Report Price Elasticity of Demand

[philliptrost]

I'm building a promotion performance workspace for my customers and would love to include data that calculates the Price Elasticity of Demand (PED) during the promotion period. I'd most likely break it down by category and product, but that's secondary to just getting it to work overall. My preference is to perform the work in Analytics and not to export to Excel or Power BI.

I'd prefer to use the simple method: PED = (% change in quantity demanded) / (% change in price)

Any advice from other eCommerce analysts out there on promotion tracking workspaces and specifically PED?

[Jennifer_Dungan · Accepted solution]

I don't work with this type of math directly in our business, but I am trying to think about this... I am trying to figure out how to get the % Change in Quantity Demanded, I assume that would maybe be a simple cart additions, or product views, etc? Something that you can pull in Adobe from your data and compare between two date ranges....

But I am getting stuck on how you would get the % Change in Price.... You can't use date ranges directly in calculated metrics, but you can create segments that use Date Ranges.... Let's use "Last Week" and "2 Weeks Ago" as a sample...

Create a segment which just uses the "Last Week" Date Range, and another using "2 Weeks Ago":

Now, create a calculated metric that calculates a percent change based on the price of your product?

[

    (Last week) (Price of Product)

    -

    (2 weeks ago) (Price of Product)

]

/

(2 weeks ago) (Price of Product)

This is assuming your price is stored as a number and can be used in calculated metrics in this way....

IF you can get both those values as calculated metrics, you should be able to create a third calculated metric dividing the two of them.....

This is all in theory of course... I don't really have any data to test this...

If you can't get your prices as numeric values, you may have to fake it by adding them as static values.. but then you would have to do for each product and keep it manually updated....

I am worried though that this won't work, and you will need to pull out to an external tool...

Good luck, I would love to know how you make out with this.

[philliptrost]

Hey Jennifer, thanks so much in advance!

Regarding calculating Change in percent Demand, you are correct - I'll simply compare the difference between volumes use appropriate date ranges ( xx days before promo period, xx day promo, xx days following promo period). I'll do this for Carts, Checkouts, Orders, etc. Easily done in freeform tables and maybe a vis or two.

I'll continue working on the second part Change in percent Price, as this is the main challenge within AA. Not hard to do in Excel or Power BI . . . so I at least have ways to validate it I'm getting close!

[Hemang35]

Assuming you have these metrics in Adobe Analytics, you can follow these steps to create a calculated metric for PED:

Create calculated metrics for the percentage change in quantity demanded and the percentage change in price.

% Change in Quantity Demanded: Create a calculated metric using the formula ((Quantity Demanded - Previous Quantity Demanded) / Previous Quantity Demanded) * 100. In Adobe Analytics, this would look like ((metric1 - lag(metric1, 1)) / lag(metric1, 1)) * 100, where metric1 is the quantity demanded metric.

% Change in Price: Create a calculated metric using the formula ((Price - Previous Price) / Previous Price) * 100. In Adobe Analytics, this would look like ((metric2 - lag(metric2, 1)) / lag(metric2, 1)) * 100, where metric2 is the product price metric.

Create a calculated metric for PED using the formula (% Change in Quantity Demanded) / (% Change in Price). In Adobe Analytics, this would look like calculatedMetric1 / calculatedMetric2, where calculatedMetric1 is the % Change in Quantity Demanded and calculatedMetric2 is the % Change in Price.

Add the PED calculated metric to your workspace, and break it down by category and product.

Once you have set up the calculated metrics, you can analyze the PED in Adobe Analytics Workspace during the promotion period. This will provide valuable insights into how price changes affect the demand for products during promotions.

Keep in mind that the quality of the results will depend on the accuracy and granularity of your data.

[philliptrost]

I'm working through the calculated metric builder now; I'll admit my experience utilizing functions in Adobe is pretty basic - although I can create custom metrics/segments without much trouble. I find making DAX measures and M code in Power BI much easier - but glad to stretch a bit!

Q: When you refer to lag, I'm unable to locate this function in the metric builder or by adding it to the definition space. Is this formula known by another name in AA or perhaps unavailable? I hope I'm missing something basic and the response is not just from ChatGPT. . . I just don't have time for that.

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