What's your AIQ (artificial intelligence quotient)?
For many marketers today, it’s likely pretty low because they haven’t yet acquired skills needed to exploit AI for marketing efforts. A first step is understanding the various AI approaches that currently fall under the artificial intelligence umbrella. It’s also crucial to understand what activities machines are better at than humans.
A good rule of thumb is to use machine learning and other AI capabilities to automate what tasks people do versus how people think.
Manual, complex tasks siphon marketers’ time away from more strategic and fruitful priorities. AI marketing can speed up important tasks such as integrating data sources, creating segments and rules, designing tests, etc. AI can also help marketers automatically discover and generate thousands of discrete segments –instead of hundreds – to evaluate campaign treatments much faster.
AI can also help marketers efficiently sort through vast amounts of customer, operational and campaign performance data to optimize offers and personalize campaigns for customers based on their customer-service interactions, in-store behavior, or mobile app use.
A higher AIQ reduces disparity in your customers’ minds about competing brand choices – because it can help you create a unique brand experience that can’t be duplicated easily by any of your competitors. Wilson Raj SAS
Humans and machines: Complementary, not competitive
Humans are still unique in their ability to “think meta” – that is, to think outside the immediate scope of a task or problem with creativity and judgment. They can also bring a range of emotional sensitivity to craft messages, shape branding and construct symbols that appeal to and resonate with human aspirations and needs.
Machines can’t yet do that well. They are great at executing a well-defined task or solving a well-defined problem. But they can’t pose new hypotheses or questions or connect a situation to one that they haven’t faced previously.
The upshot? AI technology and machines can galvanize humans to create new ideas, challenge their own biases and reframe their perspectives. Conversely, humans must interpret the outputs and actions of machines in a much broader context – emotional, social, psychological – and use their judgment to guide machines to increasingly more relevant analyses.
AI helps human creativity; human creativity makes AI more useful.
The AIQ skillset
This begs the question: What kinds of skills will marketers need to work with AI and machines?
First, let’s be clear: AI is complementary to marketers’ skills, processes and technology investments. It will not replace marketers.
AI provides the tremendous speed and scale brands need to keep pace with escalating customer demands, the deluge of data and content, and innumerable customer journey permutations. AI also aligns with B2B and B2C marketers’ fundamental priorities to make customer engagement more timely, personalized and results-driven.
Marketers must have a foundational understanding of the underlying data behind the automation and AI functions – data literacy is crucial for marketers. Marketers across the board must know how their data is captured, what they want to get out of that data, how to interpret analytic outputs, and finally, how to connect them to meaningful operations across their company.
Three ways you can apply your AIQ
Here are three scenarios where AI gives marketers an edge now and in the future.
- Marketers can offload cumbersome processes such as evaluating campaign results, making necessary budget adjustments and calling their agencies or marketing partners to authorize changes. In a fluid, real-time world, such lags can affect customer experience and the bottom line. With AI, marketers can set up rules to automatically increase spending under high-demand conditions and drop spending if campaign performance softens.
- AI can help marketers with dynamic pricing as it relates to merchandise planning, price optimization and demand forecasting. It’s already happening today, but can go much further. AI could further integrate with the company’s enterprise resource planning (ERP) system and supply chain inputs to access cost, inventory and economic forecasting data to incorporate both dynamic pricing and fulfillment into campaigns and customer interactions.
- AI’s advantage is the built-in ability to aggregate data from a broad range of customer, behavioral, operational and content sources – at scale and in real time. Expect more AI-powered marketing systems that will directly access or accept these data types and associated metadata from systems such as content management systems, data management platforms and digital asset management systems. We’ll also see AI automatically enriching these data feeds with more third-party data, social media data, app data, public sources, partner databases and IoT data.
Boosting a marketer’s AIQ can result in a dramatic improvement for prospects and customers, realized by unlocking the full strategic value of your data. Your organization can move from basic reporting to predictive analytics, and eventually to transformative analytics. A higher AIQ reduces disparity in your customers’ minds about competing brand choices – because it can help you create a unique brand experience that can’t be duplicated easily by any of your competitors.
- Article Customer loyalty in a digital world: A new approachCustomer loyalty offers a good news/bad news message. Loyalty programs are on the rise. Bad news? About 60 percent of your customer don't belong. Here are some ways to attract and retain the best customers.
- Article Marketing measurement do's and don'tsHow can marketers capture the C-suite's attention? Draw a clear line between marketing activities and results.
- Know your data, know your customersIn the digital world, customers expect to be known as individuals with distinct preferences, not just as one member of a segment. Learn how to start with analytics.
- Article Empty shelves: The retail analytical talent deficitIf you already have an analytics team, you know how hard it is to attract and retain top talent. If you're trying to build a team, here are some ways to find (and keep) the analytical experts you need.