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How Statlas Builds Your Data

Overview​

Statlas builds data from the ground-up. This allows for consistency among all the different reports and models. Order data is aggregated up from the order details; ad data is aggregated up from the ad or creative (In some cases we just pull campaign-level data).

Order Data​

Data is rolled up into Revenue​

The simplest application of order data is just aggregating all orders and displaying it as revenue. There are some caveats when comparing against source:

  1. Statlas excludes zero-dollar orders. Giveaways are considered marketing-driven orders in Statlas and often throw off other metrics. We always exclude these orders for data integrity purposes. For this reason, you should not expect Statlas to match gross and discounts if there are free orders. Free orders generally overstate gross sales and overstate discounts.
  2. Shopify Channels often exclude certain channels - It's generally best practice to exclude POS, wholesale, and draft orders. Many stores will exclude other irrelavant channels.
  3. API differences. For example, Shopify has some known issues with trying to replicate reporting using their Orders API: a. Duties, VAT rebates and taxes are often unevenly applied and will show differently in Shopify and Statlas b. Exchanges are often treated differently depending on how they interact with the system c. Discounts are not evenly applied. There are certain types of discounts not captured. Shopify will try to make some adjustments for these whcih are not always consistent with the API data we pull. d. Returns are often off. Some returns don't appear in the API.

Contribution Margin​

Previous sections showed how order data rolls up to revenue, but we use order data to get more insights to calculate contribution margin. Order counts and products are used to calculate COGS and Cost of Delivery. This is combined with Statlas settings and ad data to get contribution margin. Other settings may also decide how refunds and shipping interact with contribution margin calculations.

Order History is kept for each customer to calculate new vs returning and LTV​

Statlas uses order data to rebuild new versus returning databases. These sometimes cause discrepancies with various platforms for these reasons:

  1. Platforms will consider the free order / giveaway as a new customer whereas Statlas will not. This causes the next order to be considered a free order in Statlas.
  2. Platforms may use different logic when calculating first orders. One example is that Statlas will use the process date for determining the first order whereas Shopify will use the create date. We have found that using the create date causes issues when the first order never gets processed or got cancelled. Although this is generally immaterial, it does cause discrepancies.
  3. Statlas makes some adjustments to known issues. For example, we know TikTok Shops will return all emails as the same email address, but we know they are all different customers.

Order Line Items are catalogued for product analysis​

Statlas will also keep track of products. This data is combined with the product and variant feed to bring product-level insights. We're currently working on building this system into an even more powerful database. The product database keeps track of customer cohorts, as well as products.

Other Data Sources​

Statlas has other analytical databases that tap into order data. These include but are not limited to:

  1. Geographic data for geo-studies
  2. Hourly data for marketing operations during large sales
  3. Payment information
  4. Attribution information

Ad Data​

Varies​

Ad data really varies by platform. Although they have similar stats like clicks, CPM, and spend; Statlas treats each platform as its own domain.