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Open data is free, but it's not really valuable to anyone in its raw form. To monetize open data or any other form of data, you need to process it. By processing it correctly, you're adding value to it. This makes it more useful to others.
For example, how useful is the historical stock price data? Not much. But how valuable is the insight into which stock will go up or down in price? A LOT. So the key is to:
So to monetize a data set, you first need to make it easy and convenient to access. And one of the best ways to do it is to expose it through an API.
How to monetize data through an API?
The first thing you need to do is build an API. The most cost-effective way to build it is by using low-code technology.
And the last step is to publish the API on one of the popular API marketplaces. This will also be covered in the rest of the article.
The first step is to get an idea of what would be a good API business. In case nothing comes to mind, here are some API business ideas you might find useful.
Once you roughly know what to do, see what data you already have at your disposal. Based on your API idea, you already know who would be interested in that data. So make sure you can provide it in the format preferred by your target market (ideal customer).
After that, you wrap it up into an easily accessible API. And you enable easy access to your potential customers.
In case you don't have any data on your own, plenty of other resources are scattered all over the internet. And one of the best choices is to use open data.
There is truly a lot of open data on the internet. One place you can start is the Data.gov website.
You will notice that the data on this (and many other sites) is fragmented. There are:
Just like in a real mine - there is gold - but you have to dig. And if you would process this data so that it's:
You might have an actual API business. Because there is always value in any product that saves someone's time or effort. Similar to what low-code technology is doing for the world of software development.
The data.gov website has different types of location data: population, housing, etc. And if you can detect internal migration and overlay it with construction trends, you can predict future housing prices. And this is just one of the examples.
If you see that some areas are getting higher population growth than the speed of housing construction, you might be onto something. Clearly, the demand for houses and apartments will be higher than the supply in that area, which will cause the prices to rise.
And who would benefit from this processed data? Real-estate agents, construction companies, and also people who are moving across the country. Because if they knew their living costs would go up, they might choose another location to move to.
Another helpful thing is to know the number of available jobs per number of unemployed people for a specific location. This would give people on the move valuable info on where to go. And also, it would inform them about areas with higher or lower job competition.
The possibilities are endless. However, the most important part is keeping in mind your potential customers. If you understand them and their needs, your data will be (relatively) easy to sell.
The first part of the architecture is an API. And using traditional programming, API development is what takes the most amount of time.
However, in recent times, there has been a complete paradigm shift when it comes to software development.
Low-code technology is taking the world by storm because it allows developers to be 3-5X more effective. This is especially noticeable when building APIs. All you have to do is:
The alternative is to do everything by hand using traditional programming and manually handle every:
Aside from taking more time and costing more, your competitors who are using low-code will be able to:
All the while doing so at a fraction of the cost that traditional development projects have to pay. Considering all of these differences, it is really safe to say that low-code technology is a paradigm shift when it comes to software development.
This is the most important and exciting part of an entire journey: monetization/selling the data sets.
Regardless of how good or productive any software development technology is, setting up an API business has a lot of moving parts. The good thing is those parts can be avoided through outsourcing.
Depending on which API monetization strategy you choose, your API will also have to:
To avoid all of this extra work that is comparable in size to your core API business, you can use API platforms/marketplaces. One of the biggest marketplaces in the world is RapidAPI.
This will give you all you need regarding payments, handling user tokens, choosing different monetization models, etc. And in exchange, all you have to do is pay a small fee.
After that, you only need to promote your API to your target customers. If they see the value in your data, you will make sales. And that is how you monetize open data sets.
Data is accessible everywhere for free. Unfortunately, it's formatted in too many different ways across many different files to be directly useful.
Processing, aggregating, and exposing this data through an API makes it easily available to people and businesses who might need it.
The most competitive way to build APIs is through low-code technology. Its main job is to automate all the repetitive tasks that require a lot of boilerplate code and waste developers' time. Plus, it's automatically scalable, so you never have to worry about that.