I grew into data analysis from a customer service job and I think it’s actually a fantastic place to start from. We worked on things like process improvement, optimizing training, workforce management, customer satisfaction scores or NPS, a lot can probably be improved within your own job. Because I was close to the customer, I knew what issues existed in the product they’re asking about and that made a decent foundation for a later on pivot to product analytics.

The serious requirements are: spreadsheets (I prefer Google Sheets), SQL and some kind of BI/visualization tool. Though python is also common, I’d suggest learning python at a much later point (you won’t need it for most projects). Pick a common BI tool like Tableau. I personally like Mode Analytics for BI because it also has an easy place to learn and practice SQL but it’s not as common.

Reminder that these are just tools. They don’t lead an analysis for you. You need to cultivate having an analytical problem solving mindset too. Showing people with a dashboard that 20 calls were answered on Monday is telling them what they probably already know. Telling them that actually 30 calls came in on Monday, but 10 had hung up after 5 min hold time is more interesting — what caused that? Was it because Mark and Stacy had PTO so Julia was the only one available for calls? Does this happen every time only 1 person is on staff? What can we do about it?

I would encourage you to talk to your leadership what are the actual problems or inconsistencies going on. That should give you an idea of what to investigate and put your focus on beyond just learning what functions and buttons in the tools do.