Edited by Peter Steidl, Behavior change expert

This article is part of a three-part series. You can read the first part here.

Neuromarketing can contribute to the effectiveness and efficiency of marketing strategies, plans, and their execution by triggering psychological biases and/or neurotransmitters that shape preferences, purchase intent and behavior.

Today, neuromarketing is becoming mainstream with priming, storytelling, sensory cues, activating goals and associations, triggering neurotransmitters and hormones, and tapping into hard-wired brain circuits. Coca-Cola’s emotional storytelling and sensory branding, McDonald’s sensory marketing and menu engineering, or Amazon’s personalization and urgency cues are case examples every marketer is familiar with.

This is happening today, but what does the future hold?

Technological advances are reshaping best practice. The use of Generative AI to produce campaign assets optimized for neural engagement has already entered the mainstream. So have chatbots and automated customer service facilitating real-time engagement, improving responsiveness and customer satisfaction. Marketing automation tools increasingly take over repetitive tasks such as email campaigns, social media scheduling, and ad placements.

With respect to Neuromarketing there are two pathways. AI can be trained by providing an understanding of neuromarketing principles, insights, and tools and the use of primes and triggers. Alternatively, AI learns what works best based on training data and subsequently from applications and, as neuromarketing boosts the effectiveness of marketing initiatives, AI starts to extensively use neuromarketing tools and insights. In this case, AI would not have a deeper understanding of neuromarketing principles, but rather rely on what works best.

Of course, creative agencies are not alone when it comes to AI changing practices. Arguably, the work of media agencies has been even more affected by the technological revolution. This is not a surprise, as the use of digital media delivers a host of digital data that can be used by AI to analyze and optimize. Real-time performance metrics such as impressions, clicks, conversions, cost-per-click (CPC), cost-per-acquisition (CPA), return on ad spend (ROAS) and more allow for the identification of underperforming ads or channels and the reallocation of budgets, optimizing timing and frequency. Tracking attribution provides insights into which touchpoints drive conversions.

While there are some examples of personalization in real world applications, it is in the digital space where progress is rapid. Advanced analytics, personalization, and predictive analytics facilitate the development and real-time adaptation of marketing campaigns and initiatives. AI auto-generates dynamic ads, adjusts visuals, pacing, and messaging in real time to optimize the impact of these exposures.

The adoption of AR, VR, and interactive digital experiences is at an early stage, but will eventually redefine how brands tell their stories and engage audiences. Augmented Reality (AR) and Virtual Reality (VR) allow customers to interact with products and brands in an immersive way, from virtual try-ons to interactive showrooms while embedding brand messages into episodic memories by combining sensory stimuli.

Travel companies, for example, can use VR to evoke nostalgia for destinations or triggering booking decisions; fashion brands can show how the potential buyer looks like in a new outfit; furniture stores or manufacturers can show how their products look like in a home or office setting, and so forth.

Given the impact of technologies which, in most applications, require new skill sets while making some positions redundant, one may wonder what the marketing department of the future will look like.

As we have already observed, AI will be deeply integrated into every aspect of marketing, from strategy to execution. More specifically,

Clearly, a traditional marketing department will not be able to accommodate these developments, yet most marketing departments are still organized along traditional lines and utilize a skill-mix that is increasingly misaligned with the tasks at hand.

Here are some of the key features of the marketing department of the future:

Agility

Keeping pace with AI’s progress

Collaboration and integration

These changes will be essential to a marketing department’s success, but the required changes on processes, focus, and skill mix are likely to play out over several years, forced by technological progress and competitive pressures.

The fragmentation of agencies providing marketing services: creative, media, social media agencies, market research, and consulting firms is inefficient and causes a burden for a client who must integrate diverse inputs into an internally consistent strategy and plan.

Integration of these functions, i.e., creating a single agency that brings all services together and – most importantly – integrates them by ensuring employees have expertise in different areas rather than working in silos, is arguably a utopian dream in today’s world of specialization.

However, what if AI is starting to integrate different elements, i.e., creates marketing, advertising, and media plans, develops market research briefs and analyses the resulting data taking patterns across a multitude of datasets into account, identifies the right KPIs, maybe even negotiates and books media, and adapts the exposure of individuals real-time to optimize the impact of the campaign and more?

Once that’s possible there are two core options: either agencies integrate services and rely heavily on AI to support their work, or their clients use AI, minimizing the input they require from their agencies. Naturally, not all agencies will go down this path and not all clients will look for an extensive use of AI – at least not in the medium-term. But long-term AI will drive the evolution of the advertising sector and the approach taken by marketing departments and teams.

How AI and data integration influence the creative process in agencies of the future

AI tools can rapidly generate a wide variety of concepts, headlines, visual treatments, and campaign ideas, acting as a powerful brainstorming partner for creative teams. But it is largely a collaboration partner, with humans evaluating the output and steering the direction the process takes with their prompts. They adjust and refine AI’s output and infuse creative concepts and ideas with emotion and, where relevant, cultural nuance. As AI generates more content, creative professionals increasingly act as curators and editors, ensuring outputs are original, on-brand, and free of bias or ethical pitfalls.

But when things get complex, AI takes the lead: AI enables agencies to maintain consistent visual and narrative themes across large, multi-platform campaigns. It can adapt creative assets and personalize at scale, ensuring brand coherence while catering to diverse audiences.

Data integration allows AI to craft hyper-personalized messages, images, and experiences based on real-time insights into audience behavior, preferences, and motivations. Campaigns become more relevant and engaging, driving higher ROI.

On the downside, there is a risk of over-reliance on AI which can lead to a loss of originality.

The third and final part of the article is available here.