Data Science: Why I care as a CX/UX professional
I always was a data-driven customer/user experience professional, but in Sommer 2018 I decided to take the leap. With my newborn little girl, which was lying on the couch next to me, I subscribed to the “Data Science with Python” career track at DataCamp: Statistics, data extraction, transformation and loading, data wrangling and data exploration, but especially machine (deep) learning algorithms, big data processing, and of course data visualization.
I was very interested in this stuff and how it links to artificial intelligence. And to be honest, I always was very impressed and a bit envious of my colleagues from the Data Science department at HolidayCheck. Will I ever play in the same league? Haha! Most probably not! But the course helped me to grasp the concepts behind and taught me enough do make my point if needed.
Today I could read why this was a seemingly good decision.
The real power of transformational customer experience is a combination of Artificial and Human Intelligence. AI will suggest actions based on customer feedback, which employees can evaluate to implement the best ideas. Companies in 2020 will look to these techniques in order to repurpose the time and energy traditionally spent on manual analysis to make near-real-time decisions that improve CX and the bottom line.
I used my new skills back in 2018 exactly for this scenario! By loading lots of raw Google Analytics Data via BigQuery and set up a rudimentary network analysis I was able to inspect the most important page paths through the HolidayCheck world. Finally, I teamed up with my colleague Robert from the Data Science department – thanks again, Robert – to work on my idea to quantize our customer journey. But that is another story.
And there is even more to read!
Artificial intelligence (AI), backed by an alphabet soup of groundbreaking technologies, is at the heart of what amounts to a customer and employee experience revolution. Combine them together, and the possibilities are endless.
To be clear, it’s the combination of technologies like machine learning, natural language processing (NLP), and robotics that lets companies, (in Gartner’s words), “industrialize the digital customer and employee experience by connecting those interactions directly to automated back-office operations and supplier ecosystems.” This kind of intelligence is based on an understanding of the context of what’s going on, allowing the company to continuously adapt “in real-time” interactions with customers and partners based on business goals.
On top of that, there is another layer on how to use Data Science skills as a CX/UX professional: Business!
Measuring success and proving the impact of your team’s efforts!
One of the keys to sustaining attention from leaders and collaboration from peers is to make CX matter in terms of the results that are important to them. Prove how satisfied customers drive up revenue, lower churn, reduce costs and grow the business by combining customer satisfaction data with the transaction and operational data.
How do you think about augmenting your CX/UX skills with a breeze of Data Science? If you wanna give it a try and invest in yourself, DataCamp is the place to be. So try it out! By the way, my Data Science programming language of choice is Python.
I’ll get some money from DataCamp if you use the button above, but I would highly recommend them also without! If you have any questions – you are welcome all the time! And of course, by sharing this article you will support me a lot spreading the word.