Great content does nothing in the face of bad strategy — lessons from The Content Trap

Rishabh Srivastava
Jul 25, 2019 · 5 min read

Content is a curse. It causes you to think you can make what’s going to delight users. It causes you to ignore their contributions. It causes you to focus on your own content rather than how to get the best content in the world — content that anyone can make.

This is my attempt at synthesizing ideas and concepts from Bharat Anand’s excellent book The Content Trap. Errors in interpretation are my fault. Credit for the insights is entirely Bharat’s.

The Current Media Scenario

The content industry is characterised by cut-throat competition, worsening financial outlooks, a passive management response, and management disagreement on how to respond to changing dynamics.

Content companies face a two-fold challenge: how to get noticed in a world with staggering choice, and how to get paid. Regrettably, responses to these challenges tend to have 3 counter-productive expressions:

  1. Obsession with isolated triggers rather than recognizing conditions that make them spread
  2. Effort to preserve content at all costs, rather than seizing opportunities around it
  3. Search for quick wins and “best practices”, instead of first-principles and capacity building

Superior content is great. Superior strategy is better.

Great content — by itself — does not guarantee long-term success. Growth and innovation often come not from better content, but from effective strategy around it.

It’s up to you to figure out what this strategy is. For publishers like The Economist, it is the provision of Status as a Service (“I am smart because I read the Economist”). For the New York Times, it is the provision of Virtue as a Service (“I help speak truth to power because I subscribe to the Times”). And for a platform like TikTok, it is Amusement as a Service (“I am not bored when sitting on the toilet because I can consume short videos”).

Content is important for each of the 3 examples described above. But strategy is what helps move companies from mere commodities to brands that consumers love.

Don’t just create great content. Think about the overarching strategy — think through how content fits in the larger narrative.

Source: The Content Trap by Bharat Anand

Getting Your Strategy Right

Get the functional (what will this content be used for), user (who consumes this content and what do they do with it) and product (how is this content consumed) connections around content right. To do this:

  1. Figure out which customers to go after and what they really want.
  2. Form a worldview about how customer behaviour is changing, but never start with your content while doing so. If you’re a content-creator, don’t start by understanding what you offer to users. Start with a view of how people are finding out about content, how they’re using content, and how they’re buying products related to your content.
  3. Figure out what to offer users in a way that matches their behaviour with your unique capabilities
  4. Think hard about the trade-offs you’re making and don’t compromise by trying to please all parties. Your strategy should be opinionated — and not look like it’s designed by committee

Leverage the community

Building a community around your content and getting them to contribute to the content — thereby making it better — is an insanely effective way of supercharging your business. Product Hunt, IndieHackers, and the PewDiePie subreddit are all phenomenal examples of leveraging the community around your content.

When embarking on a content strategy, think hard about how you can invite your most engaged users to contribute, and then use their contributions to create more value for other users. You likely won’t be able to do this when just starting out, but do think about how you can leverage the community in the long run.

Utilize spillover effects

Massive hits have a spillover effect. Between January 2000 and 2001, view ratings of Star Television in India jumped 400%. This was mostly because of one show — Kaun Banega Crorepati.

The show itself was a wild hit, but also caused a halo effect for other TV shows on the channel. Bharat Anand wrote an interesting paper about this phenomenon:

As concrete evidence, consider a simple example. Kaun Banega Crorepati (KBC) first aired on Star on 3-July-2000 at 9.00 pm. Only a month later, in August 2000, Star’s ratings over the entire weekly lineup jumped from 1.55 to 8.15 TRPs. Sure, the ratings of KBC itself were great. But the ratings for the shows that aired right after KBC on the four nights of the week also showed a dramatic increase. And, here is the real icing on the cake. While ratings for Star ’s shows on the nights that KBC was aired jumped by 380%, the ratings for its shows on nights that KBC was not aired still jumped by 320%.

Using massive hits to promote the other work that you do is an enormously effective way of driving user engagement and connecting them with valuable content. For this reason, investing in great recommendation engines is a necessity for modern content-creators.

Getting noticed

Product good content and you might receive critical praise. Publish the same content under a familiar name, and you’ll get a blockbluster hit. For instance, The Cuckoo’s Calling (a book that JK Rowling initially published under the pseudonym of Robert Galbraith) initially had muted reception. But its sales surged by 1500x after Rowling was revealed as an author.

Do note that merely having a large audience is not guarantee of success, either. For instance, former Fox News start Bill O’Reilly has a huge audience — but his new independent venture has largely failed because it lacks the punchiness that his old Fox show used to possess.

Look for opportunities to pair great content with popular trends and well-known people. Swimming downstream is far easier than swimming sideways (or upstream).

Hope you found this post useful. Do leave a note on Twitter (rishdotblog) or email me at to give feedback, or just say hi! :) I’m a tech startup founder, human-optimisation junkie, and machine learning enthusiast living in Singapore.

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