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Marketing & MediaStep into your potential this youth month and honour Youth Month
Unathi Mahlangu 8 minutes




It's about understanding that brands, like people, evolve through their experiences. The key is to stay focused on meeting customer needs, and that's where marketing comes in – communicating our value proposition effectively.
Cassava Technologies is an ecosystem of brands, offering a portfolio that covers everything from connectivity to AI. Our narrative is simple: we provide solutions for various tech needs.
We prioritise understanding our audience and tailor our communication accordingly.
Marketing plays a crucial role in ensuring we remain customer centric. We're involved early on, working closely with new acquisitions to test their value proposition, understand their target audience, and assess the competitive landscape. This helps us determine where to play and how to win.
The principles of marketing are transferable across industries. Whether you're selling beer or broadband, it's about understanding the customer and communicating value.
The key is agility, curiosity, and a willingness to learn. The tech landscape is constantly evolving, so continuous learning is essential.
It starts with insight generation and a robust innovation model. We analyse insights, look for foresights, and develop a strategic framework.
The exciting part is execution and iteration – testing, learning, and adapting. We measure results and ensure our efforts align with business goals.
AI is a fantastic tool, and we're using it across various areas, including ideation, content creation, personalization, and research. For example, in ideation, AI can help us explore contrasting ideas and visualise concepts, sparking creativity in new ways.
It's like having AI brainstorm with you, pulling data from diverse sources at incredible speed.
AI is a powerful tool, but it's only as good as the humans guiding it. We use AI to augment our creativity and efficiency, not replace it.
The human element is crucial in areas like prompting, interpretation, and addressing potential biases in AI models.