ZEROCAST Burndown Trend Predictor Back

Example datasets

Three sample datasets for the kinds of counts ZeroCast is built to forecast. Click Plot to open one straight in the app's dashboard, or download the CSV to see how ZeroCast's own upload zone handles it. Each file uses the Date,<label> format ZeroCast expects, and each column header becomes that column's chart label; add more than one count column, as the store inventory dataset does, and every column plots as its own trend line.

Store inventory burndown

Plot CSV

Weekly stock counts for two SKUs selling through side by side, with no restock in the data. A date column with more than one count column plots a trend line per column, so this one doubles as the multi-line example: Widget A sells through fast, Widget B more gradually, and each gets its own stockout projection.

Date,Widget A Stock,Widget B Stock 14 weekly rows 474 → 70 / 620 → 405 units

Bug backlog burndown

Plot CSV

Open bug count from a QA tracker, taken weekly. The trend isn't perfectly smooth — some weeks rise as new bugs are filed faster than they're fixed — which is a good test of how ZeroCast's fitted line handles noisy, real-world data.

Date,Open Bugs 16 weekly rows 319 → 197 bugs

Startup cash runway

Plot CSV

Month-end cash balance for a startup burning roughly $90-100K a month. This is the case ZeroCast's name comes from most directly — forecasting the date the balance hits zero, and what monthly burn a specific target runway date would require.

Date,Cash Balance (USD) 12 monthly rows $1.2M → $56K

How to use one

  1. Plot opens the app with that dataset already loaded — no download or upload needed.
  2. Or download the CSV and drop it onto the upload zone yourself (or click it to browse), the way you'd load your own data.
  3. Check the Trend ETA, then try setting a Target ETA in the sidebar to see the burn rate it'd take to hit that date.