FULL TUTORIAL: Price Elasticity and Optimization in Python (feat. pyGAM)

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  • Опубликовано: 11 окт 2024

Комментарии • 23

  • @hassanjaved4091
    @hassanjaved4091 6 месяцев назад

    Great content Matt! I have learnt a lot and thank you for putting out such detailed lectures.

  • @hellskitchens
    @hellskitchens 10 месяцев назад

    Great example of price optimization. I work for a global retailer and work heavily on data science tools. Its great to see other methods and ways to improve. Keep going! I can tell you 150k is just the beginning!

  • @starshipdestroyer1170
    @starshipdestroyer1170 11 месяцев назад +1

    Could you please share the link for accessing the data and python code related to Price Elasticity and Optimization? or any process to get atleast data?

    • @BusinessScience
      @BusinessScience  11 месяцев назад +1

      You will need to become a learning labs pro member. university.business-science.io/p/learning-labs-pro

  • @pallaviharishchandre3021
    @pallaviharishchandre3021 3 месяца назад

    Extremely informative and well explained. Thank You!

  • @robertsienkiewicz8063
    @robertsienkiewicz8063 9 месяцев назад

    Great video. One question. Often times prices are not set out for equal periods of time. Therefore a decline in qty doesn’t really mean much if the price was only valid for a couple days. I think really the only way around this is adjusted for the time period and seasonality. Any recommendations on how to approach this?

  • @youhavebewarned
    @youhavebewarned 11 месяцев назад +4

    Thank you algorithm for guiding me here.

    • @BusinessScience
      @BusinessScience  11 месяцев назад +1

      You got it! Thanks for watching. 😀

  • @spikeydude114
    @spikeydude114 11 месяцев назад

    Am I off base to try to analyze sales compared to 'economic strength'? So instead of price vs volume I would do sales vs inflation rate...is that possible with this approach?

    • @BusinessScience
      @BusinessScience  11 месяцев назад +1

      No I dont think you're offbase. I would test adding columns in for different days. For example if you have pricing data in different quarters or even month and the inflation rate is changing, add that in as a column. There also may be lag effects or leading effects so add lags/leads as appropriate.

  • @arturocdb
    @arturocdb 11 месяцев назад +5

    Universiyy is antiquate?... i just want to let you know that price optimization only applies on monopolistic scenario?... i learn that in a basic micro economics course in university, i recommend you to take a baisc course in economics, because the model that you are showing only applies to monopolistic market case.... you did not mention that litle detail...i'm data scientist specialized in pricing, i can teach you some really cool thing than can be a applied to a real world problems...., your code can not be applied...

    • @BusinessScience
      @BusinessScience  11 месяцев назад +3

      That’s great. Except you left out one small detail - where is your tutorial?

    • @superuser8636
      @superuser8636 11 месяцев назад +2

      @@BusinessScienceI got you but don’t even play this guy’s game. But he does have a point. I do think university is useful but it isn’t a barrier to entry anymore when there are amazing tutorials like this that really CAN make 150k$+… That means people like me have to compete and get a higher level of education beyond a bachelors since courses like these are so great. That doesn’t take away from the amazing contents of this course and I’m sure you give more information in the courses than this FREE FULL tutorial… but still, 6+ years of university is tough to compete with with 15-30 weeks of education but you really distill probably 4 years of techniques and for that, I salute you 🫡 That is to say, I have learned a lot from your videos as a professional myself

    • @BusinessScience
      @BusinessScience  11 месяцев назад +2

      Thank you for this! I see a lot of negativity these days and it baffles me. Comments like this really help put things into perspective. Thank you!

  • @flyingdutchman9804
    @flyingdutchman9804 10 месяцев назад

    Hey, bud, I love your projects section and the work that you put into it!! I have a genuine question. - This is nice and all, but steps 1-7 in the DS process are fairly straightforward and standard (some may argue that steps 3 and 4 may be combined). How is this worth $800 when someone can easily complete steps 1-7 and simply learn how to format and map results to Streamlit? I am curious because all the libs are open source, and there are abundant free resources for Streamlit (worst case scenario, a Udemy course on Streamlit is $10-$15.

    • @BusinessScience
      @BusinessScience  10 месяцев назад

      When we get you a data science job, that’s $100K to $150K - and the price that you pay $800 seems reasonable to us. But yes, good luck with udemy or any of those programs. If you can get a job, then go for it. When you can’t, we will be here.

    • @flyingdutchman9804
      @flyingdutchman9804 10 месяцев назад

      ​@@BusinessScience Already secured one using Google/docs/stackoverflow/RUclips/udemy/Kaggle :) Just interested in learning more. Pardon my confusion. Are you claiming that you get students a Data Science job or a money-back guarantee when you say, "When we get you a data science job, that’s $100K to $150K"? - If so, this might be a great deal, and I may be able to send a few people your way!

  • @AkashBiswas-r2l
    @AkashBiswas-r2l 10 месяцев назад

    please provide the dataset

    • @BusinessScience
      @BusinessScience  10 месяцев назад

      It’s available in Learning Labs Pro. You can become a member here: university.business-science.io/p/learning-labs-pro?el=youtube

  • @tighthead03
    @tighthead03 11 месяцев назад +1

    When can we expect the superior language version to be uploaded??😂

    • @BusinessScience
      @BusinessScience  11 месяцев назад +1

      It might be coming tomorrow. ;)

    • @tighthead03
      @tighthead03 11 месяцев назад

      @@BusinessScience great stuff Matt I'm looking forward to it