(David, left, Shinri, right)
Accenture Song's David Williams, head of media data and measurement, and Xinli Jia, head of data and AI, believe advances in generative AI represent a real opportunity for businesses, but some are cautious. We understand why this is the case and support a considered approach. David wants businesses to remember that AI should play a role in supporting existing business strategies, and that “AI is not a new or separate strategy.” Education is essential to building trust in AI, and David advises his CMOs to invest time in learning about all the opportunities and complexities of generative AI. Xinli predicts that the future will require even closer collaboration between marketing and technology to provide consumers with ever more seamless brand experiences, and Accenture's song is a new multidisciplinary We are exploring this with proposals for media, data, and AI.
Today, David and Xinli speak to LBB about the opportunities presented by successful AI integration, why enterprises don't have a “one-size-fits-all” AI strategy, and the questions CMOs should ask themselves to determine the right AI application.
LBB> David, what role has technology played in your career? How has it evolved from when you first started to now?
David> When I started my career, digital was still in its infancy. Globally, the share of digital in ad spend was 15%; it is now 70%. This growth has transformed marketing into a more data and technology-driven role. This means marketing teams are much closer to the organization's data and technology. Today, it is much more common for CMOs to influence digital transformation decisions that impact the entire business.
LBB> Xinli, Gen AI has been the biggest buzz in the industry this year, and it's likely to continue to be so next year. What do you think are the driving forces behind the fear, lack of knowledge, lack of practical application, and the uproar caused specifically in advertising and marketing?
Xinli> Gen AI is the biggest technology advancement of our career. There will be dramatic changes in terms of productivity and creativity. For now, a lot is still up in the air. The level of anxiety is understandable. The good news is that Accenture's AI report, The Art of AI Maturity in Europe, shows that the majority (64%) of companies are still testing areas of AI and are at a level of AI maturity that allows them to achieve superior performance. Only 11% have reached this point. Now is the time for organizations to come together and decide how to use it.
LBB> David, as Head of Media, Data and Measurement at Accenture Song, you need to be comfortable turning the abstract into concrete insights. What would you say to a CMO who hasn't yet tried generative AI or is nervous about trying it?
Next, you need to start working on aligning your entire business. IT, marketing, sales, finance – all teams will explore how to use generative AI and have unique perspectives. Having a clear business strategy that each team understands is a good starting point. Generative AI should always support that business strategy. This is not a new or separate strategy.
LBB> Let's take a closer look. How can generative AI help media teams understand their audience, media channel planning, media performance analysis? How else can it help improve media processes?
David> Our Marketing and Media Performance team in Dublin is a global center of excellence for Gen AI for Media across Accenture Song. We have developed Gen AI tools to support the marketing value chain across three key areas:
● strategy and planning
● creative and content
● Activation
Use strategy and planning as an example. Marketers rely on a variety of data sources to make better decisions. Sources may include audience behavior research, media consumption data, first-party data, evidence-based marketing research, performance data, brand tracking data, and more. Collecting that data and using it to create a media strategy is a complex and time-consuming task. Accenture Song has created generative AI tools to take care of the heavy lifting and make data meaningful and actionable. Similarly, when it comes to creative, content, and activation, our generative AI tools are empowering media teams to do more.
LBB> Which AI-powered advertising solutions should marketers know about, and what can they help marketers achieve?
David> AI-powered advertising solutions have been around for several years. Good examples are Google's P-MAX and Meta's Advantage+. With AI-powered advertising, the advertiser hands over control to the machine to achieve certain KPIs such as her ROAS. The lack of control and transparency is a concern for some advertisers. In our experience, performance has been good if done correctly. Performance varies depending on data entered. The quality of your first-party data and the structure of your product feed are some of the most important factors. Overall, we see a continued shift away from granular targeting and complex ad account structures, subject to performance, of course.
LBB> How is Accenture Song currently advising advertising clients to leverage AI? How do you foresee this evolution?
