7 Behavioral Tips for Designing the Ideal Customer Experience
Some years back, I booked a trip to Disney World with my family. I remember the advice I received from friends who had already been to the park and were seasoned pros: pack comfortable shoes, as the waiting lines are enormous. And true enough, they were. We had to wait close to two hours for some of the most popular rides.
Funny enough, though, that part of the experience did not weigh down the whole joy of the trip. Funnier still, I’m the kind of person who gets impatient waiting in line at the supermarket for a mere 10 minutes, but the vastly longer waits at Disney World didn’t bother me at all. Why not? Because the customer experience for visitors to the park had been so expertly crafted.
It’s about the journey, not the destination
Every consumer journey is unique. Not only because every organization and every product is, but also because each consumer’s perception is unique. It is fortunate then that the very premise of behavioral science is that some of the idiosyncracies in our perceptions and behavior, as consumers or in other roles, can be largely anticipated on account of systematic cognitive biases and the way our brains function.
This predictability has allowed for the development of models and frameworks that guide the creation of seamless customer journeys. For example, the CHOICE model1 and CHOICES framework2 share a name that serves as an acronym for the different parameters that one should take into account when designing the customer experience. Brands like Disney, Amazon, Netflix, and IKEA, as well as successful franchises like Harry Potter, serve as state-of-the-art applied examples, each in their own context. They represent journeys that customers enjoy retaking over and over again.
How do they do it? What are these parameters that affect the customer experience (CX) and what are some good practices? How can any organization implement these to improve their own CX?
To answer these questions, let’s take a step back and start from the beginning: what do customer journeys consist of?
References
- Clinehens, J. (2020). Choice hacking: How to use psychology and behavioral science to create an experience that sings
- McKinsey’s Behavioral Insight Lab developed the CHOICES framework based on the work of Dan Ariely, Uri Gneezy, Daniel Kahneman, John List, George Lowenstein and Richard Thaler.
- Think with Google (2018). Make it personal: Using marketing personas and empathy in your marketing
- Shiv, B., & Fedorikhin, A. (1999). Heart and Mind in Conflict: The Interplay of Affect and Cognition in Consumer Decision Making. Journal of Consumer Research, 26(3), 278–292.
- Siegel+Gale. World’s simplest brands (2021 results).
- Oosthuizen, Kim & Botha, Dr Elsamari & Robertson, Jeandri & Montecchi, Matteo. (2020). Artificial Intelligence in Retail: The AI-Enabled Value Chain. Australasian Marketing Journal.
- Dooley, R., (2019). Friction: The untapped force that can be your most powerful advantage. McGraw-Hill Education.
- Palmer, M. (2021). What your customer wants and can’t tell you: Unlocking Consumer Brains with the Science of Behavioral Economics. Mango Publishing Group.
- Berman, B. (2005). How to delight your customers. California Management Review, 48(1), 129–151.
- Chubb, H. (2019, June 6). Ed Sheeran teams up with Heinz ketchup to create ‘Edchup.’ People.
- Mazar, N., Plassmann, H., Robitaille, N. & Lindner, A. (2016). Pain of paying? A metaphor gone literal: Evidence from neural and behavioral science. Rotman School of Management Working Paper No. 2901808, INSEAD Working Paper No. 2017/06/MKT.
- Bhattacharjee, D., Gilson, K. & Yeon, H. (2016). Putting behavioral psychology to work to improve the customer experience. McKinsey & Company.
- Graves, P. (2010). Consumer.ology: The market research myth, the truth about consumers, and the psychology of shopping.
About the Author
Melina Moleskis
Dr. Melina Moleskis is the founder of meta-decisions, a consultancy that leverages management science and behavioral economics to help people and organizations make better decisions. Drawing from her dual background in business and academia, she works with determination towards uncovering pragmatic, sustainable solutions that improve performance for clients. Melina is also a visiting Professor of Technology Management as she enjoys spending time in the classroom (teaching as the best route to learning) and is always on the lookout for technology applications in behavioral science. In her prior roles, Melina has served as an economic and business consultant for 7 years in various countries, gaining international experience across industries and the public sector. She holds a PhD in Managerial Decision Science from IESE Business School, MBA in Strategy from NYU Stern and BSc in Mathematics and Economics from London School of Economics.
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