The latest iteration of Google’s search results page, featuring AI-generated content directly integrated into the results was introduced in May 2023.
Three months on, we’ve decided to dig a little deeper into Google SGE – the pros, the cons, and the future of search as we know it…
Powering this innovation is Google’s large next-generation language model, PaLM 2.
What is PaLM 2?
PaLM 2 aims to bring AI intuition to some of Google’s most popular apps, such as Gmail, Google Docs and Bard – it can understand over 100 languages, pass advanced language proficiency exams at a “mastery” level, and is able to understand nuanced text like poems, idioms and riddles.
Google states that PaLM 2:
Excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than our previous state-of-the-art LLMs, including PaLM. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements.
…Back to SGE…
The AI-generated answers are cross-referenced with conventional search results in order to ensure the most accurate information possible.
With the implementation of this update, Google aims to enhance the search experience significantly. They achieve this by harnessing the potential of natural language understanding, improved context awareness, multimodal search capabilities, and various advanced features, including the newly introduced conversational mode. The ultimate goal is to provide users with more relevant and comprehensive information when they conduct searches on the platform:
- Informational searches trigger snapshots similar to featured snippets.
- Local searches results in generative AI producing a response formatted similarly to a local pack.
- Ecommerce keywords prompt Google to showcase various products, resembling product carousels.
Pros and cons of Google SGE
It’s important to weigh up the advantages and disadvantages of something new. While it’s tempting to dive straight into generative AI, it might not be all it’s cracked up to be…
|Follow-Ups – the opportunity to ask Google SGE follow-up questions is a strong feature. However, with its intuition there are “ready-made” follow-up ideas that simulate the knowledge rabbit hole you might potentially be going down… anyone been there?
|Cluttered – the answers are often augmented with a bunch of extra (and sometimes irrelevant) information. Say, for example, you search a quite simple “where can I buy…?” the result can be a mess, littered with giant sponsored cards above the result, a confusing list of suggested stores that won’t actually take you to listings for the item, a Google Map pinpointing to the suggested stores, and off to the right, three linking cards where you could find you way to buying the item…phew!
|The power of three – Google SGE features an answer to the user’s query and a carousel of websites that SGE used to corroborate the response, with three websites visible by default.
|Slow – Users of ‘traditional’ Google search expect to see results almost immediately… Maybe we’re spoiled but waiting more than 5 seconds for an answer to my query is just too much – especially considering I can find the answer immediately if I just looked. What’s worse is that if you do end up getting an error message, it doesn’t pop-up straight away, thus wasting five seconds of your life. It doesn’t seem like much, but taking into consideration that on average we tend to avoid websites with such a long load-time – will we avoid Google search in the future?
|Content and context – it aims to provide users with more conversational and contextually relevant answers instead of a traditional list of links.
|Sources? Where? – on desktop Google displays source information as cards on the right, but you can’t easily tell which pieces of information come from which sources…unless you click on another button.
|Streamlined shopping experience – SGE aims to facilitate shopping decisions. When searching for a product, users receive a snapshot highlighting essential factors to consider and presenting relevant products. This will include comprehensive product descriptions with reviews, ratings, prices, and images.
|An AI-powered overview is not available for this search – certain – often used – keywords and top search queries will return a frustrating error message. Then some similar keywords/ queries will come up just fine with a result. I think what’s more annoying is how affable the AI seems to be, is that even possible?
SEO considerations for Google SGE
As experts in Organic Search (SEO), our highest concern is the number of SERPs that will be affected by Google SGE and how it will reflect on website traffic.
There are a few considerations to take into account:
- The selection of websites for the information snippet isn’t solely based on high rankings
- Google Ads and SERP
The unique angle of your content needs to match what the AI snapshot puts emphasis on, no matter what your usual ranking. While the inner workings of SGE’s algorithms may not be fully transparent, adapting your content to align with proven patterns and strategies can enhance its visibility and engagement. This proactive approach increases the probability of your content being chosen for display on the carousel, leading to improved visibility and potential traffic increase.
Features such as featured snippets or people also ask remain present in Google SGE but are separate from the AI-produced snippet. In the future, ads are going to be included in the snippets but redundant SERP features will be removed.
Despite the significance of links within SEO, SGE does not provide direct links back to the websites, products, or services mentioned in its AI-generated responses. The absence of these links means that users cannot access the mentioned sources directly from the search results page.
Future of search
The rapid evolution of AI evokes feelings of concern, curiosity, and uncertainty; especially for those in digital industries. Essentially, SGE has shaken up the search process (for those lucky enough to get the beta in the US) – conversational search, powered by advanced AI language models like SGE, aims to provide concise and informative answers directly within the search results. If users find these answers comprehensive enough, they may not feel the need to continue searching, which could lead to reduced traffic and engagement for businesses and websites relying on organic search or paid advertising.
For marketers and advertisers, this shift in user behaviour may pose challenges in terms of driving traffic to their websites or promoting their products and services effectively. Strategies might need to adapt to align with the changing landscape of search behaviour and cater to users who prefer succinct answers without navigating further.
As conversational search evolves and becomes more prevalent, businesses and marketers will need to closely monitor its impact on user behaviour and adjust their SEO and advertising approaches accordingly. Understanding the changing dynamics of search and user preferences will be crucial to maintaining visibility and relevance in the evolving digital landscape.