What are data connectors?

At Funnel, we talk a lot about data connectors. They are an essential building block of a marketing data hub’s functionality, and without them, comprehensive data analysis is next to impossible. 

Then, the other day while enjoying a bit of fika (it’s a Swedish coffee break with different confectionaries and good conversation), someone posed the question: “How would you explain what a data connector is to a lay person?” Then, someone else exclaimed in response, “That’s a great idea for a blog article!” 

Seriously, though, it can be a bit tough to define. A data connector isn’t an API, it’s not a standalone piece of tech. So, what is a data connector, exactly?

We’ll break it all down for you, including the different kinds of data connectors and why they are so important to your data analysis. 

What is a data connector? 

A data connector is a bit of technology that allows for data to flow from one point to another. Say you want to pull data (like open rate) from an email marketing system to your customer relation management (CRM) platform. You’ll need to establish a data connection to do so. Similarly, to extract data from Facebook and share it to a dashboard, you’ll need to first establish a data connector. 

A data connector helps data flow from one source to another destination.

To be clear, though, a data connector is not an API. The API is simply a metaphorical doorway through which a data connector can be established. The connector itself is an extra piece of software that establishes which data will be extracted from your data sources, where the data comes from, and the immediate destination – roughly speaking. 

A data connector can be used to extract every ounce of data from a platform, a general set of data defaults, or it can be highly selective in the data it extracts. It all depends on your specific needs. In a marketing data hub like Funnel, they can come in two forms: core connectors and custom connectors.

Why are data connectors so important? 

If you want to reach your audience, you need to meet them where they are. This often means that digital marketers need to run ads across different Meta properties, across search, a plethora of social media platforms, and more. In order to monitor the performance of your ads, you’ll need to review the data in an analytics dashboard or spreadsheet. 

While nearly every modern advertising platform will provide you with some kind of a report, most marketers prefer to view overall performance in one place. This means you need to, first, extract the performance data from each platform. 

To do so, you’ll need some sort of… data connector! This is where the marketing data hub comes in. Of its many features and functions, this hub will make a connection to all of the platforms you ask it to, then extract all of the data you need for your analysis. 

Without a data connector, you wouldn’t be able to extract your data to a single source of truth (you know, one dashboard to rule them all). That means you would need to go into each platform individually, review performance, take manual notes, and then try to make sense of any discrepancies or erroneous attribution in hindsight. And it can be hard to find the sorts of insights that will propel your business forward. 

The benefits of data connectors

Time saving:
Automating data flow eliminates the need for manual data extraction and ingestion, freeing up IT staff for other tasks.

More accuracy:
Manual data entry is prone to errors. Data connectors eliminate this risk by transferring data accurately and consistently.

Improved data quality:
Automated data connectors can help identify and address data quality issues during the transfer process, ensuring that only clean and reliable data reaches your analytics systems.

Faster decision-making:
With automated data updates, businesses gain access to real-time or near real-time data, allowing for quicker and more informed decisions.

Simplified data management:
Automated connectors simplify the process of integrating data from multiple sources into a central location for analysis. This can be especially helpful for organizations that use a variety of software applications.

Custom versus core connectors

Let’s imagine you're starting out along your data maturity journey. You’re aiming to be more data-driven in your marketing decisions, but you still aren’t highly sophisticated in your analysis. Instead, you may want to scrape readily available data from the most common ad platforms (see: Google Ads, Facebook Ads, etc.). 

In this case, you may want a core connector for extracting data.

Say you aren’t just any user, though. Instead, you may be after a very specific set of data, or the data sources you want to use might be very niche. In this case, you need a custom data connector. 

As you can probably guess, these connections are a bit more bespoke. In a marketing data hub like Funnel, custom connectors are often built to spec in order to get you exactly what you need. 

Can I build my own data connections?

Speaking of building connections, we often hear a common refrain: “Can’t I just go off and build my own data connector to extract my performance data?” 

In short, the answer is yes. If you have the programming expertise, you can certainly build your own data connectors. However, ask yourself if you really want to build them yourself. 

