Why is Google Getting Worse? And What Can Regular Businesses Learn From It?

Why is Google Getting Worse And What Can Other Businesses Learn From It

Google is Getting Worse

In a recent blog post I discussed how a bottom of funnel search on Google would no longer trigger a  “blue link” search result that would send a user to a business that sells what the user is looking for. And that instead, Google is more likely to show that user one of the results below:

  • A Google ad
  • A listicle post packed with affiliate links
  • A reddit forum (Reddit’s unprecedented visibility seems to align closely with news of a new “expanded partnership” between Google and Reddit… hmmm)
  • A YouTube result (Who owns YouTube?)
  • A Google Shopping result
  • One of Google’s own featured results (e.g. People Also Asked)

I also asserted that:

“The chances of your home page or product page ranking well (on Google)l for a search that specifically describes the product or service that you offer is almost zero in most cases.”

In this article I will get off the fence and come right out and say what I was inferring in that post – “Google is getting worse”. That is my opinion.

How is Google getting worse?

There are 4 key reasons that would back up an argument that Google Search has gotten worse in recent years. Those are:

  1. It’s an fundamentally a different product now
  2. It’s full of ads
  3. It prioritises Google-owned properties 
  4. It’s flooded with spam and shitty affiliate content

1. It’s an fundamentally a different product now

According to the Oxford English Dictionary, via Google Search itself (I’m aware of the irony of using Google as a source in a post lamenting the decline of Google), the definition of a search engine is as follows:

“a program that searches for and identifies items in a database that correspond to keywords or characters specified by the user, used especially for finding particular sites on the World Wide Web.”

I’ve worked in SEO for 10 years. To me, Google is a search engine. At least Google was a search engine. In fact, it was the best search engine the world has ever seen. In the early “don’t do evil” days of Google, it’s search engine was at its core a groundbreaking, user-focused product that acted as a gateway to brave new (but, up to that point, messy and unorganized) world of the world wide web. It gave rise to the, now cliché, concept of having “the entire world’s knowledge at our fingertips”.

According to Google themselves of 26/4/24: 

“Google’s mission is to organize the world’s information and make it universally accessible and useful. That’s why Search makes it easy to discover a broad range of information from a wide variety of sources.”

So Google is still a search engine in that it “searches for and identifies items in a database that correspond to keywords or characters specified by the user”. However, there is no mention of finding particular sites or sending users to websites or anything of that nature. Google still technically meets the Oxford definition of a search engine, but there’s not doubt that it’s now a very different type of search engine.

In a 2014 annual report it filed with the U.S. Securities and Exchange Commission, Google themselves stated:

“We used to show just ten blue links in our results. You had to click through to different websites to get your answers, which took time. Now we are increasingly able to provide direct answers which makes it quicker, easier and more natural to find what you’re looking for.”

I’m unsure who first made this point or coined this term, but Google, realistically, is more appropriately categorized as an “answer engine”. Whether you consider that particular type of search engine or a separate category of software entirely doesn’t really matter – the key point here is that Google is no longer a search based directory of websites, it has evolved far beyond that initial concept.

2. It’s full of ads

Sergey and Larry initially were vehemently opposed to ads within search results.

Ben Gomes was also intent on keeping organic search and paid search separate.

However, at a certain point – in keeping with the general trend amongst many the biggest “people-focused” websites in the world – Google stopped viewing Google Search as a product to delight customers and began more and more to see it as a big, juicy, profitable, online advertising space. 

The creep first began in 2016 with the introduction of a 4th Google Ad space above Google Organic Search results and has culminated today to a point where up to X% of Google’s SERP is paid-for adverts.

Take a look at the example below for a search for “mens trainers” – the entire space “above the fold” is taken up by ads.

3. It prioritises Google-owned properties 

The Google antitrust lawsuit is complex and wide ranging and I won’t attempt to explain it in its entirety in this post. In a nutshell, federal prosecutors have accused Google of using its deep pockets and status as the dominant internet search engine to shut out rivals and stifle meaningful competition.One part of the argument is around how Google’s search results are skewed towards its own properties and products.

