For some time now, online marketing has become the new holy grail of daily business. If you’re in PR and you can’t manage digital marketing, you’re doomed. If you’re in marketing and you haven’t adjusted to the new online medium, you’re screwed. If you’re in media and did not switch to online, you’re clearly passé. Not to speak about startups. If you ever think about launching a startup and haven’t considered your online presence yet, you shouldn’t even bother.
One thing is clear, though. Life moved online.
Given than, it becomes pretty self-explanatory why everyone is praising all-things-digital. It is also obvious why a growing number of people are writing how-to manuals about “how to win the digital war”.
Like any other fashion, it comes with trends.
There’s even a wide variety of names employed by digital marketers to convey methods that can help you win online. Brian Halligan and Dharmesh Shah call it “inbound marketing.” “Our conclusion was that interruption-based, outbound marketing techniques were fundamentally broken and in order to successfully break through the noise and connect to people, companies needed to rethink the way they marketed from the bottom-up. In other words, they had to ensure their customers could find them using inbound marketing.”
Ryan Holiday, channeling Andrew Chen, calls it “growth hacker marketing”. They both dismiss old marketing techniques and praise new tools meant to skyrocket your product and engage customers. “A growth hacker is someone who has thrown out the playbook of traditional marketing and replaced it with only what is testable, trackable, and scalable. Their tools are e-mails, pay-per-click ads, blogs, and platform APIs instead of commercials, publicity, and money.”
At first sight, these authors cheer the possibilities offered by internet’s mere existence. However, despite correct theorisation, there’s a space left blank: entropy (of social systems).
Drawing from thermodynamics, entropy implies the tendency of social networks and society at large to break down over time. The outcome is that of moving from cooperation towards conflict and chaos.
In 1948, Claude E. Shannon wrote a paper called “A Mathematical Theory of Communication”. He points that each symbol in the sequence of a message depends on certain probabilities, varying according to the previous symbols already transmitted. Entropy, in his view, quantifies the amount of uncertainty involved in sending-receiving a message. And this happens due to channel noise.
To give an example, flipping a coin provides less entropy than rolling a dice. Hence, the more complex a system, the higher the entropy and the degree of randomness.
In the same fashion, a group of individuals choosing to act in a variety of ways will impact the social structure and the existing rules.
As internet is a highly complex system, it is improbable for any tool to guarantee control and predictability. Be it SEO, SEM, content marketing, google ads, blogging, etc.
Also, systems rarely perform exactly as pure theory would predict.
Thus, nothing guarantees, but hundreds of hours poured into testing. Or investing every bit of your energy in building the best product. Or exhausting yourself with lobbying. Or involving the last of your acquaintances who can help increase your visibility.
Except for that, nothing and nobody will help. Books can only suggest. People can only advice. Instruments can only guide. But nothing can guarantee.
As Tim Ferriss points, in this very instructive post: “If you listen to the advice of internet pundits, they’ll tell you how you “need to” use podcasts, SEO, SEM, marketing automation, email marketing, webinars, and on and on. Ignore them. The worst thing in the world is to be mediocre at 15 different platforms.”
So, what nobody tells you about online marketing is this:
a) it is a highly complex system
b) a lot of what happens is algorithmically determined
c) in order to be able to predict you need to have a good knowledge of mathematics and statistics
d) digital marketing is closer to engineering than to PR
e) it’s not cheap at all, let alone free
f) it requires gallons of patience and analysis
g) real life networks are fundamental for scaling
h) it has a high degree of volatility
i) consistency and iteration are key, but they won’t promise anything
j) it’s frustrating, but worth trying