Tech for Product managers

Lots of PM interviews will cover Tech questions so you can easily read the listed one to your heart’s content before attending an PM Tech interview. This also helps the PMs to understand and help the dev team to clear the technical debts/ re-prioritise / clear blockers in the team leading to efficient delivery and release cycles.
Read the end for a Bonus tip!

1. Web hooks

A web hook is a way for an app to provide other applications with real-time information. A web hook delivers data to other applications as it happens, meaning you get data immediately.

Unlike typical APIs where you would need to poll for data very frequently in order to get it real-time. This makes web hooks much more efficient for both provider and consumer. The only drawback to web hooks is the difficulty of initially setting them up.

Other names — Web callback , HTTP push API, Reverse APIs. Examples:

• SendGrid — Deliver event data and even parse emails through our web hooks.
• Twilio — Twilio both delivers and reacts to phone calls and text messages using web hooks.
• Github — Github updates applications about repositories and actions taken upon them through web hooks.
• Foursquare — Foursquare notifies applications when users checkin using their web hook.

__________________________________________________________________

2. Data science

Data science is the study of data. It involves developing methods of recording, storing, and analysing data to effectively extract useful information. The goal of data science is to gain insights and knowledge from any type of data — both structured and unstructured. Data science covers the entire scope of data collection and processing.

_________________________________________________________________

3. Data mining
Data mining is a subset of data science. It involves analysing large amounts of data (such as big data) in order to discover patterns and other useful information.

_________________________________________________________________

4. Big Data

The phrase “big data” is often used in enterprise settings to describe large amounts of data. It does not refer to a specific amount of data, but rather describes a dataset that cannot be stored or processed using traditional database software.

Examples of big data include the Google search index, the database of Facebook user profiles, and Amazon.com’s product list. These collections of data (or “datasets”) are so large that the data cannot be stored in a typical database, or even a single computer.

Some of the most common big data software products include Apache Hadoop, IBM’s Big Data Platform, Oracle NoSQL Database, Microsoft HDInsight, and EMC Pivotal One.

_________________________________________________________________

5. Lazy loading

Lazy loading is a programming technique that delays loading resources until they are needed.

A common example is a webpage that defers loading images until the user scrolls to their location within the page. Lazy loading is used on the web and in software programs, such as mobile and desktop applications.

_________________________________________________________________

6. AWS services

Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.

In aggregate, these cloud computing web services provide a set of primitive abstract technical infrastructure and distributed computing building blocks and tools.

_________________________________________________________________

7. Brute force attack

A brute force attack is an attempt to gain access to a system using successive login attempts. It can be performed manually or by using an automated script. In either case, a brute force attack tries different username and password combinations with the hope of discovering a valid login.

Strong password, Two-factor authentication can protect against Brute Force attacks.

_________________________________________________________________

8. Describe how Product Analytics platforms work. Eg: Amplitude

Product analytics allows companies to fully understand how users engage with what they build. It is especially useful for technology products where teams can track users’ digital footprints step-by-step to see what they like or dislike and what leads them to engage, return, or churn. Product analytics makes that data useful again by integrating all data sources into one single organised view.

_________________________________________________________________

9. What doesn’t get recorded in analytics platforms?

In a gaming app, the users/hackers using App cloner and installing multiple versions of the same app as unique users activity doesn’t get recorded. In casual gaming, usage of parallel space app cannot be detected by analytics unless you track the list of packages used by the user.

No matter what numbers are shown for a particular event/funnel, the real source of truthful numbers can only be given by the backend/Django admin.

Analytics can be error prone and needs manual intervention. Data cannot make every decision; there are some situations where intuition has to take over. Lets consider Netflix for instance, data could not predict that a show like Breaking Bad would be a success. The creator was a former writer on The X-Files, and dramas are 50/50. In these cases, decisions are heavily based on the people and team behind the idea of the show. Whether Netflix can make a successful show like this (one with little to no data) is yet to be seen.

_________________________________________________________________

10. Deeplinking in an Android app

Deep linking is when a link sends users directly into a specific point in the app experience, rather than an external website or app homepage.

For example, if a user searching for a product on a mobile search engine and already has the app installed on their phone, clicking a link will take them directly to that specific product in the app. By removing a step from the transaction process, deep linking helps to maintain user attention and improve conversion rates.

Deep linking is not restricted to mobile websites alone; it can also be used in push notifications and email marketing. This adds value to the notification by providing the user with relevant content and increases conversion rates.

_________________________________________________________________

11. What are Sales/Marketing Funnels

Your sales funnel illustrates the path website visitors take before purchasing items. Understanding your sales funnel can also help you find the holes in the funnel — the places where visitors drop out and never convert. Funnels are specific, targeted, and specially designed for your target customer.

Awareness, Interest, Decision, and Action. These four stages represent your prospective customer’s mindset. (AIDA)

Eg:

• Retention is your ability to maintain a long-term relationship with your customers. The equation for calculating customer retention:

(# of customers at end of period — # of customers acquired during period) / # of customers at start of period) x 100 = retention rate

• Churn is those users who have stopped any interaction with you. The equation for calculating customer churn:

Customers lost during period / Total number of customers at the start of period) x 100 = customer churn

• According to the research conducted by Price Intelligently, a 1% increase in the retention rate leads to a 7% increase in profits

________________________________________________________________

12. Define a heat map

A heat map is data analysis software that uses colour the way a bar graph uses height and width: as a data visualisation tool. Heat maps are a great way to see through data to trends and understand what to do next.

A heat map uses a warm-to-cool colour spectrum to show you your site analytics, namely which parts of a page receive the most attention. This heat map, for example, shows how far down the page visitors have scrolled. In a mobile app, scroll map can also be used.

_________________________________________________________________

13. How do you measure the impact of a design change?

Make changes, track their impact, and keep optimising until you improve your product, offering, or customer journey. Many companies with technology products simplify this process by using a churn analytics platform which allows them to:

• A/B test offerings and features
• Automatically track customer behaviour
• Define and improve their customer journey
• Provide insights and feedback
• Send alerts and behaviour-based messaging

Churn fixes can be applied at any touchpoint in the customer journey, from how your product or service is built to how it is sold, marketed, and supported. Through extensive testing you’ll hopefully discover your brand’s solution to customer churn so you can improve your growth rates.

_________________________________________________________________

13. Define your Product’s tech stack

Eg: A gaming app

XYZ uses AWS as its infrastructure.
Python, Node.js as backend
Postgres, Reddis, Dynamodb as database
Postgres for User-related information and queries. Reddis and Dynamodb for creating Live quiz contests and Arena tournaments.

Here are some questions to ponder on personally based on the products you’ve worked on.

14. Who are your early users/audience/user demographics look like?

15. Define A/B testing with a scenario you worked on.

16. What opportunities do we have to reduce churn?

P.S. The answers shared are based on various websites, Wikipedia, and few are on personal experiences.

_________________________________________________________________

Bonus Tip: If you are working with a web-based product, use Built With to understand what is powering that specific product. I love this tool because it goes deep into the guts of a product’s tech stack. It’s a great place to explore and find out what new technology is being used.