5 Ways AI Can Solve a Brand’s Marketing Problems
Harnessing its influence can make it into your company’s superpower
Artificial intelligence and machine learning continue to increase the stakes in the analytic, predictive and executional arms race needed to create and keep customer relationships. Marketing is at the center of this change, and several existing applications promise to irrevocably change the landscape with step-level superpowers.
With great power comes great responsibility, and marketers must be ready to change and adapt to the new landscape if they want to avoid being the haphazard hero who lost the instructions to their supersuit. By recognizing the four ways AI and machine learning will enable change in industries and organizations, the savvy marketer can avoid costly missteps as they learn how to harness the awesome power of an enhanced world.
Follow the money
Chances are you are already using AI and machine learning to buy media. Complex and high value, programmatic media buying is the most mature AI marketing application. eMarketer estimates programmatic will drive $39 billion in total 2018 media spend and almost 80 percent of U.S. display ad traffic. But just as AI and machine learning enable programmatic, they also enable ad fraud, estimated to cost the industry about $19 billion (roughly 20 percent of total spend).
Solutions: New channels and using AI to fight AI
Companies like Uber are using AI to detect subtle patterns in time, location and sequencing to identify and shutdown systematic fraudsters. Look for more tools to help detect and discourage basic click and attribution fraud.
Beyond display, AI and machine learning applications are improving conversion rates in call centers, direct mail, voice assistant and chat by focusing on delivering the right message, in the right channel, at the right time.
Speed up to keep up
AI and machine learning significantly reduce the time to create, deploy, test and revise personalized campaigns at massive scale. This automation pulls team members out of their channel silos, allowing them to focus on products and segments across the lifecycle. As test and learn speeds up, the time required to create, approve and tag content will become the bottleneck for some and competitive advantage for others.
Solutions: Agile and content management
Marketing will need to become faster and break down existing channel-based organizational silos by adopting the Agile methodology or similar approaches.
Consider investing in content workflow software to speed the development and approval process, too. Then expand that to ensure all content is categorized and tagged to support AI-based retrieval, attribution and optimization.
Automated voice and chat marks a significant turning point as AI moves from back-office predictor to frontline transacting and brand voice. While great in theory, brand marketers must manage the increased risk from an out-of-control automated experience by setting clear policies. This is important since branded relationships will become even more necessary to stay top-of-mind when customers order by voice without visual reminders.
Solutions: Define guidelines, have less shelf space and organize new creative types
Define or tighten up policies and guidelines to set parameters for AI, including how and how often AI connects with the prospect/customer. Voice- and logic-based creative will rise in importance with a new place at the table for decision science to optimize the long-tail “choose your own adventure” narrative. And a shift from eyeballs to voice/chat could mean fewer, more curated search options with less shelf space for unfamiliar brands.
Superpowers need data
Personalization and the AI engines behind them require large amounts of data to best optimize outcomes. Beyond cookies and account data, leading brands are in a race to capture and leverage big data as a competitive advantage, with companies like Google, Amazon and Facebook holding many of the cards.
Solutions: Create hit lists, data strategies and opt-in and permissions
Identify a list of highly valuable data points to drive efficient conversions. Develop a comprehensive strategy for collection, storage and retrieval. Because of GDPR, customer opt-in should definitely be part of this hit list.
In the end, you can always ask: Use surveys, feedback forms and sales dialogue to simply ask direct questions on rich topics like motivation, intent and purchase barriers.
While AI and machine learning are an awesome addition to the marketer’s toolkit, it doesn’t replace human storytelling. Since AI can only optimize in the parameters it’s been given, it is not intuition. Applied correctly, however, high-powered optimization provides a significant advantage for marketing teams to understand and engage customers.
Ajay Agrawal says, “The organizations that will benefit most from AI will be the ones that are able to most clearly and accurately specify their objectives.” Be deliberate and focus on minimum viable outcomes in high-value processes.