Much has changed since 1998 when Larry Page and Sergey Brin officially launched Google Search.
21 years later, Google products are an intrinsic part of everyday life. It affects how we find products and companies (search), how we go places (Google Maps and Waze), how we communicate (Gmail), how we surf the web (Google Chrome), how we shop (Google Shopping), how we consume information (Google News), how we spend our free time (Youtube), how we control our home (Nest, Google Hub) and how we interact with the world (Android & Pixel).
The business world has also been affected by Google. From corporate email (GSuite business), to advertising (DoubleClick and AdMob), to user insights (Google Console & Google Analytics), Google has constantly looked beyond searching to diversify its core business.
It's important to note upfront that, with some exceptions, Google's mission has remained fairly constant: allow people to find and engage with the people, companies and products they seek.
The best way for Google to achieve this has been a concentrated effort to become the operating system of the world across channels and form factors.
But here's the catch: for Google to be successful, it needs to feed massive amounts of data into its algorithms.
Data drives relevance.
So Google needs to constantly stay two steps ahead to ensure that it is positioned in such a way that the company can collect data, interpret it and churn out personalized recommendations.
That's why, in this issue of the Website Magazine, we pay close attention to the latest advancements, rules and SEO changes Google has put in place to better refine results based on user search intent, local search results, voice search results optimization, fresh content, SEO & SEM changes and much more.
That's just one part of the picture.
Google is chasing the future. And the future is interconnectivity. The future of Google and, dare we say, the world, is profoundly interconnected.
Whereas searching will remain the backbone of Google, the company needs to evolve far beyond that. And it has.
A few years back, Sundar Pichai provided a rare glimpse into Google's vision for the future. He said:
'We've been thinking hard about how we help organize users' information on mobile. It's core to our mission of what we set out to do. [With] those kinds of things, it helps us to step back, think about it, and do it better.'
At the core of this statement lies a series of ideas that need to be unpacked further:
Google's thinks of itself as an information broker
Google continues to believe mobile is the center of information sharing
Google believes it needs to invest more into information organization (aka artificial intelligence).
So what is the future according to Google? What is the foundation on which this future is built?
As we mentioned above, the future is all about interconnectivity. Which presents the question: how is Google moving towards an interconnected world?
In this article, we will examine the most important and pervasive themes propelling Google into the future:
An AI-driven quest for relevance
A big data approach to personalization
A redefined advertising vision
An interconnected IoT world
All - powered by search. All driven by a necessity to embed Google in our everyday life.
Let's look at each of these themes in more details.
Google has been using Artificial Intelligence as part of their core business since before the term AI was part of everyday speech.
The entire Google search results logic is based on automated algorithms that make decisions based on what content is relevant for what audience.
For those unfamiliar with Google search results, we suggest starting with the introductory article on SEO we have included in this issue.
In a nutshell:
Google uses the famous Googlebot, a web crawler software, to index the internet.
The bots are always at work. They auto-magically surf the internet, capturing and following each page that is ever linked with even one link.
The bot finds new content on each website it visits, then it visits every subsequent link included in a site, be those internal links or external links.
It does so in a loop, constantly discovering new parts of the internet. The more links it finds pointing to a specific page, the more it considers that page to be relevant to online surfing as part of Google Search Results.
Lastly, as Yoast points out, there isn't one single Googlebot. There are at least five different ones indexing the digital world across text, images, video files, news and mobile apps.
But Artificial Intelligence, in Google World, has evolved WAY past the good ol' Googlebot.
As early as 2011, Google invested in the Google Brain project - the first automated algorithm employing image recognition. The first experiment was simple. Google needed to prove that it can correctly identify a cat in a phone.
Since then, Google Brain has dramatically expanded to include voice recognition, Google Translate results, analyzing videos for content and context, culminating in 2018 with Google DeepMind, the first conversational AI that can make calls to restaurants and make a reservation.
Across the board, the primary function of the vast majority of Google's AI investments have been tied to Google's most fundamental goal: to offer customers the information they seek. Nowadays, Google Maps, online search results and smart assistant are smarter than ever - and way ahead of their competition.
That's exactly what Google wanted: to build the most powerful, accurate and helpful search results to connect users with the information they're looking for in a heartbeat. If you want to learn more about how Google is experimenting with AI - they have a site for that. It's called Experiments with Google. It can be accessed here.