If you have been an active user of Google over the past number of years you will have noticed an increase in two particular broad types of results – those are:

  1. Results specifically promoting Google owned properties
  2. Google owned “rich results” 

Results specifically promoting Google owned properties

The argument in the antitrust case around promotion of Google owned properties is that Google systematically ranks its own services, like Google Flights and Google Hotels, higher in search results, which can disadvantage competitors. This preferential treatment steers users towards Google’s products over others, potentially stifling competition.

Not only is this a bad thing for Google’s competitors but it’s also arguably bad for users for a number of reasons namely:

  • Choices based on biased information: The commercial interests of Google may conflict with the informational needs of users. If Google highlights its own booking services for flights and hotels over other possibly cheaper or better options, users may not be aware that better or more relevant alternatives exist beyond what is prominently displayed and ultimately will make decisions that are not entirely based on the best available information.
  • Overall reduced choice in the long term: By promoting Google owned properties and limiting the visibility of alternative providers and offerings, competitors will  receive less traffic and, consequently, less revenue. This can stifle innovation and slow the improvement of services across the industry. This can lead to stagnation in the quality and variety of online services and products available to users.

Google-owned “Enhanced Results”

Enhanced results like featured snippets, knowledge panels and “people also asked” results appear prominently in Google’s search results. So, even if a business appears at the very top of the traditional “blue link” results on Google, they will have reduced visibility owing to competition from one of Google’s own enhanced results

In the Google antitrust trial, it is argued that Google’s use of enhanced can similarly bias users towards Google’s content and services. These features often pull data directly from websites or generate summaries from them, which might not always present the most accurate or neutral information. Critics argue that this practice can mislead users and harm other sites by siphoning traffic.

Google Search Generative Experience

One other new Google-owned search result type that is barely mentioned in the antitrust trial is Google Search Generative Experience or “SGE”. The reason for its glaring absence is quite simple – the antitrust lawsuit largely pre-dates the rollout of SGE. 

So what is Search Generative Experience (SGE)?

According to Google:

“Google Search Generative Experience (SGE) is an early step in transforming the Search experience with generative AI. When using SGE, people will notice their search results page with familiar web results, organized in a new way to help them get more from a single search.”

Put more simply, SGE is like Google’s version of ChatGPT within the Google Search Results. It will provide users with AI generated answers for their queries. And these AI generated answers will appear above the regular “blue link” search results.

Google SGE was beta launched in May 2023, but it was only available to those who have signed up specifically for it through Google Labs. It was set to be launched fully into Google’s regular search results in late 2023 but Google appears to have rowed back on that as per this statement in Jan 2024: “we’ll continue to offer SGE in Labs as a testbed for bold new ideas”. Whilst we don’t have a date for a full rollout, as of March 2024 Google is now testing AI overviews in the main Google Search results, even if you have not opted into the Google Search Generative Experience labs feature.

Does SGE make Google Search better?

Google claims that “SGE is rooted in the foundations of Search, so it will continue to connect people to the richness and vibrancy of content on the web, and strive for the highest bar for information quality.”

The reality though, as per this Washington Post article in April 2024, is that “SGE sometimes makes up facts, misinterprets questions and picks low-quality sources — even after nearly 11 months of public testing.”

Not only that, but as per Forbes, SGE has been found to deliver “a nasty menu of dangerous malware and scams”.

In Google’s own documentation an SGE result looks like this:

In reality, some SGE results looks more like this:

4. Besides ads, it’s flooded with spam and shitty affiliate content

From an anecdotal perspective, I’ve been hearing more and more about how Google’s results (even outside of the ads, the results from Google-owned properties and the SGE results) are getting worse and worse. Stephen J Dubner of the popular Freakonomics podcast summed it up well in this episode when he said: 

“My search results just don’t seem as useful. I feel like I’m seeing more ads, more links that might as well be ads, more links to spammy web pages.

Okay maybe this one is not Google’s fault. The general consensus is that Google has been hijacked by a bunch of manipulative, black hat SEOs who trick it into showing their lazy, spammy, unoriginal, deceptive content. The motivation? So that they can make a fortune through affiliate marketing links and online display advertising.

On a totally unrelated note, Google Adsense is the most common display advertising platform in the world. In 2023, Google’s ad revenue from display ads and other Google Network ads was $31.316 billion, which is 10.20% of its total revenue of $307.4 billion. In an alternate universe where Google was actually a sneaky, growth obsessed, greedy entity, they might even decide that it might be worth their while prioritizing sites on their SERP that serve Google display ads.

