Artificial intelligence-driven automation of human jobs has been a widely discussed topic for the last ten years.
While factory employees and other manual workers may have accepted their fate to be laid off, most white-collar workers with creative functions have the assurance of more time.
However, Kai-Fu Lee, Google’s ex-president, recently forecasted that AI will soon do away with one-half of all jobs and that the white-collar jobs would be the first to disappear.
The application of machine learning AI has been the main cause of disruption in marketing. This technology can learn and become better at its work by being trained using huge datasets of information.
The ironic bit is that the same technology that is currently causing humans to be laid off was designed based on the functions of the human brain.
Smart marketing applications currently in use are not new. For instance, Facebook has been utilizing machine-learning algorithms to undertake targeted advertising for a long time.
Even so, Gartner forecasts that 20% of the entire business advertising content is currently being written by smart machines.
As AI continues to get smarter with each passing day, what lessons can humans take away from machine learning marketing algorithms in a bid to remain relevant?
- Grow Naturally by Staying abreast of Technological Trends
Machine learning algorithms can adapt, evolve and make autonomous decisions, without having to be programmed.
In an era where technologies and trends are changing rapidly, creative teams require not only to adopt this level of productivity but also stay updated about technological advances and developments in their industry.
Advertising appears to be shifting away from TV and print. As such, human marketing teams require keeping themselves informed about where their target audience spends most of its time.
- Concentrate on Developing Creative Campaigns that are more Real-time and Relevant
In the current digital age, staying up to date with consumer trends can be challenging. Therefore, as a market, you need to know what’s ideal and what’s not for all the different target groups in real-time.
The takeaway lesson from machine learning AI is the need to be relevant and evaluate trends in real-time.
For human marketing teams to remain competitive, they have to become increasingly data-driven and look for a way to expedite creative projects that appeal to their target audience, especially on a personal level.
- Make use of Historical Data
Gaining access to massive sets of proprietary data to help train algorithms is among the main hurdles affecting the implementation of machine-learning applications. Machine learning algorithms use huge volumes of data to learn and grow.
With this in mind, marketing teams need to take advantage of the available historical data in an attempt to learn from past campaigns and boost future processes.
Each marketing campaign ought to provide a wide array of important data resources in terms of likes and share on social media platforms as well as media and content that resonate well with different demographics.
Instead of moving straight to the next marketing campaign, marketing teams should go through the previous campaign’s results to spot useful ideas that they could use to improve their next project.