Skip to content
  • There are no suggestions because the search field is empty.

Predict: Browse Stores

Apply filters to explore stores, understand AI predictions, and quickly identify locations at risk.

1. Purpose of Browse Stores

The Browse Stores page helps users understand AI predictions at the store level based on the filters they select.

This page is designed to make it easier to review store-level risk, compare predicted demand against available stock, and identify which stores may require action.

Browse Stores is especially useful for:

  • understanding AI predictions for the current filter set

  • reviewing stores across a selected retailer, region, category, or product scope

  • identifying stores that may not have enough stock on hand to meet predicted sales

  • prioritizing fast action on stores most likely to need attention

This page supports quick decision-making by combining AI summaries, store-level metrics, and a detailed store list in one place.

2. Filters

At the top of the page, users can apply filters to define the scope of the stores they want to review.

Filter groups include:

2.1 Merch Hierarchy

  • All Categories

  • All Subcategories

  • All Products

These filters help users narrow store predictions by merchandise scope.

2.2 Location

  • All Retailers

  • All Regions

  • All Stores

These filters help users focus on a specific retailer, geography, or store set.

2.3 Prediction Model and Severity

  • Weather Forecast

  • All

These filters allow users to review stores based on the selected prediction model and severity level.

2.4 Time Range

  • Next 7 days

This determines the forecasting window used for the store-level predictions shown on the page.

2.5 Remember My Filter Selections

Users can enable Remember my filter selections to keep their preferred settings for future visits.

3. Smart Summary Panel

The Smart Summary Panel provides AI-generated takeaways based on the currently selected filters and store results.

This section is labeled AI-powered insights ready to share and helps users quickly understand the overall story behind the current store set.

The panel includes:

3.1 Quick Takes

Short, meeting-ready bullets that summarize the most important patterns in the current filtered results.

3.2 Data-Driven Summary

A more detailed narrative explaining what the AI is seeing across the selected stores.

3.3 Tips & Recommendations

Suggested next steps based on current store conditions and predicted demand.

This section is especially useful for helping users move from analysis to action faster.

4. All Stores vs Stores at Risk

The Stores List section includes two toggles:

  • All Stores

  • Stores at Risk

These toggles help users switch between a complete view of stores in scope and a focused view of locations that may require action.

4.1 All Stores

The All Stores view shows every store included in the current filter set.

This is useful when users want to:

  • review the full store population in scope

  • understand overall coverage

  • compare healthy and at-risk locations together

  • assess the broader network before narrowing to issues

4.2 Stores at Risk

The Stores at Risk view narrows the list to stores that are flagged as needing attention.

A store is considered at risk when it does not have enough stock on hand to meet AI predicted sales within the selected forecast window.

This view is especially useful when users want to:

  • quickly isolate problem stores

  • identify where inventory may be insufficient

  • prioritize replenishment or inventory reallocation

  • make faster operational decisions

This distinction is important because it allows users to either review the full network or focus only on stores where action may be required.

5. Summary Cards

Above the store table, summary cards provide a quick overview of the stores currently in scope.

These cards include:

  • Total Stores

  • Total Stock on Hand

  • Total Predicted Sales

  • Total Recommended Order

  • Net Position

These metrics help users quickly understand:

  • how many stores are included

  • how much inventory is currently available

  • expected sales across the forecast window

  • whether additional ordering is recommended

  • the overall inventory position

This gives users an immediate high-level view before reviewing individual stores.

6. Stores List Table

The Stores List table provides the detailed store-level results for the selected filters.

Users can click a row to view store details.

6.1 Table Columns

The table includes the following columns:

  • Store Name

  • Region

  • Risk Status

  • Weather Condition

  • Weather Probability

  • Time Horizon (weeks ahead)

  • Revenue Impact

These columns help users evaluate store-level risk and understand which conditions may be contributing to forecasted performance.

6.2 Risk Status

The Risk Status column highlights whether a store is currently flagged, such as:

  • At Risk

This helps users identify which stores may need closer review.

6.3 Weather Context

The Weather Condition and Weather Probability columns provide additional context about the local weather conditions influencing demand forecasts.

This is especially useful when using a weather-based prediction model.

6.4 Revenue Impact

The Revenue Impact column helps users understand the possible financial effect associated with each store’s forecast and risk level.

7. How Browse Stores Supports Quick Decisions

The Browse Stores page is built to help users make faster, more targeted decisions.

By combining filters, store toggles, summary metrics, and AI-generated analysis, users can quickly:

  • understand what the AI predicts for the current scope

  • identify stores with insufficient stock relative to predicted sales

  • focus on the subset of stores most likely to require action

  • evaluate store-level risk in the context of weather and forecast horizon

  • move from broad network review to targeted operational follow-up

8. Using Browse Stores Effectively

Browse Stores is most effective when users start with filters that reflect the business question they want to answer, then switch between All Stores and Stores at Risk to compare the full picture against the priority set.

Used effectively, this page allows teams to:

  • understand AI predictions for their selected filters

  • isolate stores that may not have enough stock on hand

  • prioritize replenishment and inventory decisions faster

  • use AI summaries to support quick alignment and action

By surfacing both the full store set and the at-risk subset, Browse Stores helps users make quicker and more confident decisions.