Methodology: Ecommerce Data Calculations

This section goes out to all our fellow data nerds … plus, anyone who wants to better understand the charts and graphs contained within the reports.

Ecommerce Data Calculations are based primarily on Statlas: our proprietary ecommerce growth tool composed of data from Common Thread Collective (CTC) clients, ADmission members, and Statlas users.

To pull together the full story, we rely on ~300 ecommerce businesses, the experience of our analysts, and a pinch of CTC data magic.

Inclusion

To be included in Ecommerce Data, stores must meet three requirements …

1. Report revenue OR Facebook Spend OR Google Ads Spend for all but 4 days between January 1, 2020 and the end of the most-recent week 

   And

2. Be consistently reporting and connected to Statlas for at least the last month; stores must be eligible for our dataset for 1 month prior to being added to that dataset

   And

3. Be included in the list of currencies we can convert:

   1. USD - United Stated Dollar (Dolla Dolla Bills, y’all)
   2. JPY - Japanese Yen
   3. BGN - Bulgarian Lev
   4. Cypriot - Cypriot Pound (now the Euro)
   5. CZK - Czech Koruna
   6. DKK - Danish Krone
   7. EEK - Estonian kroon
   8. GBP - Pound Sterling
   9. HUF - Hungarian forint
   10. LTL - Lithuanian litas
   11. LVL - Latvian lats
   12. MTL - Maltese lira
   13. PLN - Polish złoty
   14. ROL - Romanian leu
   15. RON - Romanian leu
   16. SEK - Swedish krona
   17. SIT - Slovenian tolar
   18. SKK - Slovak koruna
   19. CHF - Swiss franc
   20. ISK - Icelandic króna
   21. NOK - Norwegian krone
   22. HRK - Croatian kuna
   23. RUB - Russian ruble
   24. TRL - Turkish lira
   25. TRY - Turkish lira
   26. AUD - Australian dollar
   27. BRL - Brazilian real
   28. CAD - Canadian dollar
   29. CNY - Renminbi
   30. HKD - Hong Kong dollar
   31. IDR - Indonesian rupiah
   32. ILS - Israeli new shekel
   33. INR - Indian rupee
   34. KRW - South Korean won
   35. MXN- Mexican peso
   36. MYR - Malaysian ringgit
   37. NZD - New Zealand dollar
   38. PHP - Philippine peso
   39. SGD - Singapore dollar
   40. THB - Thai baht
   41. ZAR - South African rand

Formulas

Here’s a rundown of the formulas we use to calculate the Ecommerce Data …

Average Weekly Ecommerce Revenue

Total Ecommerce Revenue ÷ Total Stores reporting

Average Weekly Channel Spend

Total Channel Spend ÷ Total Stores reporting

Average Weekly Channel CPMs (Cost per 1000 Impressions)

(Total Channel Spend x 1000) ÷ Total Channel Impressions

Average Weekly Channel ROAS (Return on Ad Spend)

Total Channel Revenue ÷ Total Channel Spend

Average CPC (Cost per Click)

Total Spend ÷ Total Clicks

Average CTR (Click through Rate)

Total Channel Clicks ÷ Total Channel Impressions

Average CR (Conversion Rate)

Total Channel Buys ÷ Total Channel Clicks

MER (Marketing Efficiency Ratio)

We employ three parameters before calculating:

1. Filter out all stores with average MER above 14
2. Filter out all days with MER above 16
3. Calculate MER for each store and take the average MER of that MER

(Σ All Stores(Total Store Revenue with Spend ÷ Total Store Ad Spend)) ÷ Number of Stores

Average AOV (Average Order Value)

Total Revenue ÷ Total Orders

Average Weighted CAC (Cost of Acquired Customer at the store level)

Total Ad Spend ÷ Total Customers

Average CPA (Cost Per Acquisition calculated directly from Facebook and Google reporting)

Total Ad Spend ÷ Total New Customers

aMER (Acquired Marketing Efficiency Ratio)

Total New Customer Revenue ÷ Total Ad Spend

Understanding How These Metrics Impact Your Business

We’ve covered a lot of data points, formulas, and metrics in this methodology. But, ultimately, our goal is to help you understand how these metrics play into the success of an overall campaign. 

The best way to do that?

Plug them into the equation for channel ROAS. 

From a high level, the ROAS formula looks like this: 

ROAS = Revenue ÷ Spend

By decomposing the equation, you can see how different parts of the funnel are performing by breaking down “revenue” and “spend” into some of the metrics we previously mentioned. 

ROAS = (1 ÷ CPC) x CR x AOV

The equation can be decomposed even further, pulling in CPM and CTR:

ROAS = (1000 ÷ CPM) x CTR x CR x AOV

So, why should you care about all of these metrics?

Because every single one of them contributes to the success of an ad campaign. And, understanding what each metric means — and its importance within the overall health of your business — enables you to pinpoint the exact areas of improvement on a granular (and more tangible) level.