David> It's tempting to think that AI is the solution to every problem. Every client is different. It starts with understanding how AI can help clients achieve their goals and what tangible value it brings. Every organization has limited budget and time. Understanding the tangible value that AI initiatives bring can help CMOs make decisions.
Quantifying the value of AI use cases can be difficult, but these four questions are a good starting point:
How much can you increase your top line by increasing sales?
How much will the cost reduction reduce revenue?
How much will it improve the customer experience?
How much will it increase productivity within your company?
By fitting AI into a clear overall strategy and determining its value, you will be in a position to invest in AI. Once clients understand the value of AI, they can evaluate and develop their digital core. In other words, each business will need the right infrastructure to enable AI. This includes composable data integration, accessible data foundations, cloud-first infrastructure, and data security.
Another important area is talent and work style. Many advertising teams are already experimenting with generative AI. What we're seeing is people taking the initiative to learn how generative AI can benefit their daily lives. As technology becomes more integrated with the tools already in use, I think this will naturally lead to generative AI being embedded into workflows.
With a technology as impactful as generative AI, there are inherent risks related to intellectual property, ethics, and bias, so governance and AI accountability should be areas of focus. Finally, this is a recurring theme, but one that cannot be overstated. Generative AI should be part of your overall strategy. A future consideration is how the various generative AI tools in different parts of the business will be interconnected. Implementing generative AI tools alone is a mistake.
LBB> Tell us a little bit about your media, data and AI proposition – how did it emerge from the need?
Xinli> COVID-19 has accelerated the pace of digital transformation, and generative AI can help continue that trend. From a customer perspective, they will expect a better experience from brands that require experience and collaboration across marketing and technology. That's exactly what we propose. Media, Data, and AI is a multidisciplinary team that spans multiple disciplines including media planning, channel optimization, customer data, martech, and AI.
LBB> How and why do you think media, data and AI will help CMOs? Have you tested it with your clients so far?
David> Helping CMOs solve the toughest problems they face. for example:
How can you prove that your marketing investments are delivering growth?
How can you derive value from your customer data?
How can you integrate data sources and automate reporting flows for insights?
The answers often require cross-functional efforts, and anyone who has worked cross-functionally knows how difficult that can be. Media, data, and AI can help bridge the gap between teams within your organization. Having one team that speaks the language of marketing, data, and AI is what sets us apart.
LBB> Are there any AI-related quick wins that CMOs should keep in mind for 2024? And what should they keep in mind in the long term?
David> In the short term, adjust the value of AI to your organization and start experimenting if you haven't already. Off-the-shelf solutions may be available that address your immediate needs or at least provide a method for experimentation. It’s also worth learning what AI capabilities are available in your current martech stack. We see that many clients are keen to move from the ideation and experimentation stage to the actual integration of AI into their teams. Accenture is working on more than 1,100 generative AI projects in the customer field. It is very exciting to be able to put this experience and skill to work for our clients. In the long term, we don't pretend to know what things will look like in 12 months' time, but we do want to keep our overall business strategy and goals clear and as a guide to what's going to happen next. Concentration is always a good idea.
LBB> Lastly, is there anything you would like to say to AI skeptics?
David> Some commentators have pointed to the potential pitfall of generative AI, which makes mediocre tasks achievable by anyone. But a lot of marketing is just mediocre as it stands. I hope that marketing will become more creative and valuable, rather than focusing only on efficiency culture and productivity.
I'll end by sharing something that I found interesting and that may reflect how generative AI could impact marketing. Before photography, painters focused on realistic expression. Remember the old portraits in which the painter tried to record exactly what he saw? This is called realism. When photography first appeared, cameras or “machines” were far better and faster than any artist. This allowed artists to do things that machines couldn't, such as incorporating emotion and multiple perspectives, which gave rise to abstract art. I think generative AI will drive marketing in a similar way. This is expected to allow marketers to focus more on meaningful work and advance creativity.
