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Why Successful Marketing Strategies Must Integrate AI, Starting Today

(David, left; Xinli, right.)

As much of an impact as AI seems to be having on the world of advertising, the data tells a less sure-footed story. According to a report by Accenture Song, The Art of AI Maturity in Europe, 64% of companies are still in the testing phase when it comes to integrating AI into their operations with only 11% reaching ‘AI maturity’, analysis of 1200 global companies reveals. Accenture Song’s own machine learning models predict that the level of AI maturity will more than triple by the end of 2024, reaching 29% across Europe. 

Accenture Song’s David Williams, media data and measurement lead, and Xinli Jia, data and AI lead, see the advancements of generative AI as a real opportunity for business though they understand why some remain cautious, supporting a considered approach. David wants businesses to remember that AI should play in support of an existing business strategy, reminding that “it is not a new or separate strategy”. Education is essential to build AI confidence and David advises CMOs invest time educating themselves about the opportunities and intricacies of all things generative AI. Xinli predicts that even closer collaboration between marketing and technology will be required in the future to provide ever more seamless brand experiences to consumers, which Accenture Song is exploring in its new, multidisciplinary Media, Data & AI proposition. 

Today, David and Xinli tell LBB about the opportunities presented by successful AI integration, why there’s no ‘one size fits all’ AI strategy for businesses, and the questions CMOs should ask themselves to help determine the right AI applications. 

LBB> David, what kind of role has technology played over the course of your career? How has it evolved from when you first started to where you are now?

David> At the beginning of my career, digital was still growing up. Globally, digital was 15% of ad spend, whereas today it’s 70%. That growth transformed marketing into a more data and tech-driven role. It means that the marketing team is much closer to the organisation’s data and technology. It’s far more common today to find CMOs influencing decisions about digital transformation that affect the entire business. 

LBB> Xinli, Gen AI was the industry’s biggest talking point this year and it’s likely to remain so next year too. Fear, lack of knowledge, inability to see practical applications – what do you think are the driving forces behind the commotion it has caused in advertising and/or marketing specifically? 

Xinli> Gen AI is the biggest tech advancement of our careers. From a productivity and creativity perspective, there will be dramatic change. For now, so much is up in the air. The level of anxiety is understandable. The good news is that, according to Accenture’s report on AI, The Art of AI Maturity in Europe, the majority (64%) of firms are still testing the AI waters, and only 11% have reached AI maturity to achieve superior performance. Now is the time for organisations to come together to make decisions on how they will use it. 

LBB> David, as the media, data, and measurement lead at Accenture Song, you must be used to turning the abstract into concrete insights. What do you say to the CMOs who haven’t yet tried out generative AI or are apprehensive to do so?

David> I would advise CMOs to learn as much as they can on the topic. Talk to the experts, do the free courses, and read from good sources. Podcasts are great too. Google and Microsoft have free courses that give you an understanding of the basic components and how it all works. I’m not saying this to plug Accenture any further, but we do have a podcast called ‘Accenture AI Leaders’ which is genuinely very insightful! You can also try the brilliant WARC podcasts, which have some AI episodes. 

Then you’ll need to start working on alignment across the business. IT, marketing, sales, finance – every team will be exploring how to use generative AI and will have a unique perspective. Having a clear business strategy that each team understands is a good starting point. Generative AI should always support that business strategy. It is not a new or separate strategy.

LBB> Let’s get more granular. How can generative AI help media teams understand audiences, media channel planning, and media performance analysis? How else can it help improve the media process?

David> Our marketing and media performance team in Dublin is the Global Centre of Excellence for Gen AI for Media across Accenture Song. We have been developing Gen AI tools that support the marketing value chain across three main areas: 

Strategy and planning 

Creative and content 


I’ll use strategy and planning as an example. Marketers rely on many different data sources to make better decisions. Sources might include audience behaviour research, media consumption data, first-party data, evidence-based marketing studies, performance data, and brand tracking data. Collecting that data and using it to create a media strategy is a complex and time-consuming job. Accenture Song has created generative AI tools to handle the heavy lifting and make data meaningful and actionable. Similarly, for creative and content and activation, our generative AI tools are helping media teams do much more. 

LBB> Which AI-powered ad solutions do marketers need to know about and what can they aid marketers in achieving?

