As the leaders of Google APAC’s Ads and Cloud marketing teams — and as marketers ourselves — we talk to many partners and friends about AI in marketing. One of the things we hear most clearly is that people want to move beyond the hype to the how.
So, to help marketers get their heads around the opportunities and how to make the most of what AI enables, we’ve developed a framework for how to put AI to work in your marketing.
This article lays out essential actions you can take to get started and how to scale when you’re ready.
Investing in your first-party data strategy can give you a solid AI foundation and drive quick wins, growth, and efficiency for your business. Google’s AI-powered campaign products and off-the-shelf products and tools can help you achieve these benefits.
For those who want to do more, Google Cloud offers a powerful platform for broader AI transformation. Tap its offerings, which can include purpose-built solutions like scaled creative production or AI-powered predictive audiences and analytics, to give you a competitive edge.
Whether you’re just getting started or looking to maximise what AI can do, our AI framework is a great resource to help you think about how to take advantage of using AI in your marketing, and to assess what you’re already doing vis-à-vis what’s possible.
The AI for Marketing Engine
Until recently, marketing practices followed a fairly linear path. We’d create content intended for a specific audience; publish it on the channels or platforms where our audiences were; measure its effect on marketing metrics (often only rough proxies for business growth); tweak it; then repeat the process.
Enter AI and a framework we call the “AI for Marketing Engine.” It’s premised on familiar marketing functions: creative, media, and measurement. These aren’t independent activities, of course. They’re increasingly interlinked, but they’re a useful way to categorise the opportunities AI offers.
Let’s take a closer look at each.
Measurement and insights
You might ask, “Why start with measurement and insights? Don’t they usually come last?”
We start here because successfully adapting AI in marketing first requires setting a solid foundation for your data and measurement. First-party data is the fuel that AI uses to uncover unique insights and trends, identify valuable audiences, and help you better measure customer lifetime value.
AI can transform measurement’s role in your marketing, helping you go from analysing historical trends to acting on predictive insights.
Your organisation is likely already rich with this kind of marketing data: surveys, customer reviews, transaction, and loyalty-program data. It will be crucial to combine this information and to identify any gaps.
But even the best data sets are only as valuable as the actions you take on them. AI can transform measurement’s role in your marketing, helping you go from analysing historical trends to acting on predictive insights and enabling outcome-based marketing.
The top measurement pain points that marketers think AI tools today can help them solve ranges from managing and analysing large data sets (27%), to measuring true return on ad spend (26%), and capturing more and more accurate conversions (24%).1
When it comes to analysing customer journeys and converting high-value users, solutions like Ads Data Hub can be highly beneficial for planning and optimisation. They can help you to identify new customers and to predict repeat shoppers or those likely to refer friends, so you can focus on these people to increase brand and sales lift.
Tanishq is a powerful example of a company that has put AI to work in this way. With 90% of its sales happening offline, the Indian jewellery brand needed a way to measure the impact of its YouTube campaigns on store sales during Diwali. Using Ads Data Hub, Tanishq and its agency partner Hiveminds blended the brand’s first-party store sales data with YouTube’s campaign data to distinguish between first-time and repeat buyers. By successfully quantifying the impact of its YouTube spends on offline store sales for these groups, Tanishq was able to apply these insights to make better marketing campaign decisions and ultimately optimise ad spend.
Questions to ask your team
Media and personalisation
The longtime dream for marketers has been the “right ad, right person, right place, right time.” Today that dream is closer to reality than ever before, because AI is the ultimate real-time optimisation engine.
For years, predictive AI has helped us understand the intent behind millions of queries every second, evaluate tens of millions of potential ads, and then choose the best one. It’s what powers the bidding and audience solutions that match people to ads.
But showing the perfect ad on every surface has been a real challenge. Now, generative AI is poised to unlock enormous new opportunities and a whole new era of ad experiences. Marketers look to AI to help solve their top media buying pain points, such as optimising bid strategy (33%); reaching new/right audiences (33%); targeting customers at different phases in the purchase journey (32%), and managing campaigns across multiple channels/platforms (31%).2
Generative AI is poised to unlock enormous new opportunities and a new era of ad experiences.
Our latest Gemini models are supporting an entire ecosystem of products, platforms, and APIs, including tools such as Demand Gen and Performance Max. These AI-powered campaigns enable you to optimise for business results like sales, revenue, or profitability.
