Customers today expect personalised, relevant experiences that speak directly to their needs and interests. At a recent Altron CMO Round Table, hosted in partnership with TechCentral, senior marketing executives gathered to discuss how data, analytics and AI are shaping the future of precision marketing.

The round table’s theme, From Data to Decisions: Harnessing AI for Smarter Marketing, fostered an insightful conversation around the opportunities, challenges and strategies to optimise revenue generation in a world where data and AI are key drivers of success, with participants sharing valuable insights into their current practices, challenges and aspirations for the future of data-driven customer engagement.

Precision marketing and AI: current realities

The round table opened with participants sharing their current approaches to precision marketing. Some marketing teams have successfully implemented data-driven strategies, while others are still in the early stages. Key challenges that emerged include:

Data integration and stakeholder buy-in: One of the most cited hurdles was the difficulty in integrating data from multiple sources, such as CRM systems, social media and customer support platforms. Beyond technical integration, participants emphasised the importance of involving a broad range of stakeholders from the outset. Starting with small-scale projects or proofs-of-concept (POCs) was seen as an effective way to demonstrate the value of data-driven marketing, building relationships across departments, and securing alignment before scaling initiatives. By clearly communicating the expected outcomes of data insights in early POCs, teams can foster a collaborative culture and ease adoption among stakeholders.
Data accessibility and storytelling: Another common theme was the need for data to be consumable and actionable. Participants noted that while data teams possess the technical expertise to gather insights, they often lack storytelling capabilities to make these insights meaningful to marketers. Conversely, marketing teams, while skilled in communication, may lack the technical fluency needed to interpret complex data. Bridging this gap is essential, and some organisations are experimenting with embedding data professionals within marketing teams to foster a culture of collaboration and cross-functional learning.
Targeting and audience segmentation: Many teams face challenges in identifying the best segments to target. A phased approach, where internal stakeholders serve as the initial test audience for campaigns, emerged as a popular strategy to refine targeting before expanding to external audiences. This approach helps organisations refine their data-driven strategies in a controlled environment.
Data transparency with media partners: Participants expressed concerns over the lack of transparency in tools provided by media partners like Google and Meta. Although these platforms offer valuable algorithms, they often operate as “black boxes”, making it difficult for marketers to assess their effectiveness fully. Participants are eager for increased visibility into these platforms’ processes and algorithms to better leverage their potential.

Measuring marketing’s impact on business outcomes

Accurately measuring and communicating the impact of marketing on business outcomes remains a priority. Participants discussed strategies for translating campaign success into measurable, meaningful results that resonate with senior leadership. AI and data analytics play an increasingly central role in connecting marketing initiatives with revenue growth and customer lifetime value, but challenges remain in aligning these metrics with business goals.

One organisation demonstrated the benefits of integrating data professionals within their marketing team, including renaming the department to reflect its broader focus on revenue growth. This integration and data-driven approach has helped the organisation reframe their value proposition to gain a competitive edge, allowed them to optimise pricing strategies based on customer segmentation and price sensitivity, and even monetise their data by sharing insights with clients. Other organisations are experimenting with AI-driven customer behaviour prediction models that allow for greater personalisation, which in turn enhances customer loyalty and drives measurable outcomes.

Participants also recognised the potential to monetise data beyond their own ecosystems, creating value for both organisations and their customers.

Addressing talent and skills gaps

As marketing evolves to rely heavily on data and AI, the demand for data-savvy talent has become increasingly urgent. Participants highlighted the difficulty in recruiting individuals with the right combination of marketing and data skills. Many are addressing this gap through upskilling initiatives and strategic partnerships.

The discussion underscored the importance of a problem-centric approach to AI adoption, focusing on clear use cases rather than technology for its own sake. While generative AI tools like ChatGPT have democratised data analysis, their open-ended capabilities can sometimes overwhelm users, leading to “analysis paralysis”. Organisations are recognising the need for continuous education and effective prompt engineering to maximise the potential of these tools. Participants emphasised the value of structured training programs to build marketers’ confidence in using AI and data analytics. Suggestions included deploying AI champions within departments to provide hands-on support and creating experiential learning opportunities to develop skills through real-world applications.

Balancing short-term execution with long-term strategy

Balancing the immediate demands of campaign execution with a long-term strategic focus remains a significant challenge. Participants emphasised that while AI can streamline short-term processes, it also has the potential to drive broader, strategic objectives, such as customer journey mapping and life-cycle management.

To help marketing teams shift focus from day-to-day execution to long-term strategy, participants suggested embedding predictive analytics into campaign planning and investing in tools that enable automated decision making. These tools can free up valuable time for marketers to concentrate on high-level objectives, such as brand differentiation and customer engagement.

Modernising marketing capabilities for the future

Looking toward the future, the round table underscored the importance of modernising marketing capabilities to remain competitive in an AI-driven world. This involves not only upskilling teams in data and analytics but also rethinking the organisation’s approach to marketing. With data democratisation, there’s a need for organisations to establish clear data governance frameworks, ensure ethical data usage and address intellectual property concerns associated with generative AI. Participants recognised the need for strong policies to guide ethical data sharing, protect customer privacy and maintain brand integrity.

Participants also noted the evolving role of marketing agencies. As organisations gain direct access to data and insights, they increasingly view agencies as execution partners rather than strategic advisors. This shift is prompting many companies to bring strategy in-house while outsourcing campaign execution to agencies, ensuring that data insights align closely with internal brand and business objectives.

The future of AI in marketing: challenges and opportunities

A recurring theme was the potential for AI to transform the marketing function entirely. However, participants acknowledged that rapid AI advancements also introduce complexities, such as data protection and cybersecurity concerns. Additionally, while AI tools hold promise, their effectiveness relies heavily on human input. There is a growing need for marketing teams to feel comfortable using AI tools, and this may require a cultural shift that encourages curiosity, experimentation and ongoing learning.

Participants also discussed the broader marketing ecosystem in South Africa, noting that while AI has the potential to drive collective growth across industries, a cohesive framework for data integration is lacking. There was a call for a national- or industry-level framework to help South African companies harness data more effectively for the benefit of customers and the broader economy.

Ultimately, the future of precision marketing will require a balance of technical acumen, ethical considerations and a deep understanding of the customer journey. By establishing strong data governance, fostering a culture of collaboration and continuous learning, building internal capacity, and being prepared for the evolving dynamics between in-house teams and external partners, organisations can harness the power of AI to drive impactful, data-driven marketing strategies that resonate with today’s increasingly discerning customers.