The Big Mistake People Make with AI
Business leaders of today have to understand the technology of tomorrow. Specifically, one would be wise to understand what AI is, how it works, and what problems it can solve for your business.
This episode of The Intuitive Customer is a conversation with Bikram Ghosh, associate professor of marketing at the Eller College of Management at the University of Arizona, Tucson about AI in business today and what is possible for your business processes.
Ghosh studies AI and its overlap with behavioral economics. He believes that the future of Customer Experience management and the way to foster customer-driven growth is AI, and here’s why:
AI is machine intelligence driven by algorithms. The goal is to mimic the human mind. By taking stimuli from an external environment, called inputs, machines try to predict the outcome.
There are many types of AI.
Machine Learning is a type of AI where machines attempt to learn from their mistakes. We learn from our mistakes; machines seek to do the same thing by making mistakes, recognizing them, sourcing them, and then fixing them moving forward.
Attitudinal Data refers to how customers talk about products on blogs and social media. From attitudinal data, the algorithm can extrapolate behavioral nuances.
Natural Language Processing makes it possible to detect behavioral nuances, and is a significant area of work in Machine Learning.
Computer Vision is when the machine analyzes micro-expressions or picture data to determine how people react to a product of brand. This AI helps companies learn how people react to their product or brand from studying customers’ micro-expressions or from picture data analysis.
AI is great at determining how a large group feels in general, but not individually. Machines are improving in these areas, however. Amazon is working on capturing the data about the nuances of customer emotions.
AI is excellent at categorizing groups. This news is excellent as many organizations do not have sufficient segmentation in their customer groups. The potential for segmenting by customer behavior is a possibility in the near future, which would allow for tracking the dynamic nature of customer actions and emotions.
Ghosh realizes that it can be daunting for people not familiar with AI to dive into the process. However, he offers some practical tips in this area:
- Begin with a form of sentiment analysis. Getting the customer’s emotions allows you group your customers based on how they feel.
- Decide what the appropriate response would be to each group.
- Map the outcome variables for the groups and their responses to design the process.
- Have your AI begin collecting data at every level down to deployment.
- Track your desired data, whether that is pertaining to customer loyalty, behavioral measures, or whatever else you want. Here, I would discover what drives value for each group.
Some additional takeaways are:
- Use AI to help with your categorizing. Solving many problems starts with effective segmentation for improved targeting. Best of all, AI can do thing your human resources cannot—and faster, too.
- Do not use AI at activities that require creativity, judgment, and decision making. That’s where humans come in.
- Think of AI as complementary to human work. Ghosh recommends that you find parts of your business process that are repetitive or physical that you can automate with AI.
- Remember you only have to understand what it can do; you don’t have to program it. Most of us can’t anyway. You hire people to do the programming. Your job is to determine what part of the process you can have them program.
- Educating the team about how customer behavior is affected by emotions is essential. Helping people in your organization understand the importance of the emotional experience and how AI can help improve it, is critical as we move forward to the Customer Experiences of the future.
To discuss this further contact us at www.BeyondPhilosophy.com
About Beyond Philosophy:
Beyond Philosophy help organizations unlock growth by discovering customers’ hidden, unmet needs that drive value ($). We then capitalize on this by improving your customer experience to meet these needs thereby retaining and acquiring new customers across the market.