LinkedIn is now more than a place where people tell others about their job and experience. It is even more than a place where you advertise new open positions and look for a new job. LinkedIn is now also a powerful marketing tool and, potentially, a large database.
LinkedIn data is often not easy to analyze when seen concurrently with data from other platforms. Learn how to import LinkedIn Data into Power BI for better visualizations using Windsor.ai.
LinkedIn as a Marketing Tool
Anyone who understands LinkedIn Marketing knows how crucial it can be to growing your business. The native tool built-in LinkedIn that provides data insight is LinkedIn Analytics. Reactions, comments, shares, impressions, all these metrics, and more are available in LinkedIn Analytics.
Even though a lot of companies use LinkedIn data these days, very few use only LinkedIn – they use other platforms too. Integrating data from different sources and channels can be challenging, fortunately Windsor.ai solves this neatly.
The best way to present data is visually and Power BI is one of the best Data Visualization tools.
Prerequisites for importing LinkedIn Data into the Power BI Service for Visualizations
This is pretty obvious, but you will need to have a LinkedIn account and a Power BI Service account to import the LinkedIn Data into Power BI.
There are several different types of LinkedIn accounts:
- Premium Career
- Premium Business
- Sales Navigator
- Sales Navigator Team
- Recruiter Lite
These types of accounts come with different price tags and offer different options and services. Generally, a more advanced and more expensive type of account equals more options and tools and subsequently more data. All LinkedIn data can be integrated into Power BI.
When it comes to Power BI, there are three types of accounts, Power BI Free, Power BI Pro, and Power BI Premium. We don’t need to tell you that each account is an upgrade on the previous one, but we will tell you a bit about Power BI and its functions.
Data Visualization and Reporting in Power BI
In Power BI you can use data that comes from different sources and use it to create visualizations and present in different ways. Now, visualizations are the most interesting aspect, but we can’t just jump from the data to the visualizations.
There’s one step between the two – you can shape your data with queries that will enable you to build data models. These models then serve as a basis to create visualizations and reports. Visualizations are perfect when you want to spot patterns and irregularities, whereas reports allow you to dig deeper into certain aspects and metrics.
Now let’s go through the process of importing LinkedIn data into Power BI.
Importing LinkedIn Data into Power BI in 5 Steps
There is a detailed process that you need to complete to import your LinkedIn data into Power BI for Visualizations via Windsor.ai.
1. Once you’re logged into your Windsor.ai account, you will need to select LinkedIn as your data source.
2. Next, you need to click ‘Grant Linkedin Access”. As we said you can do this regardless of the type of account. Just type in your username/email and password and you’re good to go.
3. Now you need to select your Data Destination or in this case Power BI (either Desktop or Web)
4. Then you need to choose the data set that you want to import. There are plenty of options, in this case, you need to select LinkedIn as the primary data source, but you can also use blended data if you’re using data from multiple sources. There are plenty of options, so make sure that you choose the appropriate data.
5. The next and final step is completed in Power BI. If you’re using the Desktop version, you will need to copy the API URL that appears in Windsor.ai and then paste it into the URL field in Power BI.
If you’re using the Web version, you’ll just need the API Key.
And that’s it, as you can see the process is very simple. Once you have the data in Power BI you can start creating customized data visualizations or even generate templates that you can use later. All good decision-making is based on data, make sure that you have the right data and make the most of it.