Why does Google prioritize garbage results?
And their unintended effect of not preparing candidates for interviews
I’ve realized that a lot of SEO strategy incentivizes writing garbage blog posts.
For example, my company Interview Query works on getting data scientists jobs through interview preparation. To accomplish our mission, we put out a lot of content in form of courses and example interview questions. And to acquire more users, we put a lot of that content on our blog for free.
So to acquire the most relevant users, we have to rank on Google for very specific keywords that result in high conversions to customers.
For example the term“Python data science interview questions” is an incredibly relevant search term for us because we have 100+ Python interview questions asked in real data science interviews.
However if you do actually Google “Python data science interview questions”, you’ll see the results that Google thinks is the most relevant.
And it’s absolutely garbage.
I can attest your interviewer will definitely expect you to know what Python is. But a data scientist knows that they’re likely NOT going to be asked “What is Python” in an actual interview. And the rest of the listicle doesn’t get any better.
In fact the next article on rank #2 has just as bad of results.
Don’t get me wrong, as a data scientist - you are expected to know what a list is. However, you will never be tested in an interview by them literally asking you “what is a list”. Rather the question will be an application of utilizing a list, like writing a function that generates a list, or parses a string into a list, etc…
But every single result on Google’s first page results in a listicle of some of the most ridiculously easy and non-realistic interview questions.
Which brings me to my theories on why Google is prioritizing this garbage.
Theory 1: People want garbage
Google is increasingly relying on featured snippets where readers don’t have to scroll through lots of text. Google can instead surface the answers to the reader without clicking into any search results.
But while this might work for simple queries like “What’s the temperature in Seattle right now?”, it doesn’t work for search queries that are complicated in nature.
This leads me to believe that the audience searching interview question keywords may actually want garbage. They want to be able to just memorize flashcards to FEEL prepared for the interview, when in reality the data science interview is made of comprehensive case questions, tough Leetcode style algorithms, and applicational SQL questions.
To me, these kinds of results only make sense if the skill level of the audience is at a complete beginner level. But because Google prioritizes engagement metrics like dwell time and bounce rates, complexity and nuance may actually be a stronger turn-off for the results they want to show.
Theory 2: Google overweights domain authority
Any domain incumbents will usually outrank any newcomers very easily in the space given their existing domain authority.
This makes sense because Google uses domain authority as reputation proxy for good results. Until you realize that it can lead to situations when companies look to exploit their domain authority for traffic growth in other subject areas.
Most companies in fact enact this strategy by grinding on SEO to establish authority in one subject area and then release less quality blog posts in a similar or completely different field.
Indeed is a great example of this. They recently released a new series of pages all around interview questions. And yes - they are mostly garbage but they started ranking quite quickly after starting this expansion given their historical dominance in the jobs space.
Theory 3: Google search is too easily gamified
This isn’t really a hypothesis as much as the state of what it is right now. There’s an entire case study on how Masterclass is able to rank for a keyword like “shallots” because they answer every single question about shallots you could possibly have.
But Masterclass is clearly building posts completely optimized for Google’s needs and not any one true reader.
The rise of SEO tools has surfaced keywords that are easy to exploit. Basically anything that gets >500 monthly keyword searches will be saturated with garbage content when you can outsource a team of copywriters to write content at scale.
Most companies will apply a formula of → (Cost of writing post) x (% of Success to Rank in 1st Position) x (Keyword Conversion Rate) = Return on Investment.
In conclusion - while it may seem like I am shaking my fist at Google, I’m not actually mad. They are trying their best make a very difficult problem fairly simple for billions of human users.
Google however is the traffic God. You literally write stuff that pleases them and then it funnels more traffic to your website. And yes there are other top of funnel traffic sources, but Google is definitely the main aggregator.