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Product Case - Linkedin
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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Product Case - LinkedinProduct Case - Linkedin

Design the algorithm to recommend new connections to LinkedIn users.

Product Case - Linkedin
Product Case - Linkedin