In the ever-evolving landscape of business, marketing stands out as a domain with immense potential gains from artificial intelligence (AI). The fundamental activities of marketing, encompassing understanding customer needs, aligning them with products and services, and influencing purchasing decisions, can be significantly enhanced by AI. McKinsey’s 2018 analysis of over 400 advanced use cases underscored marketing as the sector where AI could contribute the most value. Evidently, chief marketing officers are increasingly recognizing this potential, with a 27% surge in AI implementation reported in an August 2019 survey by the American Marketing Association.
Delving deeper into AI’s impact on marketing, a 2020 Deloitte global survey of early AI adopters revealed that three of the top five AI objectives were marketing-centric: enhancing existing products and services, creating new offerings, and fortifying customer relationships. As AI continues to permeate marketing, it is imperative for CMOs to comprehend the existing AI applications and anticipate their evolution. Drawing from a decade of experience in data analytics, AI, and marketing consultation, we propose a framework that aids CMOs in categorizing current AI projects and strategically planning future ones.
Current Landscape of AI in Marketing
AI has already found its way into marketing, handling diverse tasks such as programmatic ad placement, predictive sales forecasting, and bolstering customer service efforts. A multitude of well-established AI applications in marketing includes chatbots for lead development, inbound call analysis, marketing campaign automation, pricing strategies, and social media planning. These applications span every stage of the customer journey, from consideration and research to purchase and post-sale support.
Categorizing Marketing AI
To navigate the evolving terrain of marketing AI, it’s crucial to understand two key dimensions: intelligence level and integration with existing systems. Intelligence levels range from task automation, handling repetitive, structured tasks, to machine learning, which involves training algorithms with large datasets for complex predictions. On the integration front, AI can be stand-alone, existing as distinct programs, or integrated into broader platforms, seamlessly embedded within existing systems.
Combining these dimensions results in a four-quadrant framework: stand-alone machine learning apps, integrated machine learning apps, stand-alone task-automation apps, and integrated task-automation apps.
Stepped Approach to Implementation
While stand-alone applications still have their place, the long-term value lies in integrated machine-learning applications. Marketers are advised to move gradually towards integrating AI within their current systems, a sentiment echoed by 74% of global AI executives in the 2020 Deloitte survey. A stepwise approach often begins with simple rule-based applications, progressing to more sophisticated machine-learning models as companies accumulate data and AI proficiency.
Challenges and Risks
Implementing AI, even in its simplest forms, poses challenges. Configuring stand-alone task-automation AI can be intricate, requiring specific workflows and skill sets. As sophistication increases, considerations about integrating AI into third-party platforms and addressing customer concerns about privacy, security, and data ownership become paramount. Establishing ethics and privacy review boards is crucial to vet AI projects involving customer data, ensuring transparency and mitigating biases.
Looking Ahead
While AI holds enormous promise for marketing, realism is key. AI, at its current stage, excels in specific tasks rather than orchestrating entire marketing functions. Nevertheless, it already delivers substantial benefits and is indispensable in certain activities. The transformative journey of AI in marketing will span decades, demanding sustained attention to building capabilities and addressing risks. For CMOs seeking to harness AI’s current functionalities and future potential, developing a strategic roadmap today is imperative.
