Charting, P-Maps, Geografix

Charting

The Explore Charting Module is a dedicated section within the application designed to provide a quick, visual representation of the data contained within your report. Unlike older systems, Charting in Explore is focused on visualizing cross-tab data rather than serving as a dashboard with custom editors.

The module is accessible via the left bar of the Explore interface.

Sections of the Charting Module

The Charting Module is organized into different views, all of which aim to visualize the relationship between survey items, specifically audience (columns) and insights (rows).

1. Combined Targets (Combined Charts)

2. • Structure: Combined Charts display a chart for each group name of the items defined in the cross-tab rows. The number of charts displayed is directly linked to the number of insight (row) groups defined in the coding grid.
   • Visualization: Within each chart, the audience and data items are displayed as the legend, showing how the audience compares across the different row variables within that group. Combining all rows into a single group results in one large chart containing all the variables for that group.

2. Single Targets (Single Charts)

3. • Structure: It presents multiple individual charts, one for each target, with the chart content being controlled by the row groups (insights) defined in the cross-tab. It is used when users want to focus on a single audience rather than comparing multiple ones, as is done in Combined Charts.

3. Dynamic View

4. • Function: This feature is available in both Combined and Single Target sections and is intended to provide a more interactive, dashboard-like experience.
   • Combined Charts Dynamic View: Allows users to select a base table and then choose specific custom audiences or targets to display on the chart, enabling the isolation of targets for comparison. This acts almost like a single-target mode within the combined targets view, allowing users to efficiently filter out targets they don't care about.
   • Single Targets Dynamic View: Functions differently by creating a "mini constraint audience". Users can stack multiple audience criteria and see how the overall audience size shrinks with each added constraint, enabling in-depth audience exploration.

Process and Features to Use the Charting Module

The process begins after a cross-tab has been successfully created with rows (insights) and columns (targets).

Process Flow:

1. Navigate to Charts: Use the icon on the left bar to switch from the Data Module to the Charts Module.
2. Select View: Choose between Combined Targets (default) or Single Targets.
3. View Charts: The system automatically renders charts based on the grouping of items in the cross-tab rows.
4. Customize Charts: Use the various controls and settings (listed below) to refine the visualization.

Key Features and Controls:

Quick Reports

Quick Reports in Explore are a specialized type of report designed to capture and save a specific report visualization, primarily for quick access, demonstrations, and presentations. Changes made to Quick reports by viewers are not saved, so there is no danger to the Quick Report losing its setup because of edits by other users.

How Quick Reports are Used and the Process

Quick reports can be created in two main ways:

• From the Dashboard: Users can create a new quick report by clicking the "New" button in the "My Drive" or "Shared Drive" workspace, and then choosing the Quick Report option.
• From an Existing Report (Save As): When a user is working within an open standard report, they can use the "Save As" button in the top bar's right section. This opens the "Save As" modal, which includes an option to save the current report configuration as a quick report. This method captures all the data and chart settings established in the current view. This is the preferred way to create a quick report as it allows the user to properly create the report with the full suite of features available in regular reports.

Quick reports are highly useful for visualization and presentation purposes, especially in conjunction with the Charting Module:

• Chart Customization: Once a quick report is saved, it preserves the chart settings configured at the time of saving. Users can customize charts, for example, by cleaning up long labels from the survey to create cleaner, more presentable charts.
• Dynamic Manipulation: When viewing a saved quick report, users (if they are the editor) can still modify the analysis on the fly, such as adding a new audience from the codebook, removing existing rows, and then exporting the updated visual story. Non-editors can manipulate the data displayed (e.g., sort by index or audience) but cannot change the chart styles.
• PowerPoint Export: Quick reports facilitate the rapid export of polished charts into presentation formats like PowerPoint or Google Slides, supporting the need to generate frequently required data stories.

Perceptual Mapping (P-Maps)

Perceptual mapping, often utilized in data analysis and market research, is a visual representation of how target audiences perceive various products, brands, or services relative to each other. It typically involves plotting items on a two-dimensional grid based on key attributes or dimensions that are important to the audience (e.g., price vs. quality, innovation vs. tradition).

In Explore, P-Maps serve as a powerful visualization layer for interpreting the relationships unearthed by the cross-tabulations:

• Source of Data: The raw input for a P-Map often comes from survey data analyzed via cross-tabulation. For example, a cross-tab might show the frequency with which different demographic groups associate Brand A with the attribute "High Quality" and Brand B with "Low Cost."
• Dimensionality Reduction: Cross-tabulation can reveal many associations, but P-Maps simplify these into a visual space. With Explore, these can be graphed on the X & Y axis, and the choice exists to use 2 columns from the report, or use 2 data items to visualize the P-Map, allowing for flexibility in analysis.
• Visualization of Competition/Gaps:
• • Positioning: Brands or products are plotted as points. Their proximity to each other indicates perceived similarity, while their location relative to the axes defines their perceived positioning on key attributes.
  • Market Gaps: Empty spaces on the map can highlight potential market segments or positioning opportunities that are currently unserved by existing products.

