Once upon a time, I dared myself to go on an adventure. No, not mountain climbing or skydiving — it was an adventure into the wild forests of tech ethnography.
My first challenge regarding it? Convincing a room full of engineers that user behavior is more unpredictable than a cat on catnip. Spoiler alert: They were more shocked than a chameleon in a bag of Skittles!
The basics of tech ethnography
Think of tech ethnography as the anthropology of the tech world.
It’s about understanding how real humans — not just data points and thumb clicks — interact with technology in their daily lives. It’s one thing to know that someone clicked a button, but another to understand why they hesitated, smirked, or sighed deeply while doing it. That’s where tech ethnography comes into place!
During my adventures in IT staff augmentation and change management, it all boils down to not just tracking clicks but also deeply understanding human stories, frustrations, and joys.
Now, you might think “Well, technology is logical, and humans… not so much.” And you’d be right!
That’s precisely why tech ethnography is so important in our modern-day digital world. Using tech ethnography, you’re decoding the human element in technology, making products not just functional but intuitive and engaging. Because at the end of the day, even the most brilliant tech solution will flop if it doesn’t resonate with its users.
Digging deeper: User behavior and preferences
If you’ve read something from Simon Sinek, you’ll deeply understand the essence of WHY within people, organizations, and products.
Using tech ethnography, that why becomes even clearer, and deciphering what’s behind that why is a gold mine waiting to be conquered if you’re in the IT world.
The power of preferences
Preferences are like personal fingerprints in the digital world. They vary vastly from person to person, influenced by countless different factors — cultural background, age, tech-savviness, and even mood.
It’s not just about whether users prefer blue over red. It’s about understanding how these preferences shape their interaction with technology, your product, or your solution. The type of questions that uncover these preferences are:
- Does a minimalist design lead to longer engagement?
- Does a certain layout reduce frustration or boost it up?
- Does a more personalized approach enhance user loyalty?
- Does gamification bring a new user base?
The intersection of technology and culture
Tech ethnography tools can be your best friend in the field or they can become your worst enemy. It all depends on how you use them!
Heat maps, eye movement tracking, and A/B testing are some of the tools in your tech ethnography shed you use to gauge reactions to different features. But even they aren’t bulletproof, so when they flop and provide mixed results, good old-fashioned surveys are your greatest user feedback and asset.
Fun Fact: In Japan, there’s a term called “Information Fasting,” where people deliberately take breaks from electronic devices. So, even with the most premium Google-grade A/B testing you do, it won’t help you get the user data you need. Digital detox, anyone?
Case studies and real-world examples
1. Fitness app customization
Everybody likes to feel that pump after a workout, but no one likes to go through training that feels like a one-size-fits-all. That’s why user personalization was a plague that the fitness industry struggled with a lot!
That all changed when FitnessAI came and used AI to create a more personalized user experience with their intelligent training creation. Being a gym rat myself and experiencing this approach, I saw a shift from repetitive, generic training to tailor-made programs that align with my fitness goals.
2. Grocery shopping getting augmented
Marks & Spencer, a British multinational retailer, launched an AR grocery shopping app called “List & Go.”
At the moment, it seemed crazy — Who would want an app that shows them where’s the Apple section? But slowly, the app caught fire! It allows the customers to enter their shopping lists and then guides them through the store with an on-screen path to the products they want to buy with ZERO distractions.
3. Education 2.0 with better adaptive learning
Ecommerce platforms and fitness apps are just a few of many who want a piece of new, better user personalizations, retention, and performance pie. Columbus State Community College also wanted a piece of the game!
They introduced an adaptive learning system in their “Bridge to College Math” course, which uses AI and advanced algorithms. This system was designed to monitor students’ progress in real time and enable instructors to tailor teaching to each student’s individual needs.
It all led to a remarkable boom — From 2012 to 2018, overall course completion among all students rose from 67% to nearly 74%! Moreover, there was a significant increase in semester-to-semester retention rates among black students, from 68% in 2015 to 81% in 2018.
The future of tech ethnography
As time goes on, we’ll see tech ethnography becoming a hot industry, finding new ways how we interact and understand modern tech with trends like:
- Emphasis on ethical data use — As tech ethnography delves deeper into our lives, ensuring privacy and ethical data practices will either make or break the industry.
- Cross-disciplinary approaches – We’ll see an increase in cross-disciplinary methods, blending insights from psychology, sociology, and anthropology to gain a more holistic view of our interactions with technology.
- User-centric design revolution — Products and services will be increasingly tailored to meet the specific needs and preferences of users. Gone will be the days of developing solutions for the masses and large user groups!
- Enhanced integration of AI and machine learning — More sophisticated use of AI and machine learning in tech ethnography is bound to happen. It’s what’ll give a better edge in making more accurate and personalized behavior predictions
- Increased global and cultural perspectives — Tech ethnography will go past the global markets and into the diverse cultural perspectives. This will help in creating universally appealing and culturally sensitive tech solutions that aren’t just there for the market, but for the people who use them.
Conclusion – It’s not just about the user data
Tech ethnography isn’t just about numbers and graphs. It’s about understanding the heartbeat and the human side of tech.
One thing is clear — From personalized fitness apps to adaptive educational platforms, tech ethnography is the key to creating more intuitive, engaging, and effective digital experiences for us — the users. Looking ahead, it’ll start the fusion with AI, ethical data practices, and global perspectives, promising even more exciting user personalization and user data analysis.