“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Big data, programmatic access to high-performance media inventory and the maturity of cloud-based AI tools and services are quickly changing the landscape for marketers – and the people who work in marketing organizations.
While this trend is just now taking off, it’s clear how fast it’s accelerating. Top-performing companies are more than twice as likely to embrace AI for marketing than their peers, 28% vs. 12%, according to Adobe. Retailers are investing billions every year into AI-based marketing and customer service solutions to improve the shopping experience. Even in B2B, we’re seeing a surge in adoption for AI: Sales leaders in the configure-quote-price marketing world expect their AI adoption to increase by 155% across sales teams in two years.
If your company isn’t all-in on adopting AI today, it will be soon. As with any change, this creates opportunity. But traditional skill sets may not be as highly valued as they once were within marketing organizations. As this new frontier emerges, it’s a good time to take stock of what’s valued now in a growth-oriented marketing team, and how that may change over the next few years as autonomous marketing technology becomes more prevalent.
While senior roles are likely to remain filled by experienced marketers, over the last decade we’ve seen a shift toward a “growth hacking” mentality within the most successful organizations. Growth hacking prizes data-driven thinking. Learning quickly across channels and platforms that change and evolve constantly – and the flexibility to operate across those channels for maximum impact – will remain a key attribute for success.
Another hallmark of the growth hacking movement is closing the gap between marketing and product. Successful marketing organizations have championed the task of linking marketing to product development, creating the infrastructure for advanced data collection and analysis. That’s here to stay.
So in many ways, the “growth hacking” movement foreshadows the future of AI-powered marketing teams. The importance of data-driven, analytical thinking will always be prized. So too, will people who learn on their feet, remain flexible in times of change and demonstrate their ability to spot new or unorthodox opportunities for growth.
AI-driven systems depend on steady streams of clean data. The shrinking chasm between product and marketing is now poised to really pay off.
The need for marketing management doesn’t go away in the world of autonomous marketing. But with this new class of technology, teams will become more productive and effective, so they will be smaller and tighter in nature as the structure evolves for humans and machines to coexist.
Most tasks that AI is best suited to automate are drudgework, including running pivot tables, maintaining spreadsheets and custom dashboards, and making decisions about budget allocations. This will become especially evident when many campaign, media buying and data scientist roles become obsolete as machines prove they can handle that work better, smarter and more efficiently than humans. Automating these time-consuming, nonstrategic activities with intelligent machines frees people up to be more creative, develop more experiments and devote their time to the activity in which humans are uniquely suited to make an impact: strategy.
Teams in the autonomous marketing future will be filled with people who are analytical, strategic thinkers who understand the importance of experimentation at scale. Design-oriented thinkers, who can look at volumes of data and isolate meaningful signals from the noise in a user journey, will also become more valuable. The pressure to create more creatives, in greater volumes, will also increase and keep those skills in high demand.
Finally, there will always be room for quantitative rock stars – people who can think analytically, are comfortable with data extraction, transformation and analysis and have a deep understanding of probabilistic modeling and the tools of that trade. The best safeguard for workers is to take proactive action now to build their skill sets, so they are relevant in the future of work. The way to do this is to join professional organizations to network and seek out mentors, read (or listen) to books, articles or podcasts, and consider taking online classes from providers such as Coursera, Udacity and Udemy.