OVERVIEW
Discover the trends and technologies shaping the future of online search, from predictive search algorithms that anticipate user intent to AI-driven recommendations personalising content. In this article, we look at the rise of voice search and digital assistants, which are revolutionising user interaction with search engines, and note the critical role of mobile search and local SEO in providing tailored location-based results.
Part Three in our series on the timeline of online search looks at how evolving themes and technologies are reshaping the way people find information. If you missed the earlier segments, you can catch up on Part One: Early Search Engines Before Google and Part Two: Navigating the Changes in Online Search.
Predictive Search
Imagine typing just a few letters and seeing your desired results pop up instantly. Predictive search, powered by advanced AI and machine learning, is transforming how people search online by anticipating user needs before they finish typing. As the goalpost for the ultimate user experience is constantly moved, the predictive search feature anticipates user intent and suggests queries before users finish typing. Predictive search algorithms dynamically generate personalised suggestions based on accumulated user data. These algorithms track behaviour, search history, the context of the search, and search engines’ internal factors like popular searches, trending topics, and user preferences.
Earlier examples of this technology were Google’s “Google Autocomplete” or “Google Instant,” which were then augmented by Google’s “People Also Ask” and “Related Searches” sections, providing additional context and suggestions. Bing and Yahoo joined the trend and applied predictive search to offer auto-complete suggestions and refine search queries in real-time. Bing’s “Search Suggestions” feature offers predictive search recommendations based on user input and browsing history.
Predictive search helps users obtain more accurate and relevant results much faster. It also offers topics to find additional information that users may not have thought of. The more users engage with predictive search, the more accurate it becomes, therefore improving the quality of search results.
Artificial Intelligence for Search
In August 2024, one of the AI market-leading companies, OpenAI, announced the creation of a brand-new search engine called SearchGPT. In its testing phase at the time of this article going live, this prototype aims to lead the path towards a more natural and intuitive way of searching for information. AI-assisted search will allow users to ask follow-up questions and clarify the search results in the way queries typically flow back and forth during natural conversations.
Thus, the long-run concerns of Google’s parent company Alphabet’s investors got real-life proof that OpenAI could take a market share from Google. The full rollout of a service like SearchGPT would further revolutionise the search landscape through a new way of finding information.
This could be an important move for Google, coming off the back of a recent court ruling in which a US judge ruled that the search juggernaut has violated an antitrust law. The ruling potentially paves the way for a possible split of Google and Alphabet, irrevocably changing the search landscape from its current dominating position.
AI-Driven Recommendations
Ever wondered how Netflix knows what movie or TV shows you’ll love next? That’s the magic of AI-driven recommendations at work, learning from your behaviour to make suggestions for you. In an attempt to ‘think’ in the same way users do, a generative recommendation system is one of the most common ways of finding compatible items. Earlier versions, such as the “Related Articles” sections, primarily relied on manual adjustments, related information structures, and tags. However, modern AI-generated recommendations powered by sophisticated algorithms have enhanced this subclass of machine-learning information filtering systems.
AI-driven recommendation algorithms analyse accumulated user data (past purchases, viewing history, preferences, social interactions, etc.), distinguish behaviour patterns, examine ratings and trends, and apply contextual signals to match content relevance and curate personalised recommendations. These engines aim to enhance the user experience and increase engagement by extending the time spent and the depth of the journey with the aim of driving business conversion rates.
Think about the last time global streaming services suggested a show you binge-watched over a weekend or when Spotify created a playlist that felt custom-made for you. These personalised experiences are powered by sophisticated AI algorithms that learn from your habits and preferences. Amazon recommends products based on past purchases, browse history, and search history. Popular social media platforms like Facebook, Instagram, and TikTok also apply AI-driven recommendations to personalise users’ news feeds and explore tabs.
Voice Search and the Rise of Digital Assistants
Asking Siri for the weather or telling Alexa to play your favourite song make up part of the 3.1 billion voice searches every month. Voice search, which started as a novelty when Google introduced it in 2011, has evolved into a daily habit for over 50% of adults using it daily in 2024. With advances in speech recognition technology, voice search has become an integral part of search behaviour and marketing. Today, the average voice search SERP takes 4.6 seconds to load, and people use the technology to access information conveniently and hands-free, utilising natural language in their daily lives. Voice search is applied to such actions as searching for directions and making dining reservations to shopping and controlling smart home devices.
