hello, and welcome to this week's #Cadence.

This week I'm talking general marketing.

One of the great things about SEO is how so many people just "fall" into SEO by accident, some with (but a large number without) any form of business or marketing education.

Because of this, not all SEOs look at user behaviour through a people lens alongside the SEO lens - and when it comes to traffic monitoring, forecasting, and explaining fluctuations, it's important to be multi-lens.

Two key marketing concepts that all SEOs should be aware of are the Law of Diminishing Returns, and the Network Effect.

The Law of Diminishing Returns

The Law of Diminishing Returns is an economic concept that states that, as more units of a variable input (like labor or capital) are added to a fixed input (like land or technology), the additional output produced by the new unit will decrease after a certain point.

This occurs because, beyond a certain level of input, the efficiency of the production process starts to decline, and adding more resources provides less and less incremental benefit.

For Example

Imagine you run an online advertising campaign for your e-commerce store, allocating a specific budget to a particular marketing channel like Facebook Ads. Initially, as you increase your ad spend, you'll see a significant increase in the number of new customers and sales.

However, as you continue to increase your ad spend, you'll start to reach a point where the incremental growth in new customers and sales starts to decrease.

This could be because you've already reached most of your target audience or because you're bidding up the cost of advertising due to competition.

This example has symmetry with how we (SEOs) use the concept of Search Volume.

As queries and user journeys take different shapes, we might be able to anticipate the intent and actions of a large percentage of the people performing the query, but there will be a number still researching, or that query isn't their "destination query" but merely a "journey query".

We also run into this issue with greatly similar queries that really have the same answer. On paper we might see X queries with a combined search volume of Y, meaning page Z should convert Θ% into leads/sales - but we should only be looking at a percentage of Y to convert, and this will fluctuate depending on a large number of external factors (that you can identify through a PESTLE).

The Network Effects

Network effects occur when the value of a product or service increases as more people use it, creating a positive feedback loop that drives further growth.

This can lead to exponential growth and market dominance for the products or services that successfully leverage network effects. There are two main types of network effects: direct and indirect.

Direct Network Effects

The value of the product or service increases directly as more users join the network. Communication tools like WhatsApp or Skype are great examples of products with direct network effects.

The more people use the platform, the more valuable it becomes, as you can communicate with a wider network of friends, family, and colleagues.

Indirect Network Effects

The value of the product or service increases indirectly as more users join the network due to complementary goods and services becoming available. For example, Apple's App Store or the Google Play Store benefit from indirect network effects.

As more people buy smartphones and use these app marketplaces, developers are more likely to create and improve apps for those platforms, which in turn attracts more users.

For Example

Indirect Network Effects are commonplace in the SaaS world. A good example being Zapier. Zapier relies on demand for the products it helps connect together.

This needs to be a consideration in gauging your own demand, especially if your product or service is dependent on demand, usage, and "issues" with other platforms and services.

Both of these theories can be used to help explain changes in traffic that aren't necessarily explainable by concepts such as seasonality or set rhythms.

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