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The Data Playground is Explorer’s open-ended workspace — direct access to your KPIs and dimensions without a fixed analytical structure. Use it to build custom views, compare unrelated metrics, or test a hypothesis that doesn’t fit a standard Top Story or dimensional breakdown.

How to use Data Playground

1

Select your dataset

Click the Dataset dropdown in the upper right and choose the data source you want to analyze. This scopes the entire Playground to the KPIs and dimensions configured for that dataset.
Opening the Dataset dropdown and selecting a data source in Data Playground
2

Pick a KPI from the selection panel

Use the KPI selection panel on the right to find and select the metric you want to track. The chart loads immediately with the KPI’s full timeseries across your dataset’s configured granularity.
Browsing the KPI selection panel and choosing a metric to load in the chart
3

Add more KPIs to compare side by side

Select additional KPIs from the panel to overlay them on the same chart. Each metric appears as a separate series, letting you spot correlations or divergences across your business at a glance.
Selecting multiple KPIs and watching each new metric appear as a series on the chart
4

Toggle between Overlaid and Separate views

Use the toggles above the graph to switch between Overlaid (all KPIs on a shared axis) and Separate (each KPI on its own chart). Overlaid is useful when KPIs share the same scale; Separate prevents a large-scale metric from hiding smaller ones.
Toggling between Overlaid and Separate chart views to control how multiple KPIs are displayed
5

Select dimensions to filter your view

Pick one or more Dimensions from the list on the right to focus on the segments that matter most — a specific region, channel, or product category. The chart updates to reflect only those dimension values.
Selecting dimension values from the right panel to narrow the chart to specific segments
6

Hover for tooltips and adjust the time window

Hover over any point in the timeseries to see a tooltip with actual and predicted values for that period. Drag the time window slider below the chart to zoom in on a specific date range — useful for isolating a spike or comparing a campaign period against baseline.
Hovering over chart points to view tooltips with actual and predicted values, and dragging the time window slider to adjust the date range
7

Add a dimensional overlay to break down the KPI

Choose a supporting dimension to overlay directly on the chart. The visualization refreshes to show the KPI broken down by each value of that dimension — surfacing which segments are driving the overall trend and which are diverging from it.
Selecting a dimensional overlay and the chart refreshing to show the KPI broken down by each dimension value

How to use Explorer

Data Playground is one of three ways to explore in Explorer — here’s where to start depending on the question you’re asking.
SituationStart with
”Which KPIs tend to move together?”Correlation Matrix
”Which regions / channels carry the most impact?”Dimensional Analysis (Top N)
“Which segments are underperforming most?”Dimensional Analysis (Bottom N)
“I want two KPIs on the same chart”Data Playground
”I need raw numbers for a specific period”Data Playground → Table view
”Compare this KPI for UK vs US”Data Playground → Dimension filter
If your dataset has multiple AD Groups configured, use the AD Group selector in Explorer to compare how each model classifies the same KPI movement. Anomaly bands update in real-time when you switch groups.

What’s next

Correlation Matrix

See which KPIs tend to move together across the dataset.

Dimensional Analysis

Rank segments by Top N / Bottom N contribution.

Dashboards

Pin a Playground view as a shareable dashboard tile.

Top Stories

Start here — stories give you the what, Explorer gives you the why.

Filter Presets

Once you’ve found the right segments, save them as a Filter Preset.

Wisdom

Ask a follow-up question in plain English.

Autonomous Insights

Explorer is where you validate the why behind an autonomous insight.