Product Improvement Mock Interview with Archana Panwar, SPM at Axis Bank | PM School Mock Interview

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  • čas pƙidĂĄn 21. 07. 2024
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    Watch as Archana Panwar (SPM at Axis Bank) talks to Khanjan (PM at Razorpay) about a mock case on Product Improvement of Facebook's Birthday Feature!
    Timestamps:
    Introduction: 00:00
    Case question: 00:50
    Clarifications: 01:15
    Structure: 06:20
    Persona and pain points: 07:55
    Improvement Features: 19:18
    Prioritization: 28:43
    Success Metrics: 36:05
    Summary: 41:34
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    Speakers -
    Archana Panwar / archana-panwar
    Khanjan Desai czcams.com/channels/E2g.html...
    PM School is the leading platform for Product Management aspirants in India, founded by BITS Pilani and IIT Bombay graduates. We believe Product, as a discipline, is best taught by industry practitioners. Our Live Program has produced PMs who now work at top companies like BYJU'S, Reliance Jio, Ninjacart, Games24x7, Classplus and Freecharge to name a few.
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    #Tech​ #Product​ #MockInterview​ #Mock​ #ProductImprovement #ProductManagement​ #PM​ #PMSchool​ #LeadTech
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Komentáƙe • 10

  • @pmschoolx
    @pmschoolx  Pƙed 2 lety

    🚀 Take the 1st step in Product Management with our Live Program - pmschool.io/course/
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  • @NitinSehgal88
    @NitinSehgal88 Pƙed 3 lety +7

    Sometimes it feels interviewee is taking the interview 😂

  • @stevenspellberg
    @stevenspellberg Pƙed 3 lety +4

    Loved Archana's approach. Methodical, Structured and most importantly - Well Articulated

  • @gauravjain24
    @gauravjain24 Pƙed 3 lety

    Very well structured

  • @nikhilgupta6763
    @nikhilgupta6763 Pƙed 2 lety +1

    I think we get notifications from app about birthdays, the first problem statement Archana mentioned

  • @user-vd3qo2th9z
    @user-vd3qo2th9z Pƙed 8 měsĂ­ci +3

    Not a Quality PM Interview from some coming from Axis Bank..seems pretty average.

  • @shubhammeshram2944
    @shubhammeshram2944 Pƙed 3 lety

    In the before and after analysis, the numbers in the after implementation might look improved, but then there could be other factors as well that might have been responsible for increase in number. How do we identify what percentage of the increase is number is due to our feature implementation?

  • @aakriti360
    @aakriti360 Pƙed 2 lety

    How do you make sure that the person doesn’t feel threatened if you are using personal information to auto fill their birthday wishes?
    Will machine learning be able to achieve this or you need a human at the other end of the system to accomplish this?