Choose Data Fields and aggregations for a Cloudbeds Insights dashboard

Introduction

A dashboard can return a technically valid number and still answer the wrong question if the Data Field or aggregation does not match your reporting goal. Two decisions have the biggest effect on the result:

• Which Data Field represents the information you want to measure?
• How should multiple numerical values be summarized when records are grouped together?

Start with the reporting question, then choose the Data Field and aggregation that represent that question. This is especially important when similarly named fields represent data at different reporting levels or when a numerical value can be summarized in more than one way.

Use this guide while creating or editing a dashboard visualization. For the complete dashboard-building workflow, including adding visualizations, placing Data Fields, and applying filters, see Create and Configure a Custom Dashboard in Cloudbeds Insights.

Table of contents

• Choose the right Data Field
• Identify field types
• Understand how aggregation works
• Choose an aggregation
• Commonly confused aggregations
• Avoid misleading calculations
• Understand no value and zero
• Troubleshoot unexpected results

Choose the right Data Field

Start with the question the visualization should answer. Cloudbeds Insights can represent similar information at different reporting levels, so Data Fields with related names can produce different results.

For example, some fields describe the reservation or room reservation as a whole, while others represent activity for each applicable stay date.

Common field choices

Identify field types

Data Fields can represent different types of information. Field-type icons help you recognize how a field behaves in a visualization, but they do not replace the field definition.

After Data Fields are added to a visualization, numerical metrics display a number icon (#), while non-numerical dimensions use a text-type icon. Date fields use a calendar icon. Aggregation options are available for numerical Data Fields. Text and date fields do not have aggregation options.

The example below uses Room Type as a non-numerical dimension in Group Rows, while Rooms Sold, Occupancy, ADR, and Total Room Revenue are numerical metrics in Columns.

Understand how aggregation works

A numerical Data Field can contain values across many underlying records. When a visualization groups those records, the aggregation determines how the numerical values are summarized into the result shown for that group.

Filters also affect the values included in the result. Records that do not match the active filters are excluded before the remaining values are summarized for the visualization.

To review the aggregation for a numerical metric, open its three-dot menu in the visualization configuration area. The example below shows the aggregation menu for Rooms Sold.

Choose an aggregation

Choose the aggregation that matches the question you are asking. The available options shown for a numerical metric are Sum, Mean, Max, Min, Count, Std, and Var.

The first five options cover most day-to-day reporting questions. Std and Var are statistical measures and are less commonly needed.

When to use common aggregations

• Sum: Use for values that accumulate, such as revenue, taxes, fees, room nights, guest nights, and paid amounts.
• Mean: Use for a typical raw per-record value, such as room rate, stay length, or booking window.
• Max and Min: Use to find extremes or check the range of the data. They can help expose unusually high, low, or zero values.
• Count: Use when the question is how many records contain a value. Choose the field you count carefully because records with no value are skipped.
• Std: Use when you need to understand how much the values vary around the average. Because Std is expressed in the field's own unit, such as dollars or nights, it is the more readable measure of spread.
• Var: Use only when a statistical workflow specifically requires variance. Var is Std squared, so the result is not expressed in the field's original unit and is usually less useful for day-to-day operational reporting.

Commonly confused aggregations

Some aggregation options answer similar-looking questions but calculate different things. Use these distinctions when a result looks unexpected.

Avoid misleading calculations

Do not Sum rates, percentages, or other non-additive values

Sum is appropriate when values accumulate. A percentage, rate, stay length, or booking window does not become more meaningful by adding it across records. For example, adding three 80% occupancy values produces 240%, which does not represent an occupancy rate.

Do not apply Mean to a field that is already an average or percentage

Fields such as ADR, occupancy percentage, and commission percentage are already calculated figures. Applying Mean to them can produce a misleading result when the groups contain different numbers of records.

For example, consider two room types in one month:

The Mean of the two ADR values is $250, but the actual property ADR is $130. The simple Mean gives the one suite night the same weight as the nine standard room nights.

Use the calculated ADR field at the grouping level you need instead of averaging ADR values again.

Understand no value and zero

Aggregations ignore records that have no value in the selected field. Those records are not treated as zero, and Count does not include them.

Zero is different. A record containing 0 has a value, so it is counted and included in calculations. For example, a $0 room rate can lower a Mean room rate, while a record with no room rate value is skipped.

Troubleshoot unexpected results

Use the checks below when a dashboard visualization's totals, averages, counts, or grouped results do not match what you expected.

Next Operational Step

After choosing the Data Fields and aggregations that match your reporting question, return to Create and Configure a Custom Dashboard in Cloudbeds Insights to add them to a visualization, configure grouping and filters, and save the dashboard.