Social media analytics developed quickly, leaving marketers with a dilemma. Digital marketers now have dozens of tools at their disposal, such as Sprout Social, Google Analytics, Hootsuite, and IBM Watson Analytics for Social Media, which provide valuable insights into customer and brand sentiment, brand awareness, and voice engagement. However, business-to-business (B2B) marketers rely on social media to drive demand and brand awareness, with Twitter and LinkedIn being our primary channels.
For business-to-consumer (B2C) companies, information (especially from Twitter and Facebook) is very valuable for defining and measuring ads and messages.
Unfortunately, LinkedIn is limited to analyzing organic updates, engagement, and activity.
LinkedIn recently expanded its conversion tracking service with sponsored (paid) updates. While this information is critical to measuring the ROI on LinkedIn’s advertising spend, the challenge is to measure the impact and impact of LinkedIn’s organic business.
As marketers, we are responsible for generating content and demand, and we know the impact LinkedIn has on reaching our audience, website traffic, and determining what content, features or campaigns are critical.
Solve LinkedIn’s organic measurement challenge
However, marketers don’t need to manually process data or make assumptions about their overall organic social media activity. With the advent of new self-preparing tools, marketers can record data in all different formats, including organic engagement information, directly from a company’s LinkedIn profile page and combine it with other data for visual analysis.
Whether the information comes from APIs, database files, web pages, or spreadsheets, with a data preparation tool, you can merge all these formats in one workspace and normalize and merge the data into something you can use to work and analyze.
With a data preparation solution, you can easily select all refresh statistics on the web page and then copy and paste them directly into a data preparation workspace, where they can be displayed in rows and clean columns. The information is then available in a workspace where it can be combined with other important datasets such as metrics from Twitter, Google Analytics, and Salesforce.com and then exported to a visual analytics dashboard.
Using this previously inaccessible data, marketers can make more informed business decisions and create a holistic campaign assessment that allows them to:
- Comparison of website traffic data from unpaid social media channels
- Identify which content and campaigns perform best
- Detect which channels are converting into leads, opportunities, and closed deals
Self-service analytics tools help marketers avoid wait times for IT execution and reporting on the latest campaigns. Basically, data preparation allows the marketing team to work with the data as effectively as the data scientists.
Measuring LinkedIn’s Impact: Some First-Hand Information
When marketers can correctly measure the impact of a marketing campaign or new content on a social platform, they can quickly divert their efforts to improve engagement.
For example, we recently promoted a new e-book and wanted to compare its performance with previous sources to measure whether the message was correct and determine the most successful channel. Our analysis, conducted across multiple lead generation channels including Pardot email, Google pay-per-click advertising, Twitter messaging, and organic engagement, revealed exceptionally good performance on LinkedIn. This positive result immediately inspired us to use the e-book in LinkedIn paid to advertise, lead generation campaigns, and other social media vehicles.
Without an analytic view, we wouldn’t know that expanding marketing can lead to greater audience engagement.
After further analysis, our reviewers were able to link to our site’s traffic and determine if they were looking for content outside of the specific post. That’s why we consider alternative call to action (CTA) phrases at the end of the article to help drive more traffic. In addition, we may contact commenters directly to offer a free trial, access additional resources, invite them to join related LinkedIn groups, or encourage them to become brand ambassadors.
The marketing team can optimize their use of paid LinkedIn updates to get high-quality, proven content and make informed decisions when planning future content.
Selection of data for an executable content view
Marketing continues to lead to many operational functions when using analytics. Analytics goes beyond individual data streams to selected and combined datasets and provides even deeper insight into what works with your marketing strategy. It all starts with a single question or objective, such as what content resonated last quarter; why the email rate was so low; or which social channel has the most efficient traffic.
Using self-service readiness tools, data-driven marketers can enrich their standard metrics with previously inaccessible data about LinkedIn’s organic activity, providing better insights and more reliable analytics to address these issues.