I love marketing. I find it to be a fascinating intersection of creativity and business savvy, and it has been an area where creative people have worked and thrived.
However, as Bob Dylan sang, ‘the times, they are a-changing.' Digital channels now require and provide vast volumes of information. To optimize the efficiency of the marketing efforts, marketing organizations are required to collect a lot of data about the customer behavior and how they interact with the marketing content. Marketers also need more content to be produced and disseminated to an increasing number channels.
It is difficult to create, manage, analyze, and optimize huge amounts of content manually. It can’t be done using creativity alone. Even the best analytics tools and content management systems cannot help an organization to make the right decisions at the speed of digital—at least not manually. Not only does Web and eCommerce personalization require super-fast number crunching to present the right message in real time, but also significant amounts of granular product information are needed to put the product story together.
Not even with an army of super creative marketers would it be possible to do this manually. Customers require relevant results in real time. It also becomes increasingly difficult to manually produce all the content that is needed to put the right message together for your individual customers, at all touchpoints, for all stages in the buying journey. When you add the requisite analysis and optimization it to the mix, you will find that a new breed of solutions is needed.
Enter Artificial Intelligence (AI) and Machine Learning (ML) to save the day.
How can AI and ML help?
AI can be used to make split-second decisions. Combined with ML, AI can learn how to make better decisions over time. AI can also adapt to changes in buying behavior long before any human has had time to put a report together, analyze it, test a new idea, and iterate until it works. Most of us interact with AI- and ML-powered behavioral recommendation engines every time we shop at Amazon and many other retailers’ sites. AI controls product recommendations, provides optimized guided navigation, and adds inspirational suggestions, all based on customers’ behavioral patterns and buying habits.
This development changes the role of the marketer. AI and ML will take care of most of the merchandising—automatically and in real-time. But a behavioral merchandizing engine needs fuel, a lot of it. This fuel comes in the form of large volumes of high-quality, granular product information. In addition, to be efficient, AI also requires the right content to create a relevant, personalized and compelling product story.