TechExec 6: Product Market Fit, the Monkey Trap and Recommender Systems

(Total read time: 6 minutes)

Hey there,

Welcome to the 6th edition of TechExec - the newsletter that turbocharges your growth to become a Tech Executive!

First of all, thanks so much for your birthday wishes. That was very heart-warming and I hope that you keep finding this newsletter valuable.

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Now to the main content …

As promised, here are this week’s BLTs:

💼 B - a Business concept/theory/story

💝 L - a lifestyle advice

🤖 T - a Tech explainer

💼 B - Product Market Fit

Product-Market Fit (PMF) is the most sacred yet overused term in the world of entrepreneurship. It is nirvana for early-stage startups. But a significant number of them are delusional about it. Either they think they have achieved PMF when they haven’t, or they are focusing on the wrong stuff to get there. So, what exactly is PMF, and why does it matter? Let’s dive into it:

Achieving Product Market Fit means that your product or service is solving a real problem for your target market, and they are willing to pay for it. PMF was coined by legendary investor, Marc Andreessen, the founder of Andreessen Horowitz and the bearer of an 🥚-shaped head.

Ignoring his head shape for a moment, Andreessen described PMF as

Profound indeed! But how do you know if you have achieved product market fit?

One way to know if you have achieved product-market fit is by looking at your customer base. Are they consistently using your product or service? Are they recommending it to others? If the answer is yes, then you're on the right track.

Another way to know if you have achieved product market fit is by analyzing your sales data. Are you seeing consistent growth 📈 in revenue and customer acquisition? If so, then you're likely delivering value that your target market is willing to pay for.

A more technical and efficient way was suggested by famed entrepreneur and marketer Sean Ellis. He suggests that companies ask the following question to all of their customers:

If the answer is “very disappointed” more than 40% of the time, then well-done to you; that means you have the product/market fit.

Now that we know what PMF looks like, how would you go about achieving it? Two simple principles to follow:

• Ensure that your value proposition is clear, compelling, and resonates with your target market.

• Listen to your customers, ask for feedback, and use it to improve your product or service.

Easier said than done, right? But nothing comes easy, my friend 😄 

💝 L - The Monkey Trap

I grew up in Varanasi (India), one of the oldest continuously inhabited cities in the world. In the late 1990s, monkeys were a menace in my town. They would jump onto house terraces and make their way into kitchens, searching for food. In the process, they would encounter adults and kids, and that wouldn’t often end peacefully.

The fix was to employ monkey-catchers who relied on an age old technique called the Monkey Trap.

So, picture this: a monkey on one side of a barrier and a pile of peanuts on the other. The monkey can easily slide its hand in and grab those tasty nuts. But wait, there's a catch! The opening, that allowed the monkey to stretch his hands out to the other side of the barrier is now too small for the monkey's clenched fist to slide out. Talk about a sticky situation!

To escape, all the monkey has to do is let go of the peanuts. But nope, it refuses and ends up stuck for life.

The irony is that we are kind of like monkeys too! We stick to jobs, relationships, or situations that make us feel trapped and confined, all because of silly reasons like social status, fear of failure, or ungratefulness.

To be fair, I get it! Peanuts are hard to come by. But hey, there are things more important than these peanuts. And you are probably sacrificing more than you are getting in return!

🤖 T - Recommender Systems

Ever sat down in front of the TV, trying to pick a title on Netflix that you might enjoy? But then you get stuck in a plethora of choices, and end up watching “The Office” anyway (it’s on Netflix Canada, sorry US folks!). While so many alternatives overwhelmed you, you were still getting exposed to a movie recommender system.

Recommender systems have become an integral part of our lives, and we use them without even realizing it. Popular platforms like Netflix, Amazon, and YouTube use sophisticated algorithms that recommend items to users based on their preferences. These systems are typically composed of three components:

• Candidate generation: generate a list of choices to pick from.

• Scoring systems: predict how the user would rate it.

• Re-ranking systems: incorporate the user’s final feedback and update the system.

While scoring and re-ranking systems are fairly technical, the candidate generation part of the recommender system is very intuitive. Broadly, all recommender systems are based on either content filtering, collaborative filtering, or a combination of both.

First up, we have content filtering. This method involves recommending items based on their attributes, such as genre or keywords. It's like being set up on a date with someone who shares your interests; you're more likely to hit it off and have a good time. Similarly, if you're into action movies, a recommender system using content filtering will suggest other action movies for you to enjoy. But the problem with this method is that you will not discover anything entirely new. And that can be pretty boring, right?

That’s where collaborative filtering comes into play. This approach takes into account the preferences of similar users to make recommendations. It's like having a group of friends who all have great taste in movies and can tell you what to watch next. Collaborative filtering is especially useful when you're not sure what you're in the mood for, but you trust your friends' opinions.

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Until next time!

Gaurav