What’s up folks, today we’re joined by Aliaksandra Lamachenka, Marketing Technology Consultant and Nonprofit founder.

Summary: Aliaksandra takes us on a journey through the evolving AI landscape in marketing, promising a future shaped by deep human expertise and broad understanding, all areas where AI is still playing catch up. The episode is ripe with insights about the rise of hybrid, business-savvy data product managers, who are subtly revolutionizing martech by marrying marketing perspectives with innovative thinking. They are unearthing overlooked insights, much like Duolingo, which leveraged data science to redefine its target metrics and boost its DAU. Amidst the din of the composable vs packaged CDPs debate, Aliaksandra brings our attention back to the basics - the crucial need for quality, traceable data. This illuminates the pivotal role of open data hubs, which could unlock the next chapter in efficient data management and utilization. Meanwhile, vendors of composable data platforms face a crossroads: will they expand to cater to growing customer needs or hold fast to their roots? Their decision could very well shape the future of martech, steering its course towards either the democratization of data or maintenance of the status quo.

About Aliaksandra

• Born in Belarus, Aliaksandra got her start in gaming and SaaS startups in product marketing roles
• In 2017 she became Head of Marketing at SplitMetrics, a team of experts building the future of mobile marketing tools
• She then moved to the UK to lead a product marketing team at Skyscanner, the popular flight comparison site where she focused on app growth and martech
• In 2021, she joined Depop as Marketing Technology Lead where she owned compliance management, multi-touch attribution and much more
• Since then she’s partnered with various companies as a Marketing Technology and Growth advisor, including the popular female health app– Flo
• In April of last year, Aliaksandra co-founded Leleka Art, an online nonprofit marketplace that allows you to buy artwork made by children from Ukraine built on top of a custom money transfer system 
• Today, she’s scaled Leleka to a team of 30+ volunteers, +5k sellers and 15k works of art helping children and their families make over 30k

The Organic Evolution of AI in Marketing and Lessons from Architectural History

Aliaksandra takes a particularly compelling approach to understanding the potential role of AI in marketing. Drawing a unique analogy from the records of Japanese architectural history, she paints a picture of how AI's integration could be less of a disruptive force, but rather an organic and gradual process.

Following the Second World War, a group of young Japanese architects refused to view architecture as merely a functional tool. They envisioned buildings as living organisms, an idea that later came to be known as "Japanese metabolism." These architects designed structures with a central spine, to which they could add or subtract modular capsules as needed. At the time, their ideas were regarded as revolutionary, indicative of what the future would undoubtedly hold.

Decades later, their concepts have not been realized in their envisioned form, mainly being used for storage purposes, yet they have certainly left an indelible mark. The idea of high modularity, the foundational spine with small attachable elements, is now visible in various facets of our lives. You can observe it in modular housing, landscape-integrated buildings, and even in the functionality of platforms like Pandora, Tesla, or the App Store.

Aliaksandra sees AI's trajectory in a similar light. Like the revolutionary architectural concepts of the past, AI's ideas may appear bold and groundbreaking. However, their integration will likely be more gradual than anticipated, quietly shaping our future. Much like the world adapted to the concepts of modularity, so too will it adapt to AI.

Just as we accept modular buildings as a natural part of our world today, in 20 or 50 years, AI's presence in marketing will feel just as natural and intrinsic. AI won't displace marketers overnight but will instead weave itself into the fabric of the profession organically.

Takeaway: The progression of AI in marketing is not likely to be a sudden, disruptive force. Instead, as Aliaksandra's rich analogy suggests, AI will bring about a natural evolution in the field, slowly but surely shaping its future.

AI and the Future of Early-Stage Marketing Careers, Depth, Breadth, and Generalism

One of Aliaksandra’s key points is the future value of professionals who can operate at the intersection of different industries or specialties. In a world where the boundaries between industries are blurring, being an expert in more than one field could be a significant advantage. For instance, understanding both engineering and marketing, or medicine and business, can provide a broader perspective and unique insights. In the future job market, the collision of different worlds could be the breeding ground for innovation.

However, depth of expertise remains equally critical, and this is something Aliaksandra wishes she had realized earlier in her career. She warns against the temptation of becoming a generalist too early on, of trying to learn a little bit of everything. Instead, she suggests starting by deepening expertise in one or two fields, then gradually acquiring knowledge in additional areas. This approach allows for a solid foundation of deep expertise paired with a broad understanding, a balance that she believes could be crucial for early-career success in the evolving landscape.

Lastly, she draws our attention to the inherently generalistic nature of AI language models, like ChatGPT. These models are designed to draw on a wide range of sources and generalize information, lacking the depth of expertise that humans can have. In this regard, individuals with profound expertise in their field have an advantage, as it would be challenging for a language model to compete with their specialized knowledge.

Takeaway: The future of marketing careers may lie in cultivating a blend of deep expertise, cross-industry knowledge, and a broad understanding. Above all, it's the depth of human expertise that AI has yet to match.

The Impact of Business-Oriented Machine Learning/Data Product Managers in Martech Teams

Aliaksandra opened up about her experiences working with these dynamic professionals known as business-oriented machine learning/data product managers. Their passion for growth and marketing sets them apart as natural innovators. Interestingly, their lack of traditional marketing knowledge or business processes doesn't limit them, but rather fuels their innovative mindset.

She explained that these professionals constantly challenge established beliefs and norms within the team. They aren't afraid to question the reasoning behind the set processes and methodologies. This sense of inquisitiveness often leads to uncovering novel perspectives and solutions that may have been neglected due to the team's ingrained biases.

Another area where these data product managers excel is in their effective collaboration with engineering teams. With a firm grasp of technical complexities and trade-offs, they can have meaningful exchanges with engineers, propose manageable initiatives, and break down larger projects into smaller, achievable parts. In essence, they're the link between the marketing and engineering teams, bringing valuable perspectives to both sides.

However...