Pricing Analytics: Are You Leaving Money On The Table?

In this video, we review analytical methods used to measure price elasticity and explain how price elasticity can used to support business pricing strategy, whether for an existing product line or for a new product.
We will discuss several of the most important strategic-pricing objectives that firms often set as they pursue a business strategy. In particular, we will outline several analytic methods used to measure price response, providing pros and cons, advantages and disadvantages, providing examples along the way.
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[@chrispachas8486]

Very very good explanation! Thanks a lot guys! Blessings

[@DecisionAnalystArlington]

Glad you liked it!

[@Ali-bk1hr]

Hi I have a data analyst degree and can code but I do not have a maths background such as calculus, linear algebra, statistics etc. Is this something that’s heavily part of the job or can I apply?

[@stoneage8810]

Thanks for sharing, just a quick question regarding price elasticity, to calculate it we need to choose two time periods and see how things are changing right? if we choose period A and B, there is a value, if we change to period A and C or B and C, the elasticity result can be quite diff. So over time this is quite dynamic, how do we approach this variance problem and get a reliable elasticity estimate ?

[@DecisionAnalystArlington]

Thanks for your question. One would expect that the impact of a price change manifests over time since buyers would not, typically, be immediately aware of the price change.
When price elasticity is based on stated choices in a survey, one approach is to include an awareness-build over time to the simulation equations to simulate short- or long-term impacts of price changes. The survey results, unadjusted, are more representative of a long-term price impact since survey respondents are 100% aware of prices.
When price elasticity is estimated based on econometric modeling of historical data, distributed lag models are often used to account for lagged impacts of a price change.

[@stoneage8810]

@@DecisionAnalystArlington thanks, i suppose survey based result is more accurate but hard to obtain.... result based on historical data, elasticity between 2021/2022 can be very diff from that of 2022/2023, having time series data can produce many diff results.. will take a look at the distributed lag models you referred to