A lot of platforms and aggregators at the end of the day serve as a search engine for users.

Users come on these platforms to look for something, and what they see is determined by how the internal search and recommendation system ranks different entries.

So, for the people using these platforms for posting offers and content, they have to play the SEO game.

And not just any SEO, but the SEO of that specific platform.

Think about it: a restaurant’s survival might depend on DoorDash’s ranking algorithm.

A musician’s career hinges on Spotify’s recommendation engine.

A small business lives or dies by Amazon’s search results.

A freelancer’s income is determined by how Upwork’s algorithm surfaces their profile.

Every app store, every e-commerce website, every job board, every listing-based site is a game of appearing at the top.

If you are at the top of search results or at the recommended section, then you are in for a good time.

That is the position where visibility, clicks, conversions, and outcomes start to happen.

You want to top the search and recommendation algorithms of the platform you are on.

One way to do that is to have huge volume, with constant iteration, doubling down on everything that works.

Another way is to pay the platform to put you on top, but then you have to be sure that your unit economics would work out.

You have to make sure that what you are selling allows you to profit even after paying for visibility.

Amazon, LinkedIn, IndiaMART, eBay, Etsy, YouTube, Instagram, Coursera—all of them run and earn off their search and recommendation systems.

They are designed to filter and rank what users see, and they monetize the traffic and attention that comes from that.

Thus, to win on this platform, the way is either to have huge volume, or to have a high enough ticket size of your product that you can afford ads.

So, for an entity, the path is to pick a platform they see booming.

A platform that has attention, that has traffic, that has growing user behavior, and that is likely to keep serving demand for a long time.

Once that platform is selected, the next step is to go all in on it.

That means adapting yourself to how that platform works.

That means understanding how search happens there, how recommendations are made, how visibility is distributed, and how conversions happen.

And then start pumping out a huge volume of offers and products that are designed to work within that system.

Not one product.

Not one offer.

Not one attempt.

But tens or hundreds.

Different target audience, Different angles, different categories, different listings, different price points.

For an app store, that just might mean releasing tens of apps instead of one.

The more volume you push, the more signals you get, and the more chances you have to get something to rank.

Then you double down on what works.

Whatever gets traction, you feed more into it.

More versions, more updates, more attention.

Volume and doubling down.

That is the cycle.

If you are on PolicyBazaar (Indian insurance market place), then you follow the same logic.

You cannot rely on a single insurance product.

You have to list multiple offerings.

Different premiums, different coverages, different bundles.

And then track what gets discovered, what gets clicks, what gets conversions.

Then you keep improving that.

You invest more in the ones that are showing results.

You pull back from what is not working.

You keep feeding the winners with more visibility, more budget, more focus.

That is how you win the internal game of the platform.

For Amazon, Ebay, Etsy that means running mutliple brands and products.

For Youtube, Instagram that means multiple accounts and content styles.

For any marketplace it means having many offers.

Just makes you realize that a lot of world’s commerce and attention is hinging on the search rank and recommendation algorithm.

Not just in Google anymore. Every platform is a vertical search engine and recommendation systems now.

It’s not a game of making one great thing anymore.

It’s a game of pushing a hundred things into the pipe and watching which ones the algorithm picks up.

Then feeding the winners.