How To Use Google’s ‘AI For Marketing’ Framework For High-Impact ROI

Overwhelmed by the hype around AI for marketing? 

To help marketers get their heads around new AI developments, Google has come up with a range of AI solutions to fit your needs. Their AI-powered campaign products provide quick wins and Google Cloud enables more ambitious AI transformations, such as custom creative studios or predictive audience modelling.

A strong first-party data strategy can create successful AI-driven marketing. 

To help you navigate this landscape, here’s all you need to know about Google’s ‘AI for Marketing Engine’ framework.

The AI for Marketing Engine

Traditionally, marketing followed a linear, iterative process: create content, distribute, measure impact, refine, repeat. Even though it was effective, the approach often relied on assumptions and limited data.

Google’s ‘AI for Marketing Engine’ framework reimagines this process by focusing on three core functions: creative, media, and measurement. 

Here are the three core areas to focus on:

1. Measurement and insights
2. Media and personalisation
3. Creativity and content

These areas, though interconnected, provide a clear structure to understand AI’s transformative potential. 

Let’s delve deeper into each.

Measurement and Insights

You might wonder why we’re starting with measurement and insights. After all, they’re typically seen as the final step. However, in AI-driven marketing, it’s where we begin.

A robust data and measurement foundation is essential to access AI’s full potential. First-party data is the first step to unlock the benefits of AI. It helps uncover hidden patterns, identify high-value audiences, and predict customer lifetime value.

Your organisation likely possesses a wealth of marketing data: surveys, customer reviews, transactions, and loyalty program information. Consolidate these assets and identify data gaps. Shift the focus from analysis to predictive action. 

Marketers can move beyond rearview mirror metrics and enable proactive decision-making. By transforming data into foresight, AI focuses on future trends to predict what should be the way forward for a brand.

However, data’s true value lies in its application. AI revolutionises measurement, and transitions from retrospective analysis to predictive action. Predictive metrics like lifetime value will help you identify high-potential customers, optimise resource allocation, and drive significant growth.

Questions to ask your team:

1. How do you collect first-party data, where do you store it and how do you make it available for marketing purposes?
   
   
2. How do you combine first-party data with AI to gather new insights?

Media and Personalisation

The age-old marketing dream to deliver the “right ad, right person, right place, right time” is now a reality, thanks to AI’s ability to optimise in real-time.

For years, predictive AI has powered our platforms, matching ads to intent with astonishing precision. However, achieving this perfection across all channels was tough.

Now, generative AI is revolutionising the game. Gemini models, with products like Demand Gen and Performance Max, enable hyper-personalised ad experiences at scale. They not only match ads to people; but drive sales, revenue, and profitability.

Generative AI will soon unlock a new era of hyper-personalised ad experiences. Ready to accelerate your AI journey? Start with a test, learn, and scale approach. 

Begin by pitting AI-powered campaigns against traditional methods. Once you’ve identified a winning formula, expand its reach. Use the combination of your data and AI to create highly targeted customer segments based on their potential value. 

Continuous optimisation is key to maximise your ROI.

Questions to ask your team:

1. How does your process for testing and scaling AI-powered campaigns differ from manual ones?

2. What could we save from increased productivity if we get AI-powered campaigns to outperform our manually managed campaigns?
   
   

Creative and Content

Modern campaigns demand an overwhelming volume of assets to reach diverse audiences across multiple platforms. Manual creation can’t keep pace with this complexity while maintaining quality standards.

AI offers a powerful solution. 

By automating tasks like formatting, resizing, and captioning, it frees up creative teams to focus on higher-level concepts. AI can also analyse existing assets to generate fresh, relevant ad variations. Overall, it accelerates the creative process and drives better results.

AI empowers you to optimise, scale, and innovate. 

By analysing performance data across copy, images, and video, AI uncovers the winning formula for your creative. This data-driven approach enables you to adapt your campaigns in real-time based on audience, trends, and performance.

Questions to ask your creative teams and agencies:

1. How are you using generative AI to spark ideas and move faster?
   
   
2. How do you ensure that people are using generative AI tools in ways that protect your data and IP?
   
   
3. How are you using AI to increase asset variety?
   
   
4. What productivity increases are we seeing, and how can we redeploy the budget toward better creative or more media spend?

Unlocking AI’s Potential Using Your Magic Circle

Successful AI implementation depends on robust cross-functional collaboration. Cultivate strategic partnerships with your ‘magic circle’.

Ask yourself: Which relationships will be critical to my network?

• Finance
• Agency partnerships
• New roles / responsibilities
• HR: Job skilling
• Engineering
• Legal

This alliance can transform marketing pilots into enterprise-wide AI initiatives.

Questions to consider:

1. Who is in your Magic Circle already? Identify these stakeholders before you need them, while you are building out your first solutions.
   
   
2. Who else might you need to bring in? Identify the relationships you need to build. Taking action can be as simple as setting up a coffee next month.
   
   
3. Work with your peers to complete the business cases for your desired initiatives.
   
   
4. What needs to happen, and why is it important from an overall business perspective?

Results: Measure your progress with AI

Make sure that you have a strong business case to invest in AI across your organisation. 

Depending on the project, you may choose to measure the success of your AI initiatives based on revenue growth or cost savings. Revenue growth can come from projects where you get more time for creativity or when you are able to respond to customer requests faster than before. 

Cost savings can come from reducing time spent on AI-eligible tasks, such as resizing or formatting creative, translating, or personalising content for thousands of people. 

Set goals and track progress for the right metric for your project.

Prioritise Responsible AI Adoption

The AI landscape is vast and complex. To ensure ethical and effective AI implementation, prioritise partnerships with reputable providers committed to data privacy and intellectual property protection. 

Equip your team with trusted AI tools to prevent suboptimal decisions and mitigate risks.

Need a fresh perspective? Let’s talk.

At 360 OM, we specialise in helping businesses take their marketing efforts to the next level. Our team stays on top of industry trends, uses data-informed decisions to maximise your ROI, and provides full transparency through comprehensive reports.