The Product Intern
Lessons learned as the youngest one at a data startup
February 2023, I started working as a product intern at a data startup. Not the usual domain that I prepared for, but little did I know this role would end up teaching me a plethora of skills and savor an experience with the ideal culture any employee could ask for. From learning, to projects, to me going full time, here’s what I learned throughout my journey in 3 short sprints.
The Product On-boarding Plan
The project: create an onboarding plan for yourself, as a new product manager.
The challenge: I haven’t been a product manager before.
The solution, I started looking for it. At first it wasn’t easy, but slowly it started growing on me, this role of being responsible for my own self. The feeling of creative freedom, open acceptance to past knowledge, and an opportunity to put my skills to test, it was the perfect playground for me to put up a great show.
I started digging deeper into the product role and found out the key responsibilities that one should fulfill, according to our organization and the job we do here. Soon I got to know that I’m stuck in a classic case of analysis paralysis. My director got up to me, strung me amidst the team and gave me the motivation to prioritize execution over ideation.
I took it up. Collected data resources from existing product documentation, picked up the most cherishing TED talks that helped me shape the thinking of a product manager, added activities and frameworks that help functioning in the domain an soon I had a solid Plan of Action. Hooked it up, finalized the context, added the fillers and the project went to review.
I was skeptical to see how this new approach with a TED talk filled onboarding plan would turn out, but so it happens, the Product Director loved the plan! It was a fresh perspective presented in a cohesive manner with videos he used to learn from, while working as a Product Manager.
Would like to thank my managers back then, Shubhanshu Jain (Director of Product) and Manish Agrawal (Head of Curriculum) for giving me the freedom and opportunity to think bigger. Great folks working with data, leaving their LinkedIns here, do connect they’ll be more than willing to help someone with potential and passion.
Lesson Learned: Take the risk, think from user perspective, execute ASAP.
The Data Digging
The project: Identify the popular data tools used by our competition
The challenge: 200 companies across 15 categories in 3 days
The idea was to find out the most used tools from a plethora of information available on online tools. We used a tool called zoominfo for filtering out the categories, but still going through each one of them was a hassle, not because we wanted to, but we wanted to do this operation with minimal investment. But the numbers and expectations were steep.
The ask was to identify some popular tools that are common across these 15 categories. It would give us an idea of what our prospects are using, and what features would be key while building a story around these data tools while creating pitching decks, product offerings, and product dashboards.
It was manual effort as I had to do the data analysis, tried developing a python code, but the end goal would not be fulfilled if a machine did the job, and this is where I realised the value of a human v/s AI. The person hired for a job holds accountability for the project which a trained AI model doesn’t, well until it is designed for a specific job. So I did it.
Insights: Identified around 20 focal competitor data tools
Efficiency: 67 companies per day, 8 companies per hour (average)
Learnings: Smart work > Hard work, Value > Effort, Time > Money
The Data Migration
The project: Move product docs from notion to VScode using MKdocs
The challenge: Edit 200+ pages for syntax, naming, and appropriate file path
A high value generating project, that would help the organization release the product documentation to general public with multiple benefits. This would help our prospects look at our product architecture, find solution to their problem, and understand the data-first approach our product brings to the table.
I started learning the markdown format as Notion exports files in this editable format. Next was to get handy with Visual Studio Code. The problem came in when the documentation team started editing and updating documentation content while it was being edited in markdown for the migration. In comes Bitbucket for version controlling.
Using these tools with flexibility took time, to adapt, learn, and to create a smooth workflow that suits everyone’s usability. The absolute pain point was to sort folders and their images with relative path instead of the actual path, with renaming all files to lowercase and also checking all images for alignment and auto adjustable size. The headings needed to be re-done, and finally the glitches Notion throws while exporting files (like popping multiple * entries ahead of headings or bold words) must be eradicated.
The job was to be finished in a month, I did this in 11 days. Created a python code that automatically renames all files, handles the heading sizes, and also removes irrelevant * additions. The custom code runs with zero errors and could be used by anyone in the team to sort future coming pages from Notion to markdown.
Lesson learned: Up-skill for efficiency, code to delegate, deliver finished products.
Completed 3 projects in 3 months as a Product Intern at The Modern Data Company. It helped me prove my willingness and skill-set for working in a fast paced innovation oriented environment and match the thinking of fellow data geeks with ease and efficiency.
Working at a startup helped me realize 3 big things:
- A solution oriented mindset sets you up for a better tomorrow.
- Initial growth is knowledge, financial growth comes naturally after.
- Value wins over effort every-time, it is the value that is compensated.
This role helped me advance as a Product Analyst in the company, and earned me a seat at the table to learn and work alongside great minds reshaping the data space. Coming ahead is my journey as an analyst.
Stay tuned. Connect with me on LinkedIn and Twitter for quick data bites.