That last tinfoil-hattie paragraph aside, Google has actually acknowledged the growing visibility of spammy and ai-generated content and has been taking steps to address the issue e.g. the March 2024 spam-focused algorithm update. It’s too early to tell, however, whether or not this  update has had the desired effect.

Incompetence vs Malice

So, based on the evidence above, it’s my assertion that Google has become worse over the past 10 or so years. But why?

Hanlon’s Razor states:

“never attribute to malice that which can be adequately explained by neglect, ignorance or incompetence.” 

So the question is – can this decline in usability, effectiveness and user-focus be attributed to incompetence or to malice?

The argument for malice

Any argument that the decline in quality of Google’s search product is a result of malice needs to demonstrate intentional actions or decisions by Google that knowingly degraded the user experience or usability for financial gain or other strategic benefits, despite understanding the negative impacts on the users. Essentially, Google has favored hyper-growth at the expense of a great product.

Luckily for me, Ed Zitron has already made the argument in a manner so thorough and eloquent that I haven’t really needed to spend much time researching or structuring it myself. I would advise you to read Ed’s piece on “The Man Who Killed Google Search” in full but for brevity, I will do my best to summarise the key aspects of the argument:

Ed argues that Google’s leadership began to prioritise revenue over user experience through decisions to manipulate the search algorithm to increase ad revenue even when it contradicted the quality of search results. His points include:

  • Google purposely blurred the distinction between ads and organic results (by reducing the clarity of ad labelling)
  • Google held discussions around engagement hacking methods (i.e. increasing search queries by making search results worse) to increase search queries which for some reason was a KPI
  • Google may have rolled back changes that were made to maintain the quality of search results*

(*Ed admits that this is an educated guess on his part and presents no concrete evidence)

Overall, the article suggests Google undertook a deliberate strategic realignment that knowingly compromised the product’s core value — unbiased and effective search results.

The argument for incompetence

“Sure, even Google doesn’t know how Google works”

That was a dismissive comment by a lead developer at an agency that I worked for back in the relatively early stages of my SEO career. 

My knee jerk reaction at the time, if I had had the confidence to actually argue with him, would have been to defend Google and explain to him that actually Google was pretty straightforward – you write great content, build relevant links and ensure your website is technically sound and voila – you rank well on Google. That was, after all, what all of the SEO training and resources had told me and those three “pillars of SEO ” had been the anchor of all the SEO work I had done up to that point – and sometimes it had been really successful. The comment however stuck with me ever since, and every day since then a slow realisation has gradually taken hold of me – he was on to something.

That comment was probably in around 2016, not long after Google had introduced RankBrain. Prior to RankBrain, Google had already been using various forms of machine learning to improve search results. That being said, RankBrain, introduced around 2015, was a significant advancement because it utilised deep learning techniques to process search results and was arguably the metaphorical handing over of thekeys to Google’s Search algorithms from developers to machines. 

Have a look at the screenshot of one of the transcripts from the Google antitrust case in the US where Google’s Vice-President of Search, Pandu Nayak .

Source: https://thecapitolforum.com/wp-content/uploads/2023/10/20231018-APM-BT24-AM-Google.pdf 

It’s important to note that one mitigating factor for the shift towards machine learning in recent years is the barrage of shitty AI-generated content that has exponentially flooded the internet in recent years which has made Google’s life much more difficult.

That being said, machine learning models tend to be highly complex and capable of learning from data without explicit programming for every scenario. On the plus side, this means that they can autonomously “improve” their algorithms based on new data. On the other hand, this level of machine autonomy can make it challenging, or even impossible, for developers to predict or understand the model’s final decisions (e.g. in the case of Google Search, SERP rankings) or to tweak the system in order to align it more closely with the desired outcomes. The Google algorithm may essentially have become a “black box”.

Therefore the argument for incompetence, I would suggest, is this: as Google’s Search algorithms have become more sophisticated and reliant on machine learning and ai for the functionality of Google’s information search, retrieval and ranking processes, the sheer complexity of managing and integrating these systems effectively may have overwhelmed even a well-intentioned development team, resulting in a suboptimal product.