Big data is a term often used by tech people to define a process by which machines can interpret massive amounts of information to provide actionable insights to a user or company. Here's a standard definition of Big Data from Digital Authority Partners:
Big data is generally defined as a large set of complex data, either unstructured or structured, that can be effectively used to uncover deep insights and solve business problems that could not previously be tackled with conventional analytics or software. Data scientists usually employ artificial intelligence powered analytics to constructively evaluate these comprehensive datasets in order to uncover the patterns and trends that can provide meaningful business insights.
Big data is the very foundation of everything Google has ever attempted to do. GoogleBot is the first example of big data looking at billions of data points to structure the internet as search results. But it goes way beyond that.
One of the most commonly known big data strategies leveraged by Google is tied to tracking web and mobile cookies. With browser cookies (ex., Chrome), Google stores information about every single website a logged-in user has ever visited. As Google has begrudgingly confirmed again and again, they store our user data for ever.
How does Google use this data? It's simple.
User level data (ex., sites visited, user location, interactions with sites and Google Maps) allow Google to constantly refine what they show us to ensure that the results are better and more accurate over time.
They do this in two ways: 1) by constantly changing their algorithms to better refine individual search results (user does A therefore user will be interested in X); and 2) collectively across users with similar attributes (user A is like user B, user A likes X, therefore user B may like X as well).
Another great example of big data from Google is tied to its consistent and predictable updates to Google search results based on semantic and literal search results.
Literal search results means just that: Google is looking at exactly what a user is typing into the search engine, then maps that information onto an existing inventory of articles and multimedia assets.
Semantic search results refer to a super complex big data algorithm that learns from what content people are consuming online in order to surface relevant results even if you didn't type in the exact search terms.
Say you are looking online for "artificial intelligence in pharma." Google will show you articles with those exact keywords, but it will also offer other results that will answer your query even if you didn't type in the derivative words such as "AI in pharma" "AI in medicine" "AI in drug discovery" and more. In simple terms, Google doesn't want you to miss out on relevant content simply because you didn't type a specific correlated keyword into its search engine.
Google uses big data because it needs to algorithmically understand all the possible permutations of specific search strings and how they relate to your search. The goal, just with Artificial Intelligence is simple: constantly refine what you're showing users based on their preferences, location, past search history and what other users with similar attributes are searching.
Even today, almost 90% of Google's revenue comes from advertising fees. Ads are big business for the giant company - the biggest of all.
We intentionally made Google's vision for ads the third item to cover in this article. Why? Because Google itself has gone on record saying that the future of Google Ads is connected to both Artificial Intelligence and Big Data, which we covered above.
Last year, when the company turned 20, Adweek interviewed Philipp Schindler, the officer and SVP of global ad sales and operations at Google. When talking about the future of advertising at Google, Schindler had this to say:
'The next revolution is that we will provide, as part of our cloud offering, something I'd call 'machine learning as a service - Machine learning is fundamentally disrupting things we thought were established [advertising practices].'
In simple terms, Google is banking on using its ever-growing Artificial Intelligence and Big Data capabilities to help show ever more relevant ads to customers surfing the internet. Google's new approach to advertisements has even given birth to a completely new discipline called data-driven marketing. Data driven marketing, in many ways, is very similar to big data, but it's applied to brand affinities, interactions and engagements.
According to ComboApp, data driven marketing is: 'the methodology of extracting actionable insights tied to consumer behavior from large data sets in order to predict consumer behavior in relation to new products, marketing positioning and users' likelihood of interacting with a brand.'
What it comes down to, in Google's eyes, is the intent to offer hyper-personalized ad-driven recommendations to customers.
It makes sense. Since much of Google's revenue is tied to a Pay-Per-Click business model, it is in Google's interest is to always convince users to click on their ads.
In fact, Google AdWords is another famous example of big data analytics applied to advertisements. The complex AdWords engine is constantly evaluating how users are interacting with content, what they are clicking on, what they like and dislike, and where they go next. It uses all this feedback to provide better and more targeted results.
Which brings us to the most fundamental shift in advertising philosophy from Google. This vision is in line with all the major initiatives in which the company is investing. Personalized user analytics and actions in the digital space should define what ads are shown and when during the user experience.
