Anti-patterns in corporate product management that should be avoided

Having worked over 6 years now in large retail corporations as a product manager, thankfully in their digital-first team, I’ve seen a lot of anti-patterns that the newly ordained product managers in big organizations follow. Fortunately, for me, I have the hindsight of working in startups for a good 5 years before, so I think I can be a good judge of these anti-patterns.

And I am by no means excusing myself from having committed some of the sins listed below — and hope, that you too can consider this in good humor.

To keep things light — everything is…

Autosaves are a simple, but an overlooked feature within most of the application design. Modern always-online applications have used the functionality to ensure users don’t lose their work in case of browser exit or unintentional page navigation (more on this later).

When it comes to enterprise solution design, time is money (though you could say the same thing about consumer product design). And in those situations, it becomes imperative that the user is notified when their work is not saved or has changed.

For this article, let’s consider a simple application where a user is performing some CRUD actions. We’ll…

A few weeks back, I was introducing a new product that the development team was to implement… The team was new in the organization, built of mainly fresh developers and a couple of seniors guys — all new to the organization. After I explained the core concept and the philosophy & the vision around the product, the natural expectations of a wall of questions were left unmet.

Instead, I was met with a blank, empty silence that betrayed understanding.

Other PMs in the call were shocked — this was the baby that we conceptualized, won budgets for, and now, the…

Deep dive into what makes a personalization engine work for the end-user and impact of trends, business logic & experimentation

Following part 1, we’ll now look at personalization from both Trends & Business logic perspective and add a flavor of experimentation within the overall personalization context.


Understanding the foundations of Personalization from a end-user view point without the complications of data science

Personalization has been a hot topic for a while now… Various tools exist that can personalize your on-site/on-app/communication to tailor to your customers’ needs. Despite that, excluding the behemoths (FANG), the experience always seems lacking on your second favorite app.

Personalization, unlike other hot-topics of its cader, does not originate from a user need. It was built from a business need — businesses needed more engagement/more conversions/better margins and hence, they decided, albeit logically, that a personalized experience is better than a generic one. …

A simple guide to parallel processing in R for Product Managers

When working with Data Scientists, it sometimes becomes a requirement for product managers to wrangle some of the data — maybe for a quick insight or for presenting the data in a different format. And sometimes, if you have the inclination, you want to run the code yourself!

So, last week, I found myself neck-deep in some data work. It felt very simple at first, but as things progressed, I figured that the code itself was very linear in approach and could do with some parallelism.

Note: This is using R. I have written about parallelism in Python and how…

Data science work doesn’t come in sprints. It is traditionally demand-driven or problem-driven. Problems, as you know, do not come in fixed cycles and mostly, there is an urgency to solve said problem — as the opportunity cost is counted daily (if there is no urgency, you’re not tackling the right problems OR aren’t framing them properly). There have been attempts to sprintify DS work, but it never works. Ask any data scientist what they’re working on, they’ll talk about how the majority of their time goes in ‘cleaning’ the data — a concept, that is not what you think…

Having worked on quite a few apps in the last 10 years, I’ve come to have an understanding of how and where you should do app tracking. App tracking tends to be a pain-point for most product/business teams as the version of truth offered by each tracking tool is different.

To put this all to rest, I’m sharing my understanding of mobile app tracking for retail apps. I’ll be breaking this down into the following sections:

  1. Understanding App Analytics
  2. Choosing your platforms & data strategy
  3. Standard KPIs for App Success
  4. Caveats and tips on tracking

Understanding App Analytics

App tracking serves the following…

What went wrong, and how it could have been better.

From Ars Technica last Wednesday, January 6:
“WhatsApp, the Facebook-owned messenger that claims to have privacy coded into its DNA, is giving its 2 billion plus users an ultimatum: agree to share their personal data with the social network or delete their accounts. The requirement is being delivered through an in-app alert directing users to agree to sweeping changes in the WhatsApp terms of service. Those who don’t accept the revamped privacy policy by February 8 will no longer be able to use the app.”

If you’ve not been living under the proverbial rock for the last few weeks, you…

Facebook’s masterplan to convert the free messaging service into a revenue-generating machine

Do a quick survey — look at everyone around you and see if they have a Whatsapp account that they’ve used today. 99.99% of the time you’ll find that everyone uses Whatsapp. In fact, unless you’re in China or parts of SEA, Whatsapp dominates your countries messenger space:

With a lead in 133 countries, Whatsapp looks ripe for commercialization — something that has already begun with Whatsapp for Business (which had over 300 million users in 2019, and currently, 175 million users each day who message a business account). …

Rameez Kakodker

Simplifying Complexities for a Living |

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