My Opinion – Why Google is Worse? And What Lessons We Can Learn?

To be perfectly honest, I think it’s more-or-less impossible to unravel this whole mess and land at a single, definitive answer as to why Google has gotten worse. If it is possible to do so, I don’t think I am the guy to do it.

My best guess, for what it’s worth, is that Google’s decline, in reality, can be attributed to a mix of overlapping reasons:

  • An obsession with growth at all costs
  • A blind trust in machine learning and AI 
  • FOMO around not incorporating AI into their customer facing product

With that in mind – in the rest of this section I have expanded on each of those reasons and proposed some lessons that can be learned by other businesses.

Reason 1: An obsession with growth at all costs

Between 2016 and 2022, Google’s revenue grew from $89.98 billion to $279.8 billion (Statista) whilst over that same period, customer satisfaction with Google as measured by the American Customer Satisfaction Index, dropped from 84 to 75.

I don’t really need to say much more here – I think the graph says it all.

Lesson 1 – Focus on Sustainable Growth Rooted in a Strong Value Proposition

For the past decade or a little more, there has been an unprecedented rise of venture investment and a sprawl of internet-based and digital-driven startups. Due to the availability of VC funding, many startups chose to operate on the principle of aggressive growth, often sidelining sustainable unit economics. They prioritised short term growth even if it was at the expense of long term stability, product quality and long term user satisfaction.

I’m not a financial expert by any means but it seems obvious that this growth in VC funding was not sustainable. And we are seeing from 2022 a significant downturn in the amount of VC investment worldwide.

This downturn in the availability of easy money has been driven by a whole host of factors, none of which I’m qualified to talk about – things like rising inflation and interest rates, supply chain disruptions, geopolitical uncertainty, market saturation in previously VC heavy sectors (e.g. fintech and consumer tech) and volatile public markets.

The result of all this is that startups can no longer afford to focus on growth at all costs. Whilst the main fallout of Google’s hyper-growth focus thus far has been a dip in customer satisfaction levels and some negative PR, for smaller businesses the impact may be far more significant.

Instead organisations should return to sustainable growth strategies which, in my opinion, should be built on the foundation of excellent products and customer service. Focus on unit economics, develop a genuinely useful product that’s a breeze to use, build long lasting relationships with your customers through excellent customer service and taking on board feedback, cultivate a strong company culture consisting of a team with shared vision and values and always be on the lookout for strategic partnerships – mutually beneficial alliances with other businesses can help to bridge the gaps left behind by the declining availability of VC funding.

Reason 2: A blind trust in machine learning and AI 

“And so we would develop ranking functions by hand, which we understood the properties of. And the reason for wanting this understandability was that when things went wrong, which they reliably did, you wanted to go back and understand what about your system led to that failure. And by understanding the system, we felt that you could actually do a really good job of fixing it and improving your system.”

As we’ve seen already, that is an actual quote from Google’s VP of Search, Pandu Nayak, after which he went on to admit that actually from 2016 onwards they decided to use machine learning more and more in Google’s search engine algorithms.

It’s my belief that in the vast majority of cases, leaving too much responsibility for the workings and behaviour of a tech product to machine learning and AI results in a shittier product. Google’s own Search product is a case in point. 

Lesson 2 – Stop Trusting AI So Much

Caution should be taken when it comes to deciding on the amount of power and trust to put into machine learning models.This reality is not exclusive to the development of algorithms or tech products but also when it comes to a bunch of other areas:

  • Online Content Creation
  • Creative Industries (Music, Art, Writing)
  • Legal Services
  • Education
  • Healthcare
  • Customer Service

AI may be able to do certain niche tasks that need to deal with massive amounts of data analysis and pattern detection really really well, but when it comes to tasks requiring creativity, emotional intelligence, and ethical judgement AI tools should be seen as assistants that need to be guided, managed and kept in check by humans with actual expertise.

I think that many companies are losing sight of that and jumping on the AI hype-train and allowing machine learning algorithms to determine the final destination (which is usually a total shithole). 

Many of the current broadly-focused generative AI tools (I would include Google’s SGE in this category), in particular, have a serious inherent limit to their capabilities and the quality of their outputs (in the case of SGE the output would be the answer to a search query) which may not even be possible to fix – check out the “Degenerative AI” section in this newsletter from Ed Zitron (again).

