Marketing and data teams have hundreds of metrics flying in from multiple platforms and channels at any given time. Connecting all this data into one view helps them to understand trends and patterns so they can better allocate their budget. But doing this manually takes more time, effort, and focus than can be reasonably expected.
As the amount of data pouring in continues to increase, automation offers a much more sustainable and scalable way to see what activities are working, and where optimizations can be made. This is where APIs and connectors come in.
This blog will explain what APIs and API connectors are, and how they help marketing and data teams to get a single view of all their data.
What is an API?
An Application Programming Interface, or API, is a set of code. More specifically, it’s the code that provides a set of definitions and rules that allow information to pass between two software applications.
What does that mean?
Let’s take Facebook as an example. Facebook’s API is basically like a port into the platform. By connecting through this port, you can access all the metrics Facebook provides about your marketing activities — reach, views, clicks, etc. to pass to you, the user.
But let’s not forget that you can also send information into the Facebook platform. It’s by connecting through the Facebook API that you can use other platforms like HubSpot to perform tasks like posting in pages and groups and managing ads.
To give Facebook these kinds of instructions, both platforms need to be speaking the same language. They need to understand the same set of rules and definitions around how data can pass back and forth. That’s what the API is.
What is an API connector?
An API connector is the mechanism through which information can be passed between two applications with APIs.
What does that mean?
So we’ve established that APIs create the infrastructure that allows different platforms to talk to each other. But this can only happen in practice when API connectors enter the mix.
To make sense of all this code and actually send data to and from a platform, you need an API connector. Connectors are the mechanisms that allow communication between two applications. Let’s go back to the example of Hubspot and Facebook.
Both Hubspot and Facebook have APIs, but it is the connector that actually brings these together so that marketers can pass instructions through HubSpot to publish a post on your company’s Facebook page.
Or, for example, Adverity's connectors provide a user-friendly, code-free way of communicating with the API to retrieve data. So, if you want to retrieve your Facebook reporting data and transfer those into an Excel spreadsheet, then the Adverity Facebook connector lets you define exactly which data you want to request from Facebook, and the data is retrieved via the Facebook API. Once the data is successfully fetched, it can be sent to an Excel destination, via another API connector.
How are API Connectors maintained?
The short answer is; with a lot of effort and time! Data platforms update their APIs all the time which means that the API connectors that serve them also need to update to ensure that they do not break and there is a continuous flow of information.
You can learn more about maintaining API updates and API connectors in this blog: API Updates: How To Deal with Connector Maintenance
Why do marketers need to understand APIs vs connectors?
To make data-driven decisions, marketers and data teams first need to break down data silos and gain a single view of all their activities. This means getting data from multiple sources in one place, and in a format that allows for comparisons and queries. So naturally, if you’re pulling data from various marketing channels, then APIs and connectors are going to be a part of this process.
For a long time, marketing and data teams were manually downloading metrics from different platforms into Excel spreadsheets, and copying and pasting these together. In the past, marketing and data teams didn’t really need to understand APIs and connectors beyond this.
However, as the number of channels and the granularity of data continue to increase, a more scalable solution is called for. Teams can automate data fetches and integration by taking advantage of data connectors. This means they can save time and avoid opening data up to the errors that naturally come along with copying and pasting data.