AI Offers Numerous Benefits for Marketing Operations

Ed Breault, VP Marketing and Industry Solutions, AprimoApplications for Artificial Intelligence (AI) and machine learning solutions are no longer confined to a few select beta tests in niche industries. These emerging technologies have matured and are showing great promise for marketing organizations when fully integrated into a technology stack.AI and machine learning applications are conduits for new, real-time data and analysis that marketers can use to gain various insights about customer desires, preferences, and demographics--as well as their own campaign workflows and operational decision-making processes.For example, some marketers are using AI and machine learning applications to administer facial recognition when repeat customers enter a store or restaurant to help expedite their commonly ordered items, or suggest items based on their demographic information. And many brands use AI Chatbots to answer questions and suggest orders for online customers.Further, these emerging technologies can be used to identify and monitor content and campaign metrics to help marketers improve ROI calculations, and expedite their own workflows and decision making.These data-driven capabilities enable marketers to offer enhanced, consistent customer experiences because they’re based on actual, real-time customer information rather than mere predictions based on old data or expectations. They also can offer marketers more accurate, detailed analytics about product and campaign success, which they can bring to the C-suite to help garner executive buy-in for other marketing activities and spend.Additionally, the more data marketers collect via these emerging technologies and progressive use cases, the more difficult it will be to manage on their own. So, they can use the enhanced, inherent AI and machine learning analytical capabilities to make better sense out of these increasing volumes of data.AI use requires cautionMarketers must also be strategic about how they integrate AI and machine learning solutions into their tech stack to ensure they are optimizing the new data they provide—and the investments and resources they require.AI should be used in combination with analytics functionalities within other applications across a marketing tech stack to ensure marketers receive a complete, contextual picture of customer needs and actions. Without such a comprehensive dataset, AI data and analytics on its own can be misleading.Further, marketers should recognize that while AI and machine learning applications continue to become smarter and more complex, they aren’t foolproof. For example, the technologies still can’t fully understand how human emotions, gut reactions, and creativity play into customer decision making. They also run the risk of creating biases for customers based on their demographic information when marketers don’t step in to monitor them.These machines are still “learning.” So, while they are working for you, don’t undervalue using human intelligence in administering them.Marketers need to have some kind of human oversight for their AI and machine learning applications so they can insert common sense into their output and analysis. They also should research how their customers and prospects feel about interacting with such technologies—and create plans to communicate how they will use the data they collect to ensure they are following their customers’ desire for privacy and ethical use of their personal information.The possibilities for AI and machine learning applications in marketing are limitless. But marketers who strategically adopt the emerging solutions as part of a comprehensive tech stack will have the best chance at optimizing their use and ultimately their ROI.