Reason 3: “FOMO” Around Adding Generative AI to Their Core Product

Did Google really need to introduce SGE when they did? I honestly don’t think so. It is possible that the popularity and public interest in ChatGPT following its release spooked Google. The release of Microsoft’s Bing with integrated AI capabilities, leveraging an enhanced version of ChatGPT, probably added further pressure. Is it possible that Google rushed the launch of SGE because they got caught up in all the hype around “ChatGPT replacing Google”?

Let’s be clear – ChatGPT is NOT a search engine. It is a Large Language Model (LLM) – a fundamentally different technology. When an LLM receives a query: “it must then predict what word comes next. To do this, the model generates probabilities for possible next words, based on patterns it has discerned in the data it was trained on, and then one of the highest probability words is picked to continue the text.” (CSET)

It’s a different solution where there is only very partial overlap – there is arguably only a single use case where Chat GPT competes with Google Search – that is for informational queries. Chat GPT is designed to provide answers to straightforward questions based on the information it has been trained on. It’s quite good at that. Then again, so is Google – Google’s own featured snippets have been doing a similar job for years.. and one advantage that featured snippets have over Chat GPT responses is that you can see who actually wrote the answer and decide yourself whether or not you trust their authority – as opposed to blindly trusting a bot who’s come to it’s conclusion through structuring each word in it’s answer piece by piece based on probability.

There is a distinct possibility that Google got spooked by the perceived AI focused advances of other consumer focused products like ChatGPT and Bing and altered their strategic direction based on a kind of paranoia. What’s notable is that they probably didn’t even need to worry that much.. According to The Wrap: “ChatGPT hit its traffic peak in May 2023 with 1.8 billion web visits, but tailed off during the summer. By August 2023, visits were down 21% from its high and they haven’t recovered since.” And whilst Bing’s market share has grown slightly to 3.35% in March 2024 (for comparison it was 3.19% in 2022), it’s still lower than it was in 2014 suggesting that Bing’s integration of AI results isn’t turning out to be the disruptor that Microsoft hoped it would be.

Lesson 3 – Don’t Be Paranoid – Focus on Your Own Business

There’s no doubt that a failure to innovate and adapt can kill a business. But it’s equally true that businesses can fail by focusing too much on their competition and not enough on themselves. You don’t need to be everything to everyone. 

Sure, it’s a good idea to keep a close eye on your competitors and new products or features that they might be working on. But you don’t need to jump head first into copying them – especially if it doesn’t align with your current strategy or user base. Try not to get too caught up in the hype when a new or existing competitor comes up with something new and novel – be logical and put time into analysing whether or not it actually poses a threat to your business model and whether that threat is a short term or long term one. Then react accordingly. 

In conclusion…

From the perspective of most users, there is a strong argument that the Google Search product has gotten worse in recent years. There is no doubt that Google has faced a bunch of challenges in that time that were not of it’s own making (black hat SEOs, the rise of ai generated content, etc.). However there is also a strong case to be made that Google has played a significant part in it’s own “downfall” (from a customer satisfaction perspective, not a revenue perspective) whether that was through incompetence or malice or a mixture of both.

There are some early signs that Google’s latest Helfpul Content Update has began to deal with some of the spammy affiliate content that has been plaguing the top of the SERP in recent times. However, many of the other significant issues that I have discussed remain.

It’s difficult to predict what the future of Google Search looks like – ultimately, running an organisation of the scale of Google brings with it significant pressure’s to continually deliver shareholder returns. I would argue though, that Google need to do a better job of balancing this hunger for hyper-growth in the short term with a focus on customer satisfaction that they embodied in their early days if they are to maintain market share in the longer term.

The point of this article though was not for me to provide business advice to the 5th most profitable business in the world. It was to delve into where Google Search has got worse, propose a few potential explanations for this decline and offer some advice to regular businesses who cannot afford to make the same mistakes. I hope I’ve been able to provide some useful food for thought and would welcome any feedback or discussion on the topic!

darren mcmanus seo

Darren is SEO Growth Lead at Velocity Growth. He is experienced in developing bespoke SEO roadmaps and implementing long term SEO strategies to build organic visibility, traffic and conversions for clients across a diverse range of industries.