Gemini and Google Machine Learning: How It Is Changing the Digital Marketing Industry?

AI and Machine Learning

Google Machine Learning is constantly evolving and improving to meet the needs and expectations of both advertisers and users. It has automated many tedious and manual processes that inhibit growth, such as bidding, targeting, and creative optimisation. It has also enabled Google Ads to provide insightful forecasts, make accurate decisions, and create predictive scenarios based on historical data and changing environments and markets.

One of the key factors that has helped Google maintain its competitive edge and attract more businesses to advertise on its site is the use of AI and machine learning to automatically allocate optimal spend to a business’ top brands, products, and services. Machine learning learns over time which campaigns show the best performance and allocates more budget to maximize total revenue.

How We Know It Works

When an Australian hardware retailer wanted to determine if Google was allocating enough spend to its top performing brands, they were glad to find Google had automatically allocated majority of their budget accordingly to support their top 10 brands. Google had learnt to recognise the best performing brands by performance and allocated spend accordingly. This in turn generated the majority of total revenue in the retailer’s Google Ads account. This trend goes across various industries. For example, Google Ads allocated majority of spend to the top 10 performing brands for an electronics retailer that produced the most revenue.

How Gemini and Recent Advancements Affect Campaign Performance 

Google is exploring new ways to harness the power of generative AI to create more natural and intuitive Search experiences. Generative AI is a type of AI that can generate new content or data that did not exist before, such as images, text, or speech. By bringing together the unique capabilities of generative AI with Google’s deep understanding of information, Google will unlock entirely new types of questions that Search can answer. 

One of the ways Google is applying generative AI to its ads solutions is through Gemini, its largest and most capable AI model. This model represents a substantial improvement over Google’s previous AI models

Gemini is now powering the conversational experience in Google Ads, a chat-based workflow that helps advertisers build better Search campaigns. All advertisers need to start is their website URL and Google AI will help them create optimised Search campaigns by generating relevant ad content, including creatives, keywords, and images. 

Gemini will also adapt the ad content based on the context of the query, ensuring that the ads are always relevant and engaging. This is especially relevant to small businesses. Small business advertisers that use the conversational experience in Google Ads are 42% more likely to publish Search campaigns with higher Ad Strength which in turn leads to more conversions. 

Generative AI is also set to boost one of the standouts of Google Ads campaigns - Performance Max (PMax). PMax is a campaign type in Google Ads that leverages the power of generative AI to drive more conversions across all of Google’s advertising channels and inventory. PMax requires only a few inputs from the advertisers, such as their website URL, conversion goals, creative assets, and audience signals. It then optimises the performance in real-time and across channels, delivering more relevant and personalised ads to potential customers. 

PMax has several benefits for advertisers, such as reach, results, and insights. According to Google’s 2023 data, PMax campaigns can boost conversions or conversion value by more than 15% on average, compared to Dynamic Search Ads campaigns, while maintaining a similar cost per action or return on ad spend. Although AI generated assets within PMax have been met by scepticism by advertisers, Gemini’s much improved capabilities are set to challenge some of that scepticism and unlock new levels of efficiency. 

Our team proactively monitors Google AI advancements, enabling our clients to seize emerging opportunities. We use in-depth data analysis to evaluate the performance of Google's AI solutions, gaining valuable insights into their effectiveness. This knowledge empowers us to select the optimal solutions tailored to our clients' needs

Foundations for AI

To unlock this efficiency organisations, need to create the right infrastructural foundations for AI. Pmax and generative AI works best when paired with customer data. Google Tag, Enhanced conversions, Google Analytics and Customer Match are the enabling tools in this context. See Figure 1.