Product Case - Linkedin

Design the algorithm to recommend new connections to LinkedIn users.
01 Outcome
Specify the outcome for the Persona(s) for whom Linkedin builds its current suite of products. Keep in mind that we are not focussed on the outcome for the company only for the end user.
02 Available Opportunities & Validation
Based on the Persona describe the “jobs to be done” that these persona’s have. What primary research have you do both qualitative and quantitative that supports the opportunity that you have selected.
03 Alternatives and Assumptions
Describe why you will not choose to pursue some alternatives.
04 Roadmap
Desricbe how did you go about doing product discovery? How do you decide what and what not to build? What is your approach on taking feedback from customers?
05 Success Metrics
Describe the success metrics for your Roadmap (defined above)
06 What we are not doing?
Finally, describe the anti-persona and therefore features you will not be building.
Outcome

LinkedIn Algorithm for New Connections
Outcome
New relevant connection per day/week/month
Relevance for the user → Ask the user
— Work remotely
— Salary
— Title
— Profile → 10 years in Product Mgmt. Companies
Four Personas
Jobs Seekers
Manage my reputation
Sales people
Recrutiers
First → Understand the user persona
Second → New relevant connection per day/week/month
Third → A/B test and get feedback
Fourth → Loop back
understand_persona()
{
Intent → Job Seeker →
Searching for jobs → Extract Meta Data from these searches
Capture Signal Profile has Open to Work →
Frequency → Based on searches in the last week
Recency → Last search that they did
...
}
relevant_connection ()
{
persona = understand_persona();
Intent → Hiring
Searching for candidates
Contacting Recruiters
...
}
Test ()




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