LinkedIn Recruiter is a powerful platform for recruiters to connect with potential candidates and manage talent acquisition. To assess your team's performance, we will analyze a LinkedIn usage report and derive valuable insights using four key metrics. You can, of course, make more metrics or develop some of your own.
Combining these metrics and incorporating additional considerations will generate graphs and identify the top x over-performers and the top x team members who may benefit from additional coaching and training.
I use ChatGPT Code interpreter to generate these insights for me. And it's saving me a lot of time and effort. You can even ask it other questions based on the data.
Here is a how to do this, step-by-step.
Step 1: Exporting the LinkedIn Usage Report
- Log in to your LinkedIn Recruiter account.
- Navigate to the dashboard or reporting section.
- Locate the option to export a usage report: for at least three or better six months.
- Export the report in a compatible format, such as Excel.
Step 2: Data Preparation
- Open the exported LinkedIn usage report in spreadsheet software (e.g., Microsoft Excel or Google Sheets).
- Review the data to ensure it contains the necessary metrics and no data inconsistencies or missing values.
- Clean the data if required by removing any irrelevant columns or rows.
Step 3: Upload the data in ChatGPT Code Interpreter
(you need to have ChatGPT Plus)
- Upload the Excel (or CSV) file with the + sign.
- Add the following prompt into the "Send a message" box and press enter.
Here is a report of a LinkedIn Recruiter account. I want you to analyze all the information there. Four key metrics:
#1: The number of saved profiles divided by the number viewed should be as high as possible. Combine this number with the number of searches performed. This indicates that recruiters can search for the right target audience.
#2: The number of messages sent divided by saved profiles must equal or exceed 1. This indicates that all the saved profiles are at least messaged one or more times.
#3: The number of messages sent is a good metric. Combine this with a high number of messages accepted, which indicates that they are performing well. If they send many messages and a low number of acceptance, it shows they are spamming their talent pool.
#4: The number of searches and search alerts saved indicates that they automate some of their stuff.
Can you develop the graphs based on the four metrics above and anything you can combine yourself?
And give a list based on these metrics (can be one and all four) above the top 3 top performers and the top 3 who need additional coaching and training. And please provide in which areas the top 3 need extra coaching and training in.
And sometimes, you need to ask ChatGPT additional questions. You will learn by doing.
These are some of the results:
This indicates what kind of recruiters / sourcers in your team use the LinkedIn Recruiter account correctly. And with additional LinkedIn Recruiter training, you can get more out of this considerable investment.
It doesn't say anything about the overall performance of the individual recruiter or sourcer. You need to look at many other performance aspects of the individual.