A good first step toward putting AI to work here is to implement a test, learn, and scale approach. Start by testing your AI-powered campaigns against your manual ones. Scale quickly once you see impact. Once you scale, use your data, combined with AI, to segment your customers based on propensity models and your specific needs. No matter where you are in this process, make sure to continuously optimise against your business objectives.
International fitness brand Les Mills is a case study in this approach. When people couldn’t go to gyms during the pandemic, it doubled down on offering the best fitness video content in the world. The company used Demand Gen to create a compelling visual storytelling experience to find and convert new subscribers. Over a four-week test, it drove 561% more sign-ups at a 72% more efficient cost per trial. Now Les Mills uses Demand Gen campaigns across all of its markets.
The airline Virgin Australia has also benefitted from AI-powered campaigns. It wanted to connect with travellers and provide them with information customised to whatever they were searching for.
Virgin Australia used broad match and responsive search ads to capture all related search queries, and serve ads with messages that resonated. It also used value-based bidding to connect with its most valuable customers and optimise its ads and bidding strategy in real time to get better returns. The results were impressive: Virgin Australia saw an 88% uplift in bookings, and 150% increase in revenue with a 17% improvement in return on ad spend.
Questions to ask your team
Creative and content
Today’s marketing is increasingly complex. Media campaigns often require thousands of assets running simultaneously across devices, platforms, and audiences. It’s simply not possible for teams to keep up with the volume, velocity, and variations of assets necessary to drive meaningful performance — while meeting a high bar of quality.
To speed up the development and relevance of your creative, you can use AI to format, trim, and resize your existing assets for different channels. It can add captions, dub your videos, and even learn from your creative library to generate entirely new ads.
AI solutions also make it possible for you to test, refine, and optimise all of your assets at scale. AI can analyse copy, images, and video alongside performance data to help you understand what makes your top-performing creative work.
And when it comes to elevating customer satisfaction, AI can offer brand-unique experiences tailored to every customer. It allows you to shift your marketing and visuals based on time, culture, and opportunities. This makes new creative workflows – both in-house and with agencies – possible, while unlocking new ways to develop creative campaigns and experiences.
That’s how KDDI unleashed its creativity and wowed customers. The Japanese communications company introduced Gemini into its metaverse and shopping services to engage its customers with immersive experiences such as interactive AI assistants, mascots, and personalised product recommendations – all powered by generative AI. What’s more, these experiences were fed with high-quality content created by AI rapidly, at scale, and at a lower cost than ever before.
The payoffs in adopting AI for marketing creativity are significant. Of the marketers who are already using AI in the creative process, 86% say it has enhanced employee/team efficiency, 76% report it boosted marketing performance, and 59% credit it with improving business revenue.3
Questions to ask your creative teams and agencies
Implement AI across your business
As you invest in AI, there are three key areas to consider to ensure successful adoption across your organisation: relationships, results, and responsibility.
Relationships: Identify your Magic Circle
It’s critical to create and develop relationships and advocacy across your organisation, such as with your finance, engineering, legal, HR, and product teams. We think of this as the “Magic Circle'' we need around us to deliver on the promise of AI for marketing. It takes a great deal of cross-functional support to move from marketing pilots to full-scale integrated programs.
There’s no one-size-fits-all organisational design, but here are some key questions to consider:
- Who is in your Magic Circle already? Identify these stakeholders before you need them, while you are building out your first solutions.
- 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.
- Work with your peers to complete the business cases for your desired initiatives. What needs to happen, and why is it important from an overall business perspective?
Results: Measure your progress with AI
You’ll want to ensure that you have a strong business case for continuing 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, say, crafting more effective creative with AI, or being able to respond to trends or customer requests faster than ever 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. Whichever is the right metric for your project, ensure that you set goals and track progress.
Responsibility: Provide guardrails for AI implementation
Finally, based on our conversations with marketing leaders, it’s clear that the industry is committed to principled AI adoption. It’s important to remember that the market is flooded with AI models and providers that are accessible to anyone in your organisation. Partner with reputable organisations who can explain how they will protect your data and IP. Give your team access to trustworthy AI tools, so they don’t make suboptimal choices that put your organisation or data at risk.
We look forward to continuing the conversation about how marketing leaders can put AI to work. In time, we believe the marketing process will turn into an all-at-once efficiency and growth flywheel — fast creative production, tailored media activation, and real-time measurement, all working together to drive performance. This future sounds pretty awesome, and we’re excited to help build it, together.
