Home SOCIAL MEDIA Data Analytics: How To Read LinkedIn Analytics

Data Analytics: How To Read LinkedIn Analytics

In the most popular “professional” social network, getting noticed is the essential requirement to increase one’s visibility: to verify the strategy’s effectiveness, various “analytics” tools can be used. Let’s see what they are and how to interpret the data made available.

LinkedIn is much more than a simple platform to find work or a social network to keep in touch with your customers. And it’s much more than an online resume, although many users tend to treat their LinkedIn profile as a simple list of skills to show off to potential clients or new employers. The platform offers unique versatility and, if used in the right way, can turn into a powerful digital marketing tool capable of boosting your career or company: LinkedIn Analytics.

In fact, in LinkedIn, it is important to have a well-defined strategy and understand what content and tools can make a difference. Having an updated and optimized profile allows you to create those relationships between contacts that have made this special social network successful. Getting noticed is the essential requirement to increase your visibility: to verify the strategy’s effectiveness, we can use various big data analysis tools. Let’s see what they are and how to interpret the data we have available.

How to interpret the information provided by LinkedIn Analytics

One of the most important tools to master (also one of the most underestimated) in LinkedIn is the so-called “Analytics”, a series of real-time statistics that allow us to understand if the strategy we have developed works results set ourselves.

To measure the effectiveness of our activity on Linkedin, the first thing to do is to change the chosen language setting and use our profile in English. Changing language is quite simple: you need to click on your profile photo to open a menu to make the change.

You have to select “English” and then go back to your profile page. By clicking on the sidebar on the right, we will finally have access to the precious statistics. On the company / institutional page, we will find a special Analytics section to filter the data based on three macro-groups: Visitors, Updates, Followers.

The platform shows by default the statistics for the last 30 days: it is possible to have detailed graphs up to one year, if necessary. From interactions to the percentage of interest up to the engagement rate (the rate of the engagement generated by content or activity), there is everything you need to monitor the effectiveness of the social strategy adopted by our company or by us.

The statistics available are related to all members registered on the platform, regardless of whether they are logged in from a normal browser on a PC or the LinkedIn and iOS app on a mobile device. It is important to remember that the so-called “traffic without authentication” of the profile is not counted.

LinkedIn Analytics is structured into three main categories

The interface proposed by LinkedIn is simple and functional (it is not at the level of the more celebrated Google Analytics). It allows the user in a short time to find out if some “insights” have been successful and, above all, to understand why certain contents work more and so on.

As for the profile, we have the statistics of those who have seen our or those relating to our company, as well as a special rank. Analytics allows the user to have the statistics related to posts under control from a quantitative perspective to study their effectiveness concerning links and the average of contacts. With the simple rank, in fact, we can find out in what percentage a personal / company profile is present in your network and the relative position in a hypothetical virtual ranking, as well as studying the trend in a specific or previous period.

To evaluate our activity it is necessary to analyze the information regarding the number of visits to our profile in a specific week (with lots of variations compared to the previous one), the number of shares / posts / updates we have made, the new links obtained, the number of comments generated and so on. By combining this valuable data, we can correct or improve our strategy.

The number of comments generated and so on. By combining this valuable data, we can correct or improve our strategy. The number of comments generated and so on. By combining this valuable data, we can correct or improve our strategy.


The platform offers a series of information and statistics on users who visit their company page on LinkedIn: just click in the Visitors section(Visitors).

The available data are related to the views obtained per page or to the number of unique users: in this way it is possible to understand who is close to our profile and which section has been appreciated the most.

The graphs can be customized at will to have even more detailed profiling. The demographic data of the visitors are very appreciated, which allow us to understand the place of origin, the job performed, the length of service, the sector, and the size of the company they work for (the strange thing is that the name is not available of the contacts following the page!).

In this way, we can understand if our profile has reached the right people, which sector our audience belongs to and in which geographical area it is most effective. LinkedIn Pulse, we can write original content and share it even more effectively.


Another important section of Analytics concerns the Followers that follow their company page. You can check the followers in a specific period and understand when they were gained or lost. In this way, we can understand if there is a close correlation between the increase or decrease in correspondence with the publication of specific posts.

Most importantly, you can analyze the variations in organic followers and those obtained through sponsored placements. This is an important difference because, as in other social networks, it is possible to “buy” followers on LinkedIn. As in the visitor’s section, in the follower’s section, it is possible to study the origin of the contacts, which professional category they belong to, and more. The section dedicated to the so-called “companies to monitor” is also interesting:


Another important category is related to “Updates,” Updates: here, you can find a series of information relating to organic and sponsored data. It is mainly used to understand how many users have seen, commented, or shared the posts and what level of interest and interaction they have generated. We have information on the total number and type of views, comments received, social shares and interactions, and much more. The graphs, of course, can be filtered to refine our social strategy further: it is important to remember that there is a precise correlation between the number of followers and the engagement rate.

How to interpret the data provided by LinkedIn Analytics

In general, a tool like Analytics can help us understand if the strategy we have adopted works through big data analysis. Thanks to the information we have obtained, we can find out at what time of day it is advisable to publish the posts, at what times and days of the week our updates are most successful. And above all, they are essential if we are to invest in some paid marketing campaign. With Analytics, we can analyze all content’s performance and compare between sponsored and organic ones.

By studying the reactions of followers and their trends and observing the trend of impressions of each update, we can determine if the content we offer is of quality and if LinkedIn appreciates it. For example, suppose we notice a drop in the overall number of impressions. In that case, the explanation is quite simple: the platform’s algorithms classify our content as not quality and limit their sharing. It is important to compare the data relating to your followers with that of visitors

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