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Your data is in and your first grid exists. This three-part guide walks one full pricing cycle: open the grid and read what the data says, run Price Optimization, then review and publish the prices you accept. Allow about 15 minutes. Start here once you have finished the Quickstart.

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Open a grid

  • Go to app.retailgrid.io. You land on Grids.
  • Each row is one grid, with its product count, the state of its price approval queue and its recent sales.
  • Click the grid name to open it.
A grid is a working set of products: the rows you want to analyze and price together. See Grids overview.
A grid open in Retailgrid with SKU, product, price and cost columns

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Read the columns

The first columns are your own data: SKU, Product Name, Brand, Price, Unit Cost and your catalog attributes. Scroll right and the columns are grouped by what produced them:
  • Metrics - values calculated from your data, such as Unit Margin %. See Metrics.
  • Market Data - what competitors charge, including Price Range and Competitor CPI (Min). Price monitoring keeps these fresh.
  • Product Roles - the role each SKU plays, such as KVI, Traffic, Profit or Niche. See Product roles.
  • Price Approval - proposed prices, once an agent has run. You work there in part three.
Use Columns to show or hide columns and Filters to narrow the rows. Save a layout you keep coming back to as a view.
The TOTALS row at the bottom recalculates on whatever is filtered, so you can size a category before you price it. See Totals row.

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Check a product in the charts

Click a row to select it, then open the analytics panel from the chart icons at the bottom of the grid. Four tabs cover one SKU at a time:
  • Competitor prices - your price against each competitor over time.
  • Sales & price - units sold against your price and the market average. This is where you see how volume responded to past price moves.
  • Profit & price - margin and gross profit at those prices.
  • Forecast - projected units at the current price.
Set Timeframe (26w, for example) and Aggregation (daily, weekly or monthly) in the panel header.
Sales and price chart for one SKU, with units sold as bars and price as a line
Two things are worth a look before you optimize: whether your price sits above or below the market, and whether units actually moved the last time the price changed. The demand model reads the same history. See SKU analytics panel.

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Next

Run the optimizer on this grid: Run Price Optimization.