How P-Maps is Used & Interpreted in Explore

The P-Maps module is accessed via the left bar of Explore. P-Maps works by visualizing the relationship between items using a scatter plot based on two axes (X and Y), which typically represent two columns or two data items.

1. Visualization of Brand Perception: The core use is to display brands or products on a chart based on customer perception, often called positional mapping or brand positioning.
2. Target Audience Comparison: It allows users to visualize two target audiences against data points to see outliers or trends. For example, users can compare two different demographic audiences (e.g., women with high income vs. men with less income) against a set of brands (e.g., potato chip brands).
3. Quadrant Analysis: The map is divided into quadrants, which help interpret the data:
4. • Items in the upper-right quadrant are indexing high for both targets.
   • Items in the lower-left quadrant are under-indexing for both targets.
   • Items in the upper-left quadrant are indexing high for the Y-axis target but under-indexing for the X-axis target.
   • Items in the lower-right quadrant are indexing high for the X-axis target but under-indexing for the Y-axis target.
4. Audience Size Representation: The size of the bubbles (data points) on the P-Maps graph represents the audience size for that data item.

Features of the P-Maps Module

The P-Maps module retains similar functionality to previous versions but features an updated UI and design. Its mapping control functions are located on the left side of the interface.

Geografix

The Geografix module is Explore’s specialized mapping tool, dedicated to visualizing relationships and data geographically. It is one of the visualization modules accessible via the left bar of Explore and is used to analyze survey data that contains corresponding geographic information. Geografix provides a dynamic view of how customer attitudes, behaviors, or demographics are spatially distributed, making complex geographic data easier to digest and communicate.

Geografix operates by linking survey data to geographical coordinates, enabling visual analysis through various layers and controls to facilitate easy analysis.

Data Requirements and Processing

The Geografix module only appears for reports using surveys that have been specifically tagged as "mapable" (this tag can be seen in the Survey Select modal when choosing surveys to be used for a report).

• Data Source: Geographic data originates from the survey provider.
• Processing: The data team processes this raw data to create KML files or its equivalent, which are necessary to enable the mapping system.
• Codebook Category: Surveys that are mapable will have a dedicated "Geografix" category in the codebook, which consolidates all mapable elements. If a survey contains geographic demographics but lacks this dedicated category, it means the processing work to transform the data into useful geocodes has not yet been completed, and mapping will not be available.

Interface and Dynamics

When a user enters the Geografix module, a map displays the selected region and the outlines of the geographic areas added to the report.

• Real-time Updates: Unlike some other modules (like segmentation apps), changes made to the data in the cross-tab reflect immediately when the user navigates back to Geografix. Removing a geographic element from the cross-tab will result in that area appearing blank on the map.
• Cross-tab Dependency: All displayed data options, values, columns, and rows within Geografix are based entirely on what exists in the cross-tab at the time the user switches to the module.

Features of Geografix

Geografix provides advanced controls for displaying data on the map:

Process to Use Geografix

1. Survey Selection: When selecting a survey, users can use the "mapable" filter in the survey selection screen to ensure they choose a survey that supports geographic analysis.
2. Cross-tab Setup: To utilize the feature, users must add geographic codings (from the dedicated "geographics" category) to their cross-tab rows.
3. Module Access: The user then switches to the Geografix Module using the icon on the left-hand navigation bar. The icon is only present if the survey has enabled geographics.
4. Interactive Analysis (Example: POI):
5. • The user can zoom into a desired area.
   • They can click directly on the map to identify a POI, where the system attempts to pick the name or address.
   • Alternatively, they can use the search functionality by typing a keyword (e.g., "gas station"), and the system returns relevant options within the map view.
   • The user can select an identified POI and click "Add to Custom Points". The system prevents saving duplicate POIs with the same geo-codes.
   • Custom points can be saved to a user's drive (personal or shared) with a custom name and reloaded onto the map later, facilitating collaboration.

Use Case Summary

The primary use case is to visually represent survey data on a map to identify patterns, relationships, and concentrations across defined geographical areas.

Specific use cases include:

• Audience Distribution: Viewing the distribution of a specific audience (column) across defined geographic areas using the heat map.
• Comparative Analysis: Utilizing the chart overlay feature to quickly compare the breakdown of all audiences (all columns) within a single geographic area.
• Location Planning/Profiling: Identifying and saving Custom Points of Interest (POIs) that can be marked and saved on the map, supporting analysis related to specific locations.
• Data Exploration: Toggling data labels (index, percent to row, etc.) directly onto the map to interpret the data without relying solely on the cross-tab table.