Voice search technology integrates seamlessly with leading search engines such as Google, Bing, and Yahoo, allowing users to perform voice-activated searches from their web browsers or, for 27% of users, from their mobile devices. With smartphones, smart speakers, and wearables becoming universal, voice search has shifted user behaviour from typing queries to simply speaking them.
Advances in natural language processing and speech recognition algorithms powered by AI and machine learning have made voice searches more accurate and intuitive. AI-driven voice assistants like Siri, Alexa, and Google Assistant now understand user intent and context, providing relevant recommendations in real-time.
As the voice search market expands, it presents numerous opportunities for businesses to connect with users in new and innovative ways, but it also poses challenges in optimisation. LLM voice recognition chatbots achieve an impressive 93.7% accuracy, ensuring businesses and website owners must optimise their online presence to appear in voice search results. Voice searches are more conversational and reflect natural human communication, which has profound implications for SEO and content strategy.
The Impact of Mobile Search and Local SEO
With smartphones becoming non-negotiable for most people, mobile search and personalised local SEO have become essential for connecting with customers on the go. Google has stated it will no longer index sites that aren’t optimised for mobile as of July this year. The transition has prompted search engines to prioritise mobile-friendly websites to deliver optimised search results tailored for mobile users. For relevancy, business owners must consider applying local SEO strategies, like updating their Google My Business listing and using location-specific keywords, to make it easier for customers to find them online and offline.
Imagine a user searching for a nearby coffee shop while walking through an unfamiliar city. Mobile-friendly sites with local SEO strategies will appear at the top of their search results, providing the most relevant and convenient options.
Google’s algorithm updates, such as Pigeon and Possum, have refined local search results to provide more contextually relevant information. This makes it vital for businesses to adopt local SEO strategies to maintain visibility. Partnering with eCommerce SEO specialists like LION Digital can help your business stay ahead of the competition.
Local SEO strategies focus on optimising a business’s online presence to improve visibility in local search results and attract local customers. Features like Google Maps, Google My Business, and Google Local Pack results have made it easier for users to find local businesses and services directly within search engine results pages. Optimising website content with local keywords and claiming and optimising Google My Business listings are essential for improving local search rankings.
Maintaining an active presence on social media and vertical search engine platforms is also necessary for local SEO. Users often turn to these platforms to find local businesses, read reviews, and engage with communities. Social signals, which refer to a webpage’s collective shares, likes and social media visibility, are considered a ranking factor by traditional search engines. Social signals contribute to a page’s organic search rankings and are seen as a form of citation, similar to backlinks. When built and managed effectively, citations signal trust and credibility to search engines and potential customers, shaping local search rankings and influencing consumer purchasing decisions.
The Challenges of Online Search
Advances in online search have led to several hurdles for businesses to overcome:
- Privacy and Data Collection: Awareness and concerns regarding the protection of privacy rights and the ethical use of user data have become prevalent and are vital for eCommerce businesses to address.
- Ethical Impact of Personalisation on User Autonomy: Personalisation in search results and advertising based on user data influences user decisions, raising ethical considerations about user behaviour manipulation, autonomy, and freedom of choice.
- Misinformation: With developments in artificial intelligence, the amount and speed of web content delivery are astronomical, making it more challenging to distinguish false and misleading content. More emphasis should be placed on prioritising authoritative sources and filtering out unreliable ones.
- Filter Bubbles and Echo Chambers: Personalised search algorithms can limit users’ exposure to diverse viewpoints and contribute to the spread of misinformation. This can reinforce existing biases and limit access to various perspectives, contributing to the polarisation of online discourse.
To remain relevant in today’s fast-paced digital world, search providers must address these challenges to avoid issues concerning unauthorised data collection and breaches. Managing your SEO effectively requires a comprehensive approach involving user education, algorithmic transparency and accountability, and regulatory oversight.
Boost Your eCommerce Success with LION Digital’s Search Marketing Expertise
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