Turning Raw Data Into Valuable Insights
Next Big Shop tracks inventory and estimates sales. We also aggregate a host of additional metrics, for private and public DTC brands. Here's how we do it.
Weekly Inventory Crawling
We're building Next Big Shop to answer a question — how does a shop go from obscurity to popularity?
Most sales estimates of private DTC companies today are not reliable. The standard today for estimating sales is applying a conversion rate to web traffic or observing LinkedIn headcount (yes, really). We think there's a better way.
We're deploying a more accurate methodology for measuring sales: Inventory Depletion.
Total Inventory
Here's how it works:
  • Inventory is checked weekly and the difference from the previous week is calculated then multiplied by price of goods sold
  • SKU data is rolled up to products which are rolled up to stores
  • Inventory increases and decreases outside expected bounds are interpolated to account for non-sales impacts on revenue like restocks, returns, SKU consolidation, and inventory destruction.
Today, we only show sales based on the coverage we do have available. In the future, we will incorporate other signals like web traffic, social, and yes, LinkedIn headcount (cause, why not?) into our sales model.
Data Quality
Every shop profile page includes a data quality module with crawling status, crawling history, and any data confidence flags including Inventory Coverage and % Sales from Bundles.
Other notes:
  • Annualized sales is not the same as trailing 12 months
  • Data is DTC only, and if a merchant's inventory going to wholesale, FBA, or point of sale is managed in the same system, we'll count that too
Inventory Coverage
We have extensive or substantial coverage for 69% of shops.
  1. Extensive Coverage

  2. Substantial Coverage

  3. Partial Coverage

  4. Minimal Coverage

  5. Zero Coverage

Stores that are set up to keep selling after running out of inventory can appear to sell less than they are - we refer to the percentage of inventory we can track (not set to keep selling after running out of stock) as inventory coverage.
Depending on the total percentage of inventory Next Big Shop tracks for a given store, we assign a score from 0 to 100 and label our coverage from minimal to extensive. This shows in a badge below sales estimates at the top of shop profile pages and as a gauge in the data quality section.
We have five inventory coverage levels:
  1. Zero Coverage (0% Coverage)
  2. Minimal Coverage (Less than 25%)
  3. Partial Coverage (25% to 49%)
  4. Substantial Coverage (50% to 89%)
  5. Extensive Coverage (90% or more)
The pie chart above shows where all the shops we're tracking land within the levels.
Known Issues
We're communicating whenever we detect potential issues that can impact the quality of estimates.
Things to watch out for:
  • Stores continuing to sell after running out of stock. This is shown below every estimate via the inventory coverage from 0 to 100%
  • Stores with bundles appearing to sell more than they are. This is shown as a % of bundle sales and the label in the Best Sellers section
  • Shops with more than 5k SKUs. These shops are not being crawled unless requested
Future Improvements:
  • Showing stores that limit items per customer appearing to sell more than they are
  • Frequency of inventory syncing with third-party systems
  • Inventory shared across channels beyond DTC appearing high
As we continue to communicate about data quality, we'll keep this section updated.
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