Hiring Product Managers

At Cleartrip I was involved in hiring more than 80% of all PMs who’ve worked there in the last 4-5 years. Along the way, I developed some personal heuristics on what to look for to predict success in the PM role. This is my personal approach. And this, of course, varies depending on how the PM role is defined within an organisation.

Personally I think PMs should be responsible for an entire “flow”. As they grow, the number of such “flows” in their portfolio will also grow. Without this approach, there isn’t an end-to-end view of the customer. Which inevitably will lead to worse solutions. This means the way you evaluate a candidate also needs to adapt to this goal. So, here are the parameters that I evaluate when hiring PMs.


Knows what they have done and why. This is what I focus on in the first interaction. CVs are a good elimination tool, but almost always inflated. So, the idea is to go deep into what the candidate has done in their career and understand if they know the why. It is surprising how many with very strong CVs fall at this stage.

Comfort with data. Comfort with data is super important. Analyzing metric changes and having an intuition on the right metrics to track is critical for PMs. It is important to breakdown the problem before diving into what the problems might be. For example, I could ask — “conversion for the hotel funnel is down by 10%, what went wrong”. I am not really looking for what went wrong, but the journey she takes.

Product thinking. After data, is an evaluation of product thinking. This will typically involve discussing a product that is live or being built or something that we have been thinking about. What I am looking for is the ability to think about user problems, jobs to do for users and constraints. What gets built is the last thing I want to discuss.

Spikes and new learnings. This is a bit subjective. Here I am looking for things that we may not have thought about internally or something that is difficult for someone from a different domain to know. You will know when you spot this. This is strictly not a necessary factor. But helps with making the final decision.

Ability to work with others. There’s no PM who works alone. How do they deal with conflicts with engineering and design teams? How good is the quality of requirements they produce? Without good requirements, engineering and design teams will end up working with ambiguity. And that’s not good. I will typically ask the candidate to structure a requirement document to evaluate this.

Complement yourself. No individual is good at everything. But the team should be. Look out for skills where the candidate can add value where it is currently missing. This could be anything from marketing skills, design chops to experience working with customer support. It’s unique to every team. Decide accordingly.


This is a framework I follow. I may end up overindexing on one of these depending on the role I am hiring for and the candidates’ past experience.

Principles for Managing Teams

I have recruited and developed a team of high-performing product managers in the last few years. In terms of mentoring them to grow there are a set of principles, I try to stick to. This has evolved in the last 3–4 years. I am sure this will evolve in the future as well.


  1. To scale as a product leader, delegate and trust your team. If you cannot, you did a bad job of hiring. Take your time to build the right team. Spending time before a hire is better than after.
  2. “It doesn’t make sense to hire smart people and tell them what to do; we hire smart people so they can tell us what to do.” — Steve Jobs
  3. Define clear responsibilities, goals and expectations, then get out of the way and let them do their job. Give freedom and protection.
  4. Be available always to guide and mentor them. Give feedback along the way — don’t wait for formal reviews.
  5. Dedicate time every week to discuss their week, guide them, brainstorm with them, set expectations and inspire them.
  6. Make being redundant your goal. If you are no longer needed for what the team is responsible for, you have done great. This frees up your time to focus on other things to push the business forward.
  7. Think of your team’s future, their growth. Work towards that — with them and in the background.
  8. Work to increase their visibility in the organisation.
  9. Take the fall for them and protect them from the rest of the organisation. But show them the right path to help them improve.
  10. Be honest and brutal with your feedback if they are off-track. But be clear with examples, expectations and a path to improvement.

In a follow-up to this I will write down differences in my approach to individuals in the team. 

Simplifying Product Complexity

Over the last decade, I have been involved in building hundreds of features. Sometimes to add customer value. At other times to improve internal efficiencies. And many other reasons. The challenge has always been simplifying the solution. It is to find the sweet spot between the complexity of the build vs likelihood of risk or reward.

I started off loving the complex solutions. But have wisened up since then. Here’s how I approach this today.


Start with the problem. Think about the ideal solution that solves the problem completely for your customers. This is likely going to be complex and convoluted to build. (Which means you’ll be slower to market and, hence, slower is validating your hypotheses behind solving the problem in the first place.)

Now evaluate the impact of solving the problem. What’s the outcome going to be? For your customer. For you. What’s the likelihood of that outcome?

Now take a step back and question the solution. Does it need to be as complex? How much can you remove and reduce without reducing the benefits so much that the outcome is no longer useful — for your customers and/or for you?

This step is recursive as you keep simplifying. Where you stop is determined by when:

  1. The outcome is likely to be no longer useful for your customers.
  2. The outcome is likely to be no longer useful for you.
  3. You can’t measure (1) or (2) by simplifying any further.

What remains is something that is probably good enough to be of value to both your customers and you. (This is a simplification of explaining simplification.)


Few examples of simplification I have used in the past.

  • Use a static CSV or JSON instead of an interface.
  • Hardcoding works. (If you can convince your engineering team.)
  • Assume defaults — remove choices and inputs.
  • Use rules instead of fancy algorithms.
  • Discrete selections instead of open-ended inputs (aka chat-bot).
  • Human-powered processes instead of tech solutions.

The goal is not to create fancy tech. It is to solve a problem that your customers value. Bring in the tech once the hypotheses are validated and you need to scale.

Building Mobile Apps

Owning Cleartrip’s mobile apps between 2014–16 was one of the most satisfying assignments I worked on. It was the beginning of the mobile growth years in India. We had the opportunity to shape the direction of the product. The team’s effort improved most metrics. There was external recognition as well. The app was selected Editor’s Choice on both App Store and Play Store in this period and won a few product-design awards as well.

The success of the mobile platform also gave me the opportunity to be part of public discourse on mobile growth in India. Here are some mobile app development principles I had put together for a presentation during that time. Much of it is still valid.


  • It is still difficult to tap, type, correct and read on a mobile screen. Reduce and remove friction for these actions.
  • Reduce the number of taps required to reach a goal. Provide recommended starting points, combine actions to reduce clicks, ask for as few details as possible.
  • Reduce duplication, make it easy to find again. Remember recent and past actions, repeating inputs and “what I’ve already seen”.
  • Anticipate user needs and intervene. Assisted filters, fuzzy search and real-time input validation reduce stress.
  • Make it easy to assimilate information. Solve for aggregate (result-set grouping) as well as specific information (result metadata). Progressively disclose details.
  • Gracefully handle errors — ”What did I do wrong? What are the consequences? What should I do now?” Switching context to Google for solutions is stressful.
  • Solve for the journey; not the stop. Engagement brings users back. When users come back, trust increases. Increase in trust leads to (repeated) conversion(s).
  • What does a customer lose by leaving? What does a customer gain by staying? These are the best use-cases.
  • The best use-cases decay slower than others increasing retention. Encourage and guide users to these use cases.
  • Solve for mobility. Use device capabilities, solve mobile specific use cases (eg. near me, right now, share). But respect the physical limitations of the device — display, storage, bandwidth, battery. [1]
  • Respect the platform. Use first-party patterns where available. Don’t port patterns across platforms.

[1] This is one aspect where things have changed significantly in the last 2 years. Most of these aren’t practical limitations any more. But that is no reason to be complacent. Behaviour (eg. concern about app size) is hard to change.