+1 vote
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    asked in Strategy by (1.2k points) | 720 views
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    Bijan, which framework would you recommend for a question like this? Thank you!

    4 Answers

    +2 votes

    Clarifying questions
    By assessing impact means change in spending last winter vs previous winters and whether the change was because of weather?

    1. Any geography or all?
    2. Any specific category?

    Steps
    1. Spend means – Change in spending on goods(essential & non-essential), Change in spending on services(vacation travel/hotel), Change in seasonal spending
    2. Look at YoY spend during the same period.
    3. Look at change during holiday period when spending peaks
    4. Look at environmental factors such as unemployment, recession, war etc…
    5. Look at weather related issues such as storms, harsh winters etc…
    6. Look at spend on essential vs non-essential items. Essential means groceries vs non-essential means luxury goods, clothing etc…
    7. Look at spending across diff. geographies. Especially areas with severe winters vs low winters.
    8. Look at other factors such as change in tariffs, taxation which can contribute to pricing thus spending spending.

    answered by
    +1 vote

    How would you asses the impact of weather on consumer spend – You first ask clarifying questions – What is consumer spend- Can we assume retail spend across all categories and across ecommerce and brick and mortar? If Yes, What is winter? Which place is this? Is it October to November in US because Winter in India or Australia could be different or is this generic winter in any place? And then the most important question of all – What do you mean by Impact? Typically, you have forecasts of consumer spend – How much you thought consumers would spend as a whole or by category or by demographic or geo location etc. You also take seasonality in to account as you forecast. When the actual number is different from forecast, you try to attribute the forecast error to various factors and weather could be one of them. So you first look at actual weather vs forecast – was it an exceptionally cold winter, was it a hotter winter than expected? This would typically manifest itself by people buying more or less of winter specific products – like clothes, food, furniture. You can also look at the regular products such as toilet paper, bread etc that people buy irrespective of weather and see if they met forecasts or if people could not shop because of bad weather and they were impacted as well… I would do a forecast vs actual analysis and then do specific weather related attribution to the forecast error

    answered by
    0 votes
    Agree with the framework other two contributors have made. I would add that often when you are comparing weather patterns, you typically also look at sales per day either for a category or group of products and try and correlate to the actual weather for that day e.g precipitation level, low minimum temperature etc, look at trend within the month and yoy comparison. Important to isolate the contribution from seasonality.
    answered by (15 points)
    0 votes
    Previous contributors pointed out interesting ideas about the range of possibilities for choice of anlytics. But, I think there is a major difference whether we are looking at this question as a predictive experiment or as an observational analysis. If we do the former, we may be able to test hypothesis about the causal relationship between whether and spending. But, if we look at the data retrospetively, we can only talk about it in terms of possible correlations, which may or may not be causal.

    I think a meaningful research into the impact of wearther on consumer spending needs designing an experiment in one geographic locations to minimize the impact of socioeconomic factors. Daily or time-interval data can be collected over few years, for certain weather related factors such as rain, cloud, excessive cold, wind etc, And, as other contributors pointed out, for various types of products (essential, non-essential, etc.). Regression analytics should be used to define causal relationship between these weather parameters and spending in each category.

    If the study is retrospective, then I would also think of limiting the study in one geographic location to minimze the complicating impact of the wide range of socioeconomic contributing factors, such as income, weather differneces, social habits, etc.
    answered by

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