The development and widespread use of technology, particularly internet-based innovations, have transformed how society communicates in daily life and professional contexts. This shift extends to businesses operating in today’s digital landscape, where digital transformation has become an area of increasing interest. Marketing promotion, a central focus for marketers, has moved from traditional methods to digital channels.
In today’s business environment, promotional activities are conducted mainly through digital methods due to intense competition, widespread internet access, and the demand for personalised experiences. In this context, the term ‘digital promotion’ has gained considerable attention in both scholarly and professional circles, emerging as a prominent topic of discussion.
The rapidly evolving digital promotion domain has witnessed a profound transformation fuelled by the emergence of Artificial Intelligence (AI) and Machine Learning (ML) technologies. These innovative tools have significantly impacted the domain of digital promotion, empowering marketers to enhance their strategies and deliver more personalised and effective campaigns; for example, McDonald’s AI system dynamically adapts the menu board presentation in the advertisements, ensuring the most suitable menu options are preciously pushed to the target users.
Further, Lexus relies on IBM Watson to craft the scripts for its TV commercials, driven by intuition. Affectiva, based on affective analytics, detects consumers’ emotions as they view advertisements. Meanwhile, Replika, a chatbot powered by machine learning, offers emotional support to consumers by mirroring their communication styles.
While practitioners have shown strong interest in AI and ML for digital promotions, scholars have also turned their attention to these technologies within the domain of digital promotion. Therefore, as scholars in the domain of marketing, V. G. P. Lakshika, B. T. K. Chathuranga, and P G S Amila Jayarathne have carried out a study to synthesise the road map of AI and ML in digital promotions and map out the role of AI and ML in future digital promotions. The study’s outcome was published as a research paper, ‘The evolving role of AI and ML in digital promotion: a systematic review and research agenda’ in the Journal of Marketing Analytics by Springer.
Knowledge about using AI and ML in digital promotion has drastically increased since 2020. The same trend is expected to continue, with contributions likely growing. The USA has the highest level of scientific production among the countries in the world related to AI and ML in digital promotion. Other countries like the UK, Germany, and France also significantly contributed. Mainly in the Asian region, countries like China and India are also participating in bringing novel knowledge to practice.
The role of AI and ML in digital promotion would evolve in multiple paths: personalisation and targeting, social media marketing, advert creative and content generation, optimising customer interactions, predictive analysis, and ethics and privacy concerns. Also, AI directly links to paths such as personalisation and targeting, social media marketing, ad creative and content generation, and ethics and privacy. This signifies its role in tailoring user experiences, engaging audiences, and racing ethical considerations in digital promotions. On the other hand, ML directly connects to optimising customer interactions and predictive analysis, highlighting its utility in understanding consumer behaviour and forecasting trends.
AI and ML drive personalisation in digital promotion by analysing vast customer data to deliver tailored content and recommendations. AI identifies patterns and user preferences, while ML continuously learns from interactions to refine suggestions. For instance, AI-powered recommendation engines suggest products based on browsing history, and ML improves these recommendations over time.
AI also enhances audience segmentation, enabling precise targeting, while ML refines behavioural targeting to deliver personalised marketing messages. Future research should explore how AI and ML enhance campaign management, audience segmentation, and real-time content customisation. Studies can investigate the impact of tailored marketing on customer retention and loyalty while analysing the role of AI in delivering highly personalised offers.
In social media marketing, AI recognises branded content that engages users, optimising audience and sentiment analytics. ML enhances these efforts by learning from engagement metrics, predicting content that resonates with specific audiences, and allowing real-time adaptability. AI and ML improve targeting, customer engagement, and overall user experience. Researchers should explore their role in automating content creation, monitoring campaigns, and synchronising efforts across platforms. Advanced sentiment analysis, campaign tracking, and strategies for overcoming adoption barriers also warrant investigation.
AI and ML streamline content creation by automating processes such as generating ad copy and visuals based on audience insights. AI produces creative content aligned with user preferences, while ML refines it using engagement data to improve relevance. This data-driven approach ensures content evolves to match audience expectations, making digital promotions more effective.
Future research should address how AI complements human creativity, overcomes limitations in content creation, and transforms content marketing strategies. Emphasis should be placed on balancing automation with creativity to enhance efficiency.
AI and ML optimise customer interactions by powering chatbots and virtual assistants to handle queries and deliver personalised responses. ML further adapts based on customer feedback, creating smoother and more efficient interactions. By analysing customer journeys, these technologies refine digital promotions at various touchpoints, improve CRM, and strengthen customer relationships. Researchers should explore AI and ML’s capabilities in mapping customer journeys, real-time data monitoring, and driving personalised experiences.
Fuelled by AI and ML, predictive analytics is a cornerstone of modern marketing. These technologies analyse vast datasets to forecast consumer behaviour, optimise campaigns, and enable data-driven decision-making. This results in higher engagement, conversions, and revenue growth. Future studies should develop predictive models to evaluate campaign outcomes, assess the efficiency of AI-driven analytics, and address challenges like data security and algorithmic bias.
Ethics and privacy are critical in AI-driven marketing. The collection and use of large datasets raise concerns about transparency, consent, and fairness. ML algorithms can unintentionally reinforce biases, leading to unfair targeting. Ensuring compliance with privacy regulations like GDPR and CCPA is essential to maintain trust.
Researchers should develop ethical frameworks, alternative targeting methods, and strategies to mitigate risks while balancing innovation with consumer trust and privacy.
In summary, AI and ML transform digital promotions through personalisation, engagement, and predictive analytics while addressing critical challenges in ethics and privacy for sustainable adoption.
This revolutionary nature of the role AI and ML play in digital promotion certainly challenges conventional marketers, pushes them towards digital platforms, and demands them to navigate promotional activities supported by AI and ML along the suggested road maps to survive or outperform in the global competition.
By V. G. P. Lakshika
Senior Lecturer
Department of Marketing Management
University of Sri Jayewardenepura,
B. T. K. Chathuranga
Lecturer
Department of Marketing Management
University of Sri Jayewardenepura and
Prof. (Dr.) P. G. S. A. Jayarathne
Professor in Marketing
Department of Marketing Management
University of Sri Jayewardenepura
