The Potential of Artificial Intelligence in Marketing

In recent years, artificial intelligence (AI) has gained enormous attention in the marketing world. Many professionals have heard about it but often struggle to understand how to turn the hype (massive buzz for a media campaign) into tangible results for their businesses. This article outlines the essential actions you can take to get started and how to scale when you’re ready. Whether you are just starting out or want to maximize the potential of AI, this framework is a valuable resource for understanding how to leverage artificial intelligence in your marketing and to evaluate what you’re already doing compared to what’s possible.

The AI engine for marketing

Until recently, marketing practices followed a fairly linear path. Content was created for a specific audience, it was published on the channels or platforms where your users were, the effects on marketing metrics were measured (often only approximate in relation to business growth), actions were improved, and then the process was repeated.

The arrival of artificial intelligence has brought about a radical change, giving rise to what we call the “AI engine for marketing.” This framework is based on three fundamental marketing functions: creativity, media e measurement. While these activities are not independent, but increasingly interconnected, they offer a useful way to categorize the opportunities provided by AI.

Measurement and insights

AI can transform the role of measurement in your marketing, helping you shift from analyzing historical trends to taking action based on predictive insights and enabling you to implement outcome-driven marketing. Your organization likely already has this type of marketing data: surveys, customer reviews, transactional data, and loyalty program data. It will be essential to combine this information and identify any gaps.

But even the best data sets are only valuable if you act on them. AI can transform the role of measurement in your marketing, helping you shift from analyzing historical trends to taking action based on predictive insights. Metrics such as predictive lifetime value are incredibly advantageous for planning and testing. They can help you predict customers who will make repeat purchases or those most likely to recommend your brand, allowing you to focus on these customers to increase brand lift and sales.

A powerful example of a company putting AI to work in this way is PepsiCo. Many of its brands don’t typically have direct relationships with consumers, so they’ve used innovative ways to build first-party relationships. Applying QR codes to packaging and in stores to connect customers to their loyalty programs has helped deepen audience insights and transform customer relationships from purely transactional to something more enduring and profitable.

Media and personalization

The longstanding dream for marketers has been “right ad, right person, right place, right time.” Today this dream is closer to reality than ever, as AI is the ultimate driver of real-time optimization. For years, predictive AI has helped us understand intent behind millions of queries per second, evaluate tens of millions of potential ads, and select the best one. It powers the bidding and targeting solutions that match people to ads.

But showing the perfect ad on every surface has been a real challenge. Now, generative AI is ready to unlock huge new opportunities and a new era of advertising experiences. Our latest Gemini models are powering an entire ecosystem of products, platforms, and APIs, including tools like Demand Gen and Performance Max. These AI-powered campaigns let you optimize for business outcomes like sales, revenue, or profitability.

A good first step to putting AI to work in this area is to implement a test, learn, and scale approach. Start by testing your AI-powered campaigns against manual ones. Scale quickly once you see the impact. After scaling, use your data, combined with AI, to segment your customers according to propensity models and your specific needs. Wherever you are in this process, be sure to continuously optimize toward your business goals.

The international fitness company Les Mills is a case study in this approach. When people couldn’t go to the gym during the pandemic, the company doubled its efforts to deliver the world’s best fitness video content. They used Demand Gen to create a compelling visual storytelling experience to find and convert new subscribers. In a four-week test, it generated 561% more sign-ups with a 72% more efficient cost per trial. Now Les Mills uses Demand Gen campaigns in all its markets.

The footwear and apparel company Vans has also benefited from AI-powered campaigns. Like many clothing brands, it faced the challenge of managing fluctuating demand and the unpredictability of the holiday season. While manually navigating this challenge is daunting, it’s exactly where AI excels.

Vans used Performance Max to create personalized journeys for its diverse audience. This meant delivering the right message, at the right time, to the right person—whether they were skateboard enthusiasts or parents preparing for back-to-school. The results were impressive: Vans achieved a 46% increase in conversions and an 86% increase in sales compared to its previous shopping solutions.

Creativity and content

Today’s campaigns are increasingly complex. They often require thousands of assets running simultaneously across different devices, platforms, and audiences. It’s simply impossible for teams to keep up with the volume, speed, and asset variations needed to drive meaningful performance, while maintaining a high standard of quality. To accelerate your creative development and relevance, you can use AI to format, crop, and resize your existing assets for different channels. It can add subtitles, dub your videos, and even learn from your creative library to generate entirely new ads.

AI solutions also make it possible to test, refine, and optimize all your assets at scale. AI can analyze text, images, and video alongside performance data to help you understand what works best in your flagship creative. It lets you adapt your marketing and visuals based on timing, culture, and opportunity. This paves the way for new creative workflows and unlocks new ways to develop creative content in-house and with agencies.

To improve campaign quality and reduce time-to-market, French retailer and wholesaler Carrefour and its marketing team built an AI creative studio with Google Cloud, training it on the brand’s guidelines and the company’s most successful campaigns. Now, AI learns from Carrefour’s historical campaign data and, when it receives guidelines for an upcoming program, can create a first draft of complete marketing campaigns in minutes.

Implementing AI across the company

As you invest in AI, there are three key areas to consider to ensure successful adoption throughout the organization: relationships, results, and responsibility.

Relationships: identify your Magic Circle

It’s essential to build and foster relationships and advocacy throughout your organization, including with your finance, engineering, legal, HR, and product teams. We think of this as the “Magic Circle” we need to fulfill AI’s promise for marketing. It takes great cross-functional support to move from marketing experiments to large-scale integrated programs.

There is no one-size-fits-all organizational design, but here are some key questions to consider:

• Who is already in your Magic Circle? Identify these stakeholders before you need them, as you build your first solutions.
• Who else might you need to involve? Identify the relationships you need to build. Taking action can be as simple as scheduling a coffee next month.
• Collaborate with your colleagues to complete the business cases for your desired initiatives. What needs to happen and why is it important from an overall business objective perspective?

Results: measure your progress with AI

You’ll want to make sure you have a strong business case to continue investing in AI throughout your organization. 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 like creating more effective creative with AI or the ability to respond to trends or customer demand faster than ever before. Cost savings may come from reducing time spent on AI-eligible activities such as resizing or formatting creatives, translating or personalizing content for thousands of people. Whatever the right metric is for your project, be sure to set targets and monitor progress.

Responsibility: provide guidelines for AI implementation

Finally, based on our conversations with marketing leaders, it’s clear the industry is committed to responsible AI adoption. It’s important to remember that the market is flooded with AI models and vendors accessible to anyone in your organization. Work with trustworthy organizations that can explain how they will protect your data and intellectual property. Give your team access to reliable AI tools so they don’t make suboptimal decisions that could put your organization or data at risk.
Source: thinkwithgoogle