Building your own connectors could, in theory, save you money up front (if you have the programming capacity freely available in-house). In the long run, though, self-made connections often lead to a lot of headaches. 

It’s not that people are bad at building connections, either. The real culprits are those pesky APIs. 

Maintaining data connectors

See, the platforms we use as data sources are constantly iterating on and improving their capabilities. These improvements lead to changes in the code, which can often require changes to the APIs allowing external developers to connect to the platforms. 

In the context of a data connector, a change to the API will often break the connection to your data source. That means no data, no analysis, and no insights. 

And these platforms can change their APIs. A lot. In fact, at Funnel, we have multiple developers dedicated solely to Facebook’s API changes, making sure the connector is up to date.

For those opting to build their own data connectors, it means you will need to employ your own experts to constantly monitor all your data sources and maintain every API-enable connection. It’s the classic build-versus-buy argument, and one we have a clear preference on. 

What kind of data connectors exist? 

As the digital marketing industry continues its exponential growth, more and more advertising platforms emerge – and that means more data sources. As a result, there are already a nearly endless amount of data connectors. 

Just take a quick look at our data connectors page, and you’ll see all of the famous platform names you know and love — plus many more that you may have never heard of. 

Think of this, with Funnel, you can connect hundreds of platforms on day one. And that’s just the platforms. You can have multiple connections for each data source, too. 

Using pre-built data connectors

Pre-built data connectors, like the ones we link to above, are ready-made tools that streamline data integration from various sources into a centralized system. These connectors easily hook up to popular data platforms, databases, applications, and APIs – meaning you don’t have to worry about custom development or coding. The great thing is that pre-built data connectors offer plug-and-play functionality, allowing users to use them without any technical knowledge.

Pre-built connectors also alleviate the need to have a dedicated tech team to keep them afloat through API updates. A fact that’s often overlooked is that many platforms update their API's quarterly, which can cause breaking changes.

Plus, pre-built data connectors may include features such as scheduling and automatic quota management, making them even better for data integration tasks.

Some popular pre-built data connectors you might recognize:

Salesforce Connector: Integrates data from Salesforce CRM with other systems like marketing automation platforms, ERP systems, or data warehouses.

Google Analytics Connector: Transfers your website analytics data from Google Analytics to various business intelligence tools, data warehouses, or reporting platforms.

Shopify Connector: Integrates e-commerce data smoothly from Shopify stores with accounting software, inventory management systems, or data visualization tools.

Microsoft SQL Server Connector: Seamlessly integrates between Microsoft SQL Server databases and other systems like cloud-based platforms, analytics tools, or data lakes.

HubSpot Connector: Syncs customer relationship management (CRM) data from HubSpot with marketing automation platforms, email marketing tools, or data warehouses.

Facebook Ads Connector: Integrates all your advertising campaign data from Facebook Ads Manager with analytics platforms, attribution tools, or customer data platforms for performance analysis and optimization.

You can find all of these connectors, and more, as ready-to-use options when you use Funnel.

Data connectors are the lifeblood of great analysis

Without data connectors, great performance analysis just isn’t possible. Can you imagine trying to manually review the performance dashboards for 500 different data sources? No, thank you. 

Those connectors need to be properly built and maintained, too. Otherwise you’re likely to spend countless hours (and money) fixing broken dashboards and suffering from the Sunday Scaries. 

We much prefer a world where you can click a button and automate the whole process, but to each their own we guess. 

FAQ

What are data sources?

A data source can be any platform you gather data from – from an email marketing system to a social media platform. 

Can you do data integration without data connectors?

Data integration relies on data connectors to make sure information flows seamlessly between different systems or data sources. To put it simply, data connectors allow different systems to "talk" to each other by transferring data back and forth. Sometimes, as in Funnel's case, the connector will do the transformation too. Without data connectors, it's much harder to perform data integration. 

Can data connectors transfer data between different systems and a data warehouse?

Yes! Data connectors act as intermediaries – making sure each data source, systems and applications are in sync. With data connectors it’s easier to extract data from various sources to one centralized data warehouse for storage or processing. 

What is data extraction?

Data extraction is the process of pulling data from various sources, structured or unstructured, for further processing or storage.