While AI is still in the early stages of deployment for most of these marketers, it is high on their agendas, and they are actively figuring out their next steps.
Marketers at the roundtable -- hosted by Oracle's Data Cloud VP of marketing and partner solutions, Cory Treffiletti, and Digital Ascendant’s CEO and founder, Susan MacDermid -- ranged from B2C businesses such as banks and retailers to B2B organizations selling enterprise technology, data, and processing hardware.
Because this forum promised a private discussion for marketers to share their experiences, I am not attaching names to comments, but providing an overview of how the discussion played out.
Conversations among marketers can be useful in generating different perspectives, and this discussion did not disappoint. I was reminded of the Indian fable in which six blind men discover an elephant and try to describe the animal based on which part they have encountered. The first, holding the elephant’s trunk, says, “The elephant is very much like a snake,” while another who touches the leg says, “No, it’s more like the trunk of a tree” — and so on. The point of the story is that the elephant is something much larger and different than each of its collective parts, which takes further discovery to understand.
Like the elephant, AI is big -- much bigger than most people realize –- and its various parts will come together in a holistic way that eventually will make sense in the marketing process. But marketers typically tackle one new thing at a time, so they seek to identify the most meaningful way AI can be used in the short term to improve business, and will work their way up to incorporating more. This is the natural order of technology adoption, and it doesn’t happen overnight.
It was interesting to hear about the different paths each marketer planned as their first foray into AI. The B2C marketers seemed inclined to view AI first as an extension of customer service, and several were making plans to use chatbots to provide Web site assistance, answering frequently asked questions such as “Where is my order?” Marketers agreed that AI would help to elevate best practices in customer service, but there was some skepticism that significant ROI would result.
Discussion turned to ways AI could make a giant impact on revenues if applied to the core business model. An example of this thinking: Stitchfix.com is a retail disrupter that provides an AI-based personal shopping service. This approach leverages data along with user preferences to provide product recommendations that become more relevant over time. This led to a discussion of how consumers will increasingly expect services that understand them and predict their likes and dislikes, providing a friction-free environment that anticipates wants and needs.
A prominent B2B marketer countered that chatbots were well down his list of marketing initiatives, as he does not believe they will move the needle for his business in the near term. When he thinks of AI, his interest lies in using advanced algorithms that tap new data sets to achieve breakthrough results. The big question in his mind was, “How can I be sure the data is of a high quality?” (By the way, Mike Azzara wrote a column earlier this month about an AI-based data access platform called Narrative.io that will help answer this kind of question.)
Another B2B marketer said that his company’s key to survival will be in collecting and making sense of data. We touched on myriad ways AI will leverage data to make faster and more efficient decisions, including the prediction of “next best customer,” omnichannel targeting, dynamic creative delivery, etc -- all ways to better target and recognize customers with relevant messaging and content.
Most in the room felt the need for a different mix of talent. At least one progressive marketer had reorganized the marketing function at her company to include more data scientists, in order to implement the company’s “personalization engine,” which gathers and uses data to understand and communicate with customers and prospects.
There was some futuristic discussion of the question: “How much will machines eventually do, versus us and our agencies?” This was a humorous conversation with serious reality behind it -- not the first time I’ve heard it, either. Machines are handling more and more jobs, and currently, no one knows exactly what machines won’t be able to do. If you don’t believe me, check out Albert.ai, an autonomous media buying platform that requires little to no human interaction.
Most hang on to the belief that creativity and ideas are still the human domain, and that someone will need to drive the AI bus.
As ever with this type of conversation, people came away with valuable ideas and motivation to keep moving on their AI strategies. The elephant in the room was that AI is much bigger than any of our specific linear areas of interest — and we know it.