As many have argued, for the longest time, advertisers using Google Ads have profoundly distrusted the user data Google has shared with them.
In simple terms, we can look at everything Google does - through AI, big data, their advertisement platforms and more - as a way for them to provide better data to advertisers. Better data means more segmentation, more personalization, more details shared with advertisers. It also means more transparency around A/B testing results, ad creatives, user feedback and more.
In sum, we expect to see far more transparency in the Google advertising space as the company collects and shares more relevant data which, in turn, will help advertisers create more compelling campaigns over time.
Google is in the business of becoming your shrink. He listens, he learns, he 'talks' and he rarely contradicts you. In an ideal world, Google will want to be there with you, as a user, at every step, always learning and always helping you along the way.
Until a few years ago, that vision could not be achieved because our lives, as users, do not entirely happen online.
With the emergence of the Internet of Things - the ability to turn inert objects into digitally connected platforms - Google has caught a huge break. IoT, of course, refers to any device that we can connect to the internet to make our lives better, even if they do not lead to a 'traditional' online experience.
This trend has been on the rise in recent years with the increase in popularity of the interconnected home model. Nowadays, many of us have smart thermostats, garbage cans, lights, locks, home security systems and cars.
Many of these devices run on Google platforms. For example, every Tesla car comes preloaded with Google Maps. Google has already purchased Nest - one of the most popular companies manufacturing smart thermostats, gas detectors and home security camera in the world.
So where does this leave Google?
Google can now learn - and act on - our everyday lives. All interconnected devices that feed data into Google are now in a position to share information with Google which allows the company to learn more about us than ever before.
To be clear - this is not a conspiracy theory. It is not to say Google has a nefarious desire to collect our information and infringe on our privacy.
Rather, it is to say that the rise of the interconnected world is putting Google in an excellent position to know far more about us as individuals which can be mapped onto user personas and then converted into actionable insights that will redefine every single aspect of Google's core business - the search results we see, the places we go, the ads we are shown, the products we buy.
IoT allows Google to become our best friend - without realizing it. Over time, it allows Google to know more about us than any of our friends; or, even more than we know about ourselves.
There have been many Google initiatives in recent years we didn't talk about in this article. Not because we don't believe them to be newsworthy - but we think they are all part of the same overall vision we've already highlighted in this article and covering them in detail would have been a distraction.
Google has also made substantial investments in finance, healthcare, gaming, travel technology, loyalty programs, restaurant reviews, social networking and more.
What all these investments have one factor in common.
Google wants to be our best friend.
The only thing we need to figure out is: who is "we".
Google wants to be the best friend of any consumer. Of every business. Of every advertiser.
Google's mission is to become ever more relevant, over time, to every single type of buyer out there.
All the examples we have covered in this article point to the same end goal.
The world according to Google, to go back to Sundar Pichai, is to organize our lives. It is to help us go places, find the information we seek, engage with our family and friends, co-workers and companies, products and places.
It's purpose is also to help companies better engage with their clients and employees. Through G Suite for business, Google is redefining how we work. Through our browsing history and the information it provides to us, Google is creating a new reality.
More often than not, we see what Google wants us to see.
Google's mission, in many ways, is very noble.
Google wants to learn from us and to use that knowledge to keep us connected. In fact, Google's mission is also to help consumers learn more about themselves than ever before. To do that, it needs to keep learning, to remain relevant in our lives and to become our ultimate assistant.
In 2013, an obscure movie captured the world's imagination. It was called Her and it involved a man called Theodore Twombly who developed a relationship with Samantha, an artificially intelligent virtual assistant.
Google is Samantha - but is more powerful, more intuitive, more personal and more relevant than Samantha could ever have become (at least based on our understanding of AI in 2013).
Samantha was primarily tied to the home. Google's ambition is to be everywhere (and it is). Samantha had to hide that she was talking to other men all over the world. Google doesn't.
Samantha's goal was purely noble - to offer companionship. Google is bound to be a dual agent serving both advertisers and consumers. Only time will tell where Google's ultimate allegiance will fall and how we, as a society, will interact with the company.
One thing is certain. The world in which we live is slowly being redefined by what Google does and the convenience it provides to us. Like it or not, consumers or companies, we all share one thing in common: we have to play by Google's rules because we live in Google's world and not the other way around.