This short manifesto covers what I hold to be self-evident about modern marketing practices, particularly related to online activity.
This piece about how people's attention flows on the web highlights the fundamental misunderstanding that causes almost all online marketing to be ineffective.
The blog that follows consists of a series of short posts that support my arguments.
Interesting observation that Social networks implode quickly.
Using search volumes as a proxy for ‘level of interest’ is inaccurate, especially with the advent of app-based access to social platforms, but these kind of charts are fascinating.
Is collapse an inevitable part of how these networks function?
A lot of SEO practitioners are touting the notion that social signifiers, i.e. ‘likes’, ‘shares’, etc. are also signals that are picked-up by search engine ranking algorithms. The argument is that these are more reliable indicators of popularity than links as it is likely that a real person is behind each signal. However, actual evidence that these ‘social signals’ cause fluctuations in rankings is non-existent.
I meant to highlight this post this last month as it is excellent - have a read to review the difference between causation and correlation as well as to assess the alternative explanations of what may be going on.
The way I look at this is that I understand the search engine algorithm to be a black box. I can see certain inputs I believe to affect the output but I have a hard time confirming the relative importance of these inputs. Over time, I believe that these signals have become more complicated, that the black box itself includes historical data that it has collected that it uses in its evaluation. I also believe that it is likely that the application of the algorithm is non-uniform - that is to say that certain factors are likely to affect the relative importance of other factors in the results on a case-by-case basis.
‘Social signals’ are by their nature ephemeral. If I was trying to return relevant results then of course I would consider these signals as potentially useful, say in combination with number-of-searches and other factors. However, the effect of these signals would be time-limited as the momentum behind them would be an indicator of whether people’s attention is staying with the topic or moving on to something new. For example, an affect of a decaying signal might be to ‘turn-down’ the similar results displayed as interest wanes. What concerns me is the implication that these signals replace links as a permanent signifier of relevance.
“I believe that future social platforms will behave more like infrastructure, and less like media companies. I believe that a number of smaller, interoperable social platforms with a clear, sustainable business models will usurp you. These future companies will be valued at a small fraction of what Facebook and Twitter currently are.”
Great observation. I can’t tell what Facebook is spending money on from the perspective of innovating on behalf of its users. It all depends on whether you defne a ‘user’ as someone who inputs their personal data into the platform or whether the real ‘users’ are the advertisers.
Same goes for Twitter. Seeking profit for shareholders appears to degrade the user experience as platforms implement the same advertising models.
Calling this an ‘ecosystem’ is appropriate in unintended ways: something is preyed upon in order to benefit something higher up the online food chain.
The ‘value’ of these platforms is entirely notional. Annoy enough people who have somewhere else to go and this value is completely destroyed.
With a tenth-of-one-percent click-through rate not including fraud or accidental clicks this is one format that needs to be consigned to web history.
Those who sell display advertising refer to this format as though it’s relevant to everyone who uses the web – much like live broadcast television advertising is utterly unavoidable.
I firmly believe this format, despite being plastered everywhere, only appeals to a certain type of user who are by-and-large in the minority. Furthermore such advertising is only applicable to a very limited set of products and services.
The idea that a ‘hover’ is a more applicable measure of success than a click on an advert is questionable. The correlation is trivial in either case and while I see it is possible to generate revenue from this medium and to gain further incremental performance gains via better use of data, I wonder whether this area is ultimately a dead-end.
Danah Boyd is great on this in Who clicks on ads? And what might this mean? by considering who is responding and thus who is being targeted when 99% of web users do not click an ad within a monthly timeframe.