The insight hiding in WhatsApp forwards
In 2015, Ankush Sachdeva, Bhanu Pratap Singh, and Farida Haidari launched ShareChat out of IIT Kanpur with a product so narrow it barely looked like a startup. The app was a content discovery tool — a place to find the memes, quotes, regional jokes, and devotional images that Indian smartphone users were already forwarding to each other on WhatsApp at scale.
The insight wasn't technical. It was demographic. India's next hundred million internet users — the people getting online for the first time on a ₹6,000 Android phone with a Jio SIM — were not English-speaking. They were Hindi-speaking, Bhojpuri-speaking, Marathi-speaking, Tamil-speaking users in Tier 2 and Tier 3 cities who had smartphones but no internet experience designed for them. Facebook and Instagram had billions of users globally, but their content algorithms were trained on English-language engagement data. Regional Indian content was a second-class citizen. WhatsApp was the medium, but there was no good source. ShareChat became the source.
On day one, users shared about 100,000 content pieces per day. The product had no social graph, no creation tools, no monetisation. It was a content warehouse for things worth forwarding. That turned out to be enough to get started — and it established the most important thing a new platform can establish early: a reason to come back.
The Decision
The question that shaped ShareChat's entire trajectory was one that most content platforms face and answer badly: stay a distribution tool, or become a creation platform?
Distribution tools are easier to build and harder to defend. If ShareChat's product was "a place to find WhatsApp-forwardable content," any competitor with better curation or a larger content library could displace it. The moat was shallow. The value was convenience, not identity. Distribution tools don't become social networks — they become utilities, and utilities get commoditised or absorbed.
Creation platforms are harder to build but build compounding defensibility. When users generate content on your platform, they have a reason to return that doesn't depend on what you source — they come back to see how their content performed, to engage with comments, to build an audience. The social graph that forms around creation is an asset that gets stronger with time and is extremely hard to move.
ShareChat's product roadmap between 2016 and 2020 is best understood as a deliberate march from distribution to creation. UGC tools were added. Language communities formed. Users could post, comment, and follow. The 15+ regional languages — Hindi, Marathi, Bengali, Gujarati, Punjabi, Odia, Tamil, Telugu, Haryanvi, Rajasthani, Urdu, and more — weren't a feature list; they were a moat. Building font rendering, keyboard support, content moderation, and recommendation models for each of those languages was expensive and technically unglamorous. It was also something no other platform had done at that depth for this user base.
The decision to go deep on vernacular infrastructure before expanding features was the most important allocation call in ShareChat's history. They could have added creation tools earlier and covered fewer languages. They could have covered more languages with shallower support. Instead they invested in genuine linguistic depth — proper keyboard input, language-specific content policies, moderation that understood what was culturally offensive in Bhojpuri versus Tamil. That investment created a platform that served the vernacular market authentically rather than as an afterthought, and it made the platform extraordinarily difficult to replicate quickly.
What Worked
The vernacular-first positioning worked because it was specific, not aspirational. ShareChat wasn't "building for all Indians" — it was building for Indians who didn't see themselves in the dominant English-speaking tech products. That specificity made the product feel like it was made for you if you were a Hindi-medium user in Bhopal or a Marathi speaker in Nagpur. Platform trust is easier to build when the product speaks your language literally as well as metaphorically.
The UGC shift worked because it changed the competitive category. A platform where users create content is not competing with other content libraries — it's competing with social networks. The ceiling on a social network is much higher than the ceiling on a content aggregator. When ShareChat added creation tools and community features, it repositioned itself from "WhatsApp's content source" to "India's vernacular social platform." That positioning was accurate by 2019.
Content moderation for regional languages was a strategic investment that others missed. English-language moderation tools don't work on Hindi slurs or Tamil political content. Building moderation infrastructure that understood the specific patterns of harmful content in Indian regional languages wasn't a visible product feature — users don't see the moderation system. But it was what allowed ShareChat to safely serve markets that other platforms either ignored or served badly. The ability to moderate at scale in regional languages was an operational moat wrapped inside a product.
The External Accelerants
Two events in 2020 accelerated ShareChat's trajectory in ways that would have been hard to plan for — but that the product was positioned to absorb because of the infrastructure decisions made in the years before.
COVID-19 lockdowns in March 2020 drove a dramatic acceleration in digital consumption. Smartphone usage increased, social media consumption nearly doubled, and daily active time on platforms spiked. ShareChat's monthly active users went from 60 million to 160 million during the pandemic period. Daily average time on platform went from 24 minutes to 31 minutes. None of this was because of a product change — it was because the product existed, had an engaged user base, and was in exactly the right category when behaviour shifted.
The TikTok ban in June 2020 was more dramatic. India's government banned 59 Chinese apps, including TikTok, Likee, and WeChat. Overnight, 200+ million TikTok users in India needed somewhere to go. ShareChat acquired 500,000 new users per hour after the ban announcement. The company responded with a deliberate product move: launching Moj, a dedicated short-video app built for the TikTok user base, which reached 80 million monthly active users with 34-minute average sessions.
The TikTok moment is sometimes cited as the cause of ShareChat's growth. It was an accelerant, not a cause. The reason 500,000 users per hour chose ShareChat rather than another alternative was that ShareChat had the vernacular content infrastructure, the UGC culture, and the community features that made it a credible destination. A platform that had spent six years doing the unglamorous work of building for the vernacular market was positioned to absorb a windfall that a newer or shallower platform could not have handled.
What Failed
ShareChat's monetisation lagged its growth consistently. By the time the company was approaching unicorn territory, its advertising product was underdeveloped for the audience it had built. The vernacular user base — predominantly from Tier 2 and Tier 3 cities, lower average income than metro English-speaking users — commands lower CPMs from advertisers than the audiences Facebook and Instagram offer. The platform's product strength was also its monetisation challenge.
The breadth-vs-depth tension in language coverage also created ongoing product quality issues. Serving 15+ languages at genuine quality depth is hard. In practice, some languages got better content moderation, better keyboard support, and better recommendation quality than others. Users in underserved language segments had a demonstrably worse product experience than Hindi speakers, which created churn pressure in exactly the markets where ShareChat had the most unique value.
The Moj launch, while strategically correct, created an internal portfolio management problem. ShareChat and Moj served overlapping user bases with different content formats and different engagement patterns. Resource allocation between two high-growth products with a partially shared user base is a difficult PM problem, and the tension between investing in ShareChat's social platform depth versus Moj's short-video growth remained unresolved.
What a PM Should Take From This
ShareChat's trajectory is a masterclass in how structural market shifts compound — and how early product decisions either set you up to benefit from those shifts or leave you on the wrong side of them. The demographic trend was visible in 2014: India's next internet wave was vernacular. The decision to build deep vernacular infrastructure in 2015 was not obviously correct — it was expensive, technically hard, and the return was years away. It was correct because the founders were reading a 10-year arc, not a 12-month roadmap.
The platform evolution from content tool to social network demonstrates a pattern worth studying: the best path to a social network is not to build a social network. It's to build something valuable in a specific use case, accumulate enough engaged users to understand what they actually need, and then expand the product category once you have the trust and the data to do it right. ShareChat's "social network" features worked because they were grafted onto a user base that already had a reason to be there.
The anti-pattern this case exposes: building for the visible user and ignoring the structural market. In 2015, the visible Indian internet user was urban, English-speaking, and well-served by existing platforms. Building another product for that user was building into the most competitive part of the market. Building for the vernacular user — less visible, less analysed, less served — was building the product that the next hundred million people actually needed.