The world is an ambiguous place. Multiple things can be true at the same time, which is hard to process. Humans crave simplicity and linear relationships. But the world isn't like that.
In Growth, we face this challenge daily. Ad campaigns, product-referral loops, and CTR optimization deliver drive results, but perfect causality is rare to find. There are two reasons for ambiguity in Growth:
- a) we're dealing with human psychology, which is not the same as physics
- b) when we deal with machines, such as Google Search, the level of complexity is high
Rory Sutherland brings this phenomena to the point in his book Alchemy:
"While in physics the opposite of a good idea is generally a bad idea, in psychology the opposite of a good idea can be a very good idea indeed: both opposites often work."
Making decision with several truths
Thriving in ambiguity means making better decisions. When facing ambiguity, our ego doesn't want us to look like we don't know what we're doing. We tend to pick the reason that fits best into our world view and ignore the other ones. That works out in some cases because we're lucky and develop an intuitive understanding of problems and solutions we face over time. That's why more experience makes better Growth experts. However, if we don't acknowledge the limits of our understanding, the presence of more than one truths, and why we make a choice, we can't develop a real understanding of what we do. It's not enough to know that something worked; we need to know why.
The why is rarely perfectly clear, which bears real potential for taking Growth skills to the next level. Growing the causal context muscle how we become better SEOs and Growth experts.
This piece is a follow-up to “A modern understanding of SEO,” in which I argue that SEO has become an “everything goes, so test everything” environment. Ranking signals are contextual and have high interdependencies. As a result, the zero-based SEO mindset comes with a lot of uncomfortable ambiguity. Making it easier to thrive in this environment is my goal with this article.
Ambiguity in Growth
The word ambiguity comes from the Latin word ambiguus, a mashup of ambi (meaning "both") and agere (meaning "to drive"). Ambiguous basically means that there are several "drivers" or reasons for a problem or solution.
Most problems in the world are multi-factorial. They don't have a single cause. So is SEO: say, you add schema to your site and see an increase in traffic. You're tempted to think that schema is a ranking signal.
But not so fast! Is the cause of the traffic increase rich snippets or something else? Are you 100% certain that nothing else, such as an algorithm update or a content refresh, happened during that time? Have you factored in seasonality? Or has Google crawled and re-evaluated your site more due to the code changes?
Maybe all of the above is true, which is hard to hold for our brains. It's the "dress problem," just in a different form. Awareness itself goes a long way, but there is more we can do.
More data ≠ more information
In the pre-internet era of marketing, John Wanamaker, the founder of Macy's and lots of other retail stores, made the famous statement: “Half the money I spend on advertising is wasted; the trouble is I don't know which half.”
The internet allows us to measure ad spend, target users, and know exactly where each dollar goes. Or do we? Cases of companies who cut their ad spend and see no change in customer acquisition pile up, for example, UBER, Chase, or Procter & Gamble. That is not to say that ads are de facto useless, but that we still don't exactly know where ad Dollars go.
We have more data than ever yet find ourselves increasingly overwhelmed. This phenomenon is not limited to advertising; it exists in all disciplines of Growth. The devil lies in the details: more data increases certainty but doesn't diminish ambiguity. Ambiguity and uncertainty are not the same. Ambiguity means there is more than one interpretation of a problem. Uncertainty means you’re missing information about the future and can't tell what's coming as a result. As such, uncertainty can be minimized with more and better data. Ambiguity, only to a degree.
While more data doesn't equal more information, we can agree that data is better than no data. We also need to acknowledge that data doesn't equal data. It has different degrees of quality. Search volume from a 3rd party keyword tool is not as qualitative as impressions in Google Search Console, for example.
Data leads to more clarity, but more data leads to more cognitive load after a certain point. The solution is to look for the highest data quality possible and gather enough to make a decision. Keep in mind that the right decision is an illusion. Any complicated problem can only have an optimal decision, something we need to get comfortable with.
Confidence = T x C x R
Confidence in data comes from trustworthiness, credibility, and reliability. We need to understand how tracking tools work and their limitations:
- Verify web analytics and tracking tools are implemented correctly.
- Learn how tracking works. Search Console clicks and organic sessions in Google Analytics are not the same, for example. Know what's being measured.
- Understand the limitations of tools. Search Console is not a good reflection of what’s going on in the SERPs. Some dark traffic is allocated to direct. Search volume is fundamentally flawed.
- Stay consistent. Pull metrics from the same tools - don't mix! You can (and should) use different tools but stay consistent with one metric from one tool.
The limitations of tools and metrics don't mean they're useless. Understanding them merely means you know what can be used when and how. Knowing the difference between operating based on intuition versus data is bliss. It creates clarity. Clarity leads to buy-in. Buy-in leads to getting stuff done.
Thinking in probabilities
The trick to making better decisions over time is to detach the outcome from the decision making process. In her book "Thinking in Bets," Annie Duke explains that we need to evaluate decisions based on the data we had when we made the decision. Steve Jobs' "You can't connect the dots looking forward; you can only connect them looking backwards" goes hand in hand with this idea.
Duke further describes the problem of imperfect decisions with a Chess versus Poker analogy: we try to look at problems from a Chess perspective, but they're often closer to Poker in reality. Chess is the idea that we know all options and possible outcomes. Poker is the opposite: the number of possible outcomes is unknown. You don't know the cards of your opponents.
SEO and Growth are the same: we have a rough idea of what works but need to think in probabilities instead of absolutes. Annie Duke describes what good Poker players do:
- a) Detached outcomes from the quality of decisions
- b) Acknowledge that luck always plays a role
- c) Reflect on decisions
We can adopt the same habits in Growth. I personally become very skeptical when people tell me they're 100% confident that something moves the needle. 90% confidence is a lot more realistic. There is always room for error.
You can't get around ambiguity, but you can learn how to thrive in it. Honesty about what you know and what not makes it easier to get buy-in and stuff done. Overconfidence leads to missing important details that lead to failure and untrustworthiness. Smart people sniff the BS.
Instead, acknowledge room for error and get comfortable with imperfect decisions. Stay consistent with data and look for the highest quality source possible.