Hello Folks! Welcome back to our weekly AMA series. This week we got an opportunity to interact with Deepak Singh, Senior Director of Products at Unacademy. 

Deepak has built 0 to 1 as well as products at scale (>50 million DAU). He has even built games, videos, gamification, edtech, classifieds, & data science products. Deepak shares interest in growth which is depicted by the fact that he runs a blog called Growth Catalyst. He led Voice Search and Assistant AI products for Flipkart and has also written a book for non-techies in PM roles.

In this AMA, Abhishek shared insights about key Product Management skills for entry level PMs. He also shared about some important PM tools and essentials for finding the right culture fit. 

So let's jump straight into it!

How critical is the knowledge of tech in depth to a PM?

The knowledge of tech is often debated for PMs. The reason is that we have seen great PMs who don't have a tech background.

But all of these PMs actually learned tech on the go. Not coding - that is different. But understanding the logic in tech - like why would something take more time. Or what APIs, BE, FE, SDKs, etc mean.

So to be a great PM, you need to understand the basics of tech but don't need to code. Over time, you are expected to understand technical system design and devops to be a good product leader.

Could you share your favourite resources that would add a lot of value to someone who wants to learn more about Design, Video products & Gamification?

To enhance knowledge, here is what Deepak recommends to you-

• Design: read and re-read 'the design of everyday things, and 'don't make me think'. Keep checking the top apps on the play store and competitor apps.
• Video products: read Mathew ball articles to start with. Read the Netflix tech blog, it's really good. Also, read the commentary around Tiktok vs FB.
• Gamification: 'The Art of Game Design'. book, Octalysis Framework, and commentary on how PinDuoDuo gamified commerce in China

Which language do you suggest a PM should have a good hold of when it comes to interacting with Data science teams and Engineering? If Language is not required, what should I be looking to improve on?

To improve in data science, don't look at learning a language. Do the course on Machine Learning by Andrew NG. It's possibly the most popular course on Coursera and the best one till date. While doing the course, focus on theory and why certain algorithms work and others don't. No need to do exercises except conceptual ones.

How does one's responsibilities change as they move up the ladder in Product Management? (From an APM -> PM -> SPM and so on)

At an APM/PM level, you are expected to learn flawless execution, basically get things done. At an SPM level, you are also expected to hold conversations with different teams like marketing, business, etc., and find the best solution. This also means that you can start taking initiatives and thinking about strategy a little bit.

What would you say was your biggest learning when writing your book?

My biggest learning while writing the book was that if we build products the right way without giving in to shortcuts or short term rewards, we would be able to build something meaningful. “Having that long term view in mind makes a lot of difference between a good and a great outcome.”

What advice would you give to someone starting his career in product management for the first 90 days?

Here are the things to remember in your first 90 days and more

1. Have 1:1 with all team members including designers and developers. Understand what you can do to make their life easier.
2. Understand how the current product works from a user flow and technical perspective
3. Schedule regular 1:1 meets with your manager on a weekly basis. keep asking for advice to improve upon and show progress on areas of improvement
4. Remember that things will go south every once in a while. Don't react to it, work upon it and just move on. In the long run, no one will remember that including you.

What are some good retention and engagement metrics to track for an Edtech product?

Define what an ideal usage of the product looks like, and that would tell you the right metrics. Some of the ones that are definitely useful:

• Daily Active Users (DAU)
• Stickiness= DAU/WAU or DAU/MAU
• Total time spent per paying user
• W1 Retention of New Users

It's a long and hard path to figure out what will move these metrics. I have succeeded in some places and I have failed in others. I can suggest you start at activation (aha-moment) because that has a cascading effect on retention. If you need to learn how to improve activation, I wrote a series of posts on onboarding and activation at growth catalyst. You can also refer to Reforge articles around these.

How do you view the role of a Product Analyst and how is that different from a PM position?

A product analyst is supposed to figure out what is wrong (funnel, cohort, segment, etc) and highlight that to the team. Every once in a while, they will also do an analysis to understand why something is wrong, like why conversion is low, or revenue has dipped.

A PM is supposed to figure out what is wrong, why it's wrong. (through data and user interviews), and how to fix it. This is beyond their usual role to move metrics by building new things :)

Which industries do you feel needs PMs who are more analytically inclined & Data-oriented?

Usually, all companies need data inclined PMs. The rigour is higher in industries that generate a lot of data and engagement. Examples are Facebook, gaming apps, video and music apps, etc. That is the reason you see FB or Google taking an analytical round in their PM interviews. 

Another thing is how far are you from consumers and how diverse is your consumer base. For example, enterprise software doesn't need very data-driven PMs because they keep talking to their consumers, and also address a niche segment most of the time. So to sum it up, scale, diversity, and closeness to consumers determine data intensiveness.

What is the advice you have for having an effective 1:1 with your manager?

Always take 15-30 mins to be prepared for pointers of discussion. This is most important. Updates, open questions, and seeking feedback are three things you can start with.

What are your favourite blogs/newsletters to read?

My favourite blogs/newsletters to read are-

1. Stratechery by Ben Thompson
2. Lenny's newsletter
3. Mathew ball blog on games and videos
4. Not boring by Packy M
5. Shreyas Doshi’s Tweets
6. Every.to section on product strategy