There is no denying that Artificial intelligence (AI) is now well past being just a trend. It is no longer a buzzword but has become a phenomenon that is now an integral part of most industries, including digital marketing. It has significantly reshaped most marketing disciplines, and paid search is not immune to this change.
It is time for marketing professionals and businesses to get to grips with the abundant world of AI tools, its fast-evolving capabilities, and features to stay ahead in this competitive industry. AI-powered algorithms have transformed the realms of paid search, and there is more to come.
In this article, we explore how AI is currently reshaping paid search and anticipate future developments that are expected to drastically alter the landscape.
Let’s dive right in…
AI has managed to revolutionise paid search by introducing unprecedented levels of automation and optimisations. With functions like smart bidding, marketers can now manage extensive advertising campaigns more efficiently than ever before.
For example, Google’s case study on FishingBooker, an online platform for booking fishing trips, revealed a 49% increase in return on ad spend (ROAS) and a 57% increase in conversions through smart bidding.
While these tech advancements offer substantial benefits, it is possible that these automatons might render traditional advertising methods obsolete.
Let’s look at how AI has already impacted paid search…
Enhanced automation via smart bidding
AI has revolutionised the automation of bidding strategies in paid search. Features like Google Ads’ smart bidding allow bids to be calculated automatically using machine learning, ensuring ads are shown to the right audience at the right time.
Google offers several bid strategies to choose from:
This reduces the need for manual intervention while enhancing campaign efficiency. Smart bidding therefore makes it possible for marketers to manage hundreds of paid search campaigns with ease at a lower cost and higher CTR.
Better ad relevance and targeting via query-matching
Through Artificial Intelligence, ad relevance has seen a substantial boost. AI-powered algorithms deploy advanced query-matching and targeting to analyse vast amounts of data, including demographics, search history, online user behaviour, and search patterns, to deliver precisely targeted ads. This helps advertisers create highly personalised ad campaigns that resonate with specific audience segments, leading to better engagement, conversion rates, and improved ROI.
Dynamic Search Ads
Based on the product information, the content of the website and the user’s search query—AI can dynamically generate ad copy and headline variations. This creates multiple versions of dynamic ads which allows Google to optimise them in real-time, saving hours’ worth of manual labour.
AI-generated responsive ads
AI can generate responsive ads based on combinations of provided headlines and descriptions. AI tests different combinations of headlines and descriptions to find the most effective ones, allowing advertisers to upload multiple ad versions while Google optimises them in real time. This automation also saves hours of manual labour to keep ads relevant and increases conversions and ROI.
AI ad content generation
While there are several AI content generation tools available to help create marketing assets through templates, Google Ads now offers an integrated tool—the Gemini Model—which helps create optimised search campaigns through a conversational experience. It generates relevant ad assets for responsive search ads, including creatives and keywords, based on the advertiser’s website and inputs.
This means AI can not only optimise the combinations of ad assets that the advertiser has provided, but it can also create new versions. Early adopters claim to have seen increased conversions when using this technique.
Predictive analytics
Google’s AI-driven predictive analytics tools can now forecast the click-through rate (CTR) of an advert for a specific keyword, providing predictions in three statuses: above average, average, or below average. If an advert receives a below-average status, the tool suggests that the ad copy may need to be better aligned with the target keyword, or that the keyword’s relevance might need re-evaluation.
Google can now actually predict the impact on the Quality Score, a metric that indicates how your advert’s quality compares to that of the competitors. Ad quality is essentially a measure of user experience with the ad. Key factors influencing the quality score include the expected CTR, ad relevance, and the landing page experience, which assesses the relevance and usefulness of the landing page content.
AI-generated SERPs, user behaviour, and the changing discourse of paid search
As AI-generated content increasingly dominates search engine results pages (SERPs), user behaviour is also expected to evolve. With detailed, highly relevant, and more personalised information readily available in search results, users are likely to interact with search engines more conversationally, akin to engaging with ChatGPT and chatbots. This shift will significantly change how marketers approach keyword targeting and content creation.
Traditional strategies focused on targeting specific keywords are becoming increasingly less effective. Instead, marketers will now need to consider how users phrase their queries more conversationally. This transformation will challenge marketers to refine their strategies, ensuring their content aligns with the nuances of user queries.
As AI continues to shape search interactions into a chatbot-like dialogue, creating content that comprehensively answers users’ questions becomes crucial. Marketers will need to rethink their approaches, moving away from keyword-centric tactics to developing content that addresses the full scope of user inquiries.
The rise of AI chatbots
AI chatbots have already revolutionised NLP (Natural Language Processing) and fundamentally changed how people interact with search engines. These intelligent bots gather information from diverse sources to provide comprehensive and precise answers to search queries, moving beyond the brief snippets typical of traditional search results. As a result, users now receive more in-depth and engaging responses from AI, making the search experience richer and more interactive.
The era of quickly scanning short summaries on SERPs is being replaced by AI chatbots that engage in meaningful conversations with users. This shift creates a more conversational and interactive search experience, which users are increasingly embracing. Consequently, marketers need to evolve their strategies to keep up with these advancements, ensuring their content meets the demands of this new conversational search environment.
Voice search optimisation
As voice search becomes more prevalent, AI will also play a crucial role in optimising ads for voice queries. This will involve understanding natural language patterns and providing relevant responses that match the conversational tone of voice searches.
Advanced fraud detection
AI will enhance the detection and prevention of ad fraud. By continuously analysing patterns and behaviours, it can identify fraudulent activities such as click fraud or impression fraud, ensuring that advertising budgets are spent more efficiently and effectively.
In the near future, AI will likely integrate with AR to create immersive ad experiences. This could involve interactive ads that users can engage with in a more meaningful way, blending digital and physical worlds to capture attention and drive engagement.
AI’s influence on search is profound and continually evolving. As technology advances, it will bring even more innovative solutions to enhance ad targeting, creation, and optimisation, making paid search more effective and efficient than ever before.
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