The Wizards Behind Zomato, Ola And BigBasket Decode The Nuances Of Product Market Fit

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With the goal of bringing the most up-to-date product development principles through the eyes of some of the most successful and knowledgeable product builders in India,  The Product Summit was unlike witnessed in the Indian startup ecosystem. 

It saw a heady lineup of India’s leading entrepreneurs such as Zoho’s Sridhar Vembu, Zerodha’s Nithin Kamath, OYO’s Ritesh Agarwal and others lay out the broad strokes of product strategies that helped them succeed. 

But behind every rockstar founder with a vision is the engineering and product team that executes the tasks and reads the user’s exact needs to build customised products that find the best traction. It all begins with the idea, but the product direction is determined by the product-market fit. 

We brought together product leaders that have ‘been there and done that’ from the product-market fit lens — the likes of Zomato product head Rahul Ganjoo, Bigbasket’s director of products Tejas Vyas and Lightspeed Ventures’ Harsha Kumar, who oversaw Ola’s transition from a few thousand rides a day to millions. Moderating the panel was Gaurav Arora, the head of startup ecosystem, Asia Pacific and Japan, at Amazon Web Services. 

The User Factor In Product-Market Fit 

Arora set the stage for gleaning varied insights on the topic from a diverse panel of experts by asking them to recount some of their interesting experiences at product startups with regard to PMF. 

Ganjoo recalled his first brush with the treacheries of product-market fit was at a Silicon Valley startup which had launched a blogging app on the App Store. At that point, Facebook and Instagram were still considered as new kids on the block and his company was confident that it had nailed every feature and functionality, besides having more users than competitors.

The evaluation was found to be mistaken ultimately as the product didn’t take off — the assumptions that past users would carry forward on the basis of features proved to be wrong. Ganjoo’s blogging app hadn’t taken into account the UI/UX demands of a generation that was beginning its digital journey with social media, but didn’t share the preferences of the existing set of the email generation.

“That’s when I first learned that it’s not about features or having more functionality. It’s deeply understanding where your users are going, how they’re using these products, what their needs are, and then solving for those,” Ganjoo said.

Tejas Vyas too learnt about PMF the hard way as his startup kept on adding features to the product even before launching. And after spending one and a half years in the building phase, the startup went to the market but soon realised that customers didn’t value all those features. “That experience was a wake up call for first talking to customers to understand their needs, or differentiate their needs and wants,” he said.

Having worked at online gaming company Zynga, Harsha Kumar said the experience taught her that PMF is all about understanding the user well enough so that features can be turned off and on to nudge behaviour. Zynga used to have daily targets for revenues and the product teams could predict how much revenue would be made from the games on a given day. 

“And if we saw that we weren’t trending towards that number, we could turn on features and experiments, and know exactly how much a feature will deliver in terms of revenue,” she recalled about her stint at the gaming company, which eventually racked up hundreds of millions of users across titles. 

The Market Never Settles, Even After Product-Market Fit

The former product head of ride-hailing startup Ola, however, maintained that perceiving PMF as one point in the lifecycle of the product is a wrong notion. While it’s undeniable that the journey for any product company begins with finding a market that wants your product and then loves it enough to stay on it, what’s also true is that most digital products can be cloned easily. 

“In the investing world, we’re constantly looking for non-linear growth. You want that hockey stick. The reality is that anything has that hockey stick can actually be imitated very quickly,” said Kumar. 

In contrast, products that have barriers of entry such as creating a supply chain tend to grow in a linear fashion i.e. they cannot have a hockey stick trajectory. 

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So digital products have to go through multiple iterations or risk threats from competitors that offer the same features and then some more. “You will have to constantly keep evolving and keep building on your product, going deeper into your customer’s life to keep sort of retaining them. Keeping a retention level steady is actually a huge feat. 

Another factor is that retention drops as a company grows as the competitive environment just gets more intense. Moreover, the internet ecosystem changes at a fast clip as people’s behavioral patterns constantly evolve — for instance ecommerce itself has gone through multiple transitions to branch out into marketplaces, social commerce, video commerce etc. 

“If you don’t keep evolving with what your users like or love, you will start losing them. This journey to PMF never quite ends — you’re constantly on a treadmill — you will hit PMF, get an S curve, and then you’ll start to plateau. And guess what, you have to find another S curve if you want to keep growing,” said Kumar.

Golden Rule: Adopt A North Star Metric 

A popular conundrum in the product-market fit arena is choosing the right metrics to measure it. While metrics such as Net Promoter Score, retention, and conversion from free to paid users are widely accepted, there are also many tech startups that dwell on numbers such as daily average users and monthly average users.

One way to resolve the problem is to look at the numbers for a company that has already achieved PMF and measure the startup’s corresponding numbers against that standard. However, one problem with this approach is when a startup creates a new product category or enters geography where the category hasn’t succeeded yet. 

When Bigbasket launched in 2011, there were hardly any success stories in the entire ecommerce sector apart from Flipkart, which was a rising star but the lone example of an online product in India that had found wide acceptance. Through the years, the Bengaluru-based grocery delivery startup has managed to carve a niche in a category that very few have understood, even globally.

This meant that it had to improvise on the usual metrics to use a figure that would communicate customer delight unique to its category — and so WYSIWYG (what you see is what you get) was adopted as the de facto indicator of user satisfaction. According to Vyas, who joined Bigbasket a year after its launch, WYSIWYG is a measure of efficiency — the completion percentage of the order i.e how much was delivered vs how much was ordered.   

Interestingly, during March and April when India was under Covid-related lockdowns, the WYSIWYG figure was hovering around 98% — falling by 1.6 percentage points from the company’s usual threshold of tolerance. However, customers were okay with even getting 60% of the cart order being delivered, as most were desperate to get whatever they could. 

“For every little tweak that we do, we base it around the WYSIWYG metric, and see how this particular metric is aligned either in terms of a customer experience. How we keep the bigger picture in the long term metrics is by iterating the product to get the short-term metric aligned internally,” Vyas said, outlining that tech products cannot have standard undeviating metrics as the market keeps evolving.

This article is part of our coverage around The Product Summit 2020 by Inc42, which took place on October 10 & October 11. TPS 2020 was supported by Amplitude, AWS, Dell Technologies, and DigitalOcean.

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