David> AI-powered ad solutions have been around for a few years. Google’s Performance Max and Meta’s Advantage+ are good examples. With AI-powered ads, the advertiser hands over control to the machine to reach a specific KPI, like ROAS. The lack of control and transparency is a concern for some advertisers. In our experience, when done right, the performance has been good. The performance does depend on the data you put in. The quality of your first-party data and the structure of your product feed are some of the most important factors. Overall, I see the move away from detailed targeting and complex ad account structures continuing, if the performance is there, of course. 

LBB> How is Accenture Song currently advising advertising clients to utilise AI? How do you foresee this evolving? 

David> It’s tempting to see AI as the solution to every problem. Each client is different. It starts with understanding how AI can help clients achieve their objectives, and what specific value AI can bring. Every organisation has finite amounts of budget and time. Understanding the specific value AI initiatives bring will help CMOs make decisions.

It can be difficult to put a number on the value of AI use cases, but these four questions are a good starting point:

How much could it increase the top line by increasing sales?

How much could it decrease the bottom line by reducing costs?

How much could it improve customer experience?

How much could it boost internal productivity?

Fitting AI into a clear overall strategy and determining its value puts you in a position to invest in AI. Once clients understand the value of AI, they can assess and develop their digital core. In other words, each business will need the right infrastructure to enable AI. This includes composable data integration, an accessible data foundation, cloud-first infrastructure, and data security.  

Another key area is talent and ways of working. Many advertising teams are already experimenting with generative AI. What we have seen is that people are taking the initiative to learn how generative AI can benefit their day to day. I think this will naturally lead to generative AI embedded into workflows as the technology becomes more integrated with the tools already in use. 

With technology as impactful as generative AI, governance and AI responsibility should be a focus area as there are inherent risks concerning intellectual property, ethics, and bias. Finally, this is a recurring theme but can’t be overstated, generative AI should be part of an overall strategy. Something to consider for the future is how different generative AI tools in each part of your business will interconnect. Implementing generative AI tools in isolation would be a mistake.

LBB> Tell us a little bit about the Media, Data & AI proposition – what kind of necessity was it borne out of? 

Xinli> Covid accelerated the rate of digital transformation, and generative AI will help continue that trend. From the customer’s point of view, they will come to expect better experiences from brands which require experience and collaboration across marketing and technology. That is exactly what our proposition is about. Media, Data & AI is a multidisciplinary team across several areas including media planning, channel optimisation, customer data, martech and AI. 

LBB> How and why do you think Media, Data & AI is going to help CMOs? Have you tested it with any clients so far?

David> It helps solve difficult questions that CMOs are facing. For example:


How can we prove that our marketing investments are achieving growth? 

How can we unlock value from customer data? 

How can we consolidate our data sources and automate the reporting flow for insights?

The answers often need cross-functional initiatives, and anyone with experience in cross-functional initiatives will tell you how challenging they can be. Media, Data & AI can help bridge gaps between teams within organisations. Having one team that speaks the languages of marketing, data and AI is what makes us different.

LBB> Are there any AI-related quick wins that CMOs need to have on their radar for 2024? And what should they keep in mind long-term?

David> In the short term – align on AI’s value to your organisation and start experimenting if you have not already. There may be off-the-shelf solutions available that address immediate needs or at least provide a way to experiment. It’s also worth learning what AI features your current martech stack will have available. We’re seeing that many clients are keen to move on from the ideation and experimentation stage, onto real AI integration into their teams. Accenture is working on over 1100 generative AI projects in the customer space. It’s very exciting that we can leverage such experience and skills for our clients. As for the long term – I won’t pretend to know how things will look in 12 months’ time, but it’s always a good mindset to stay clear and focused on the overall business strategy and goals as a guide for whatever comes next.

LBB> Finally, what do you have to say to the AI sceptics?

David> Some commentators have noted a potential pitfall – that generative AI will make mediocre work attainable for everyone. But so much of marketing is currently mediocre anyway! I hope that it will push marketing to be more creative and valuable, rather than becoming all about an efficiency culture or productivity.

I’ll finish by sharing something that I found interesting, and which might reflect how generative AI could impact marketing. Before photography, painters focused on realistic representation. Think of old portrait paintings where the painter tried to document exactly what they saw. This is called realism. When photography came along, the camera or ‘machine’ was far better and faster than any artist. This challenged artists to do things that the machine couldn’t – like incorporating emotions and multiple perspectives, which was a catalyst for abstract art. I think generative AI will push marketing in a similar way. It will hopefully allow marketers to focus more on meaningful work, pushing creativity forward. 

Originally Appeared Here

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