AYTM Insights Dashboard: a practical guide

Last updated: 2025-11-14

TL;DR: The AYTM Insights Dashboard is your control panel for turning survey data into stories. Instead of exporting endless tables, you can explore results visually, apply filters, compare waves, and share views with stakeholders in just a few clicks.

What is the AYTM Insights Dashboard?

The Insights Dashboard is the interactive reporting layer for your AYTM studies. It gives you a structured, visual way to:

• See topline results at a glance
• Drill into specific audiences or segments
• Compare performance across concepts, ads, or waves
• Export charts, tables, and data for deeper analysis

Instead of manually rebuilding charts in slides or spreadsheets every time, you can return to the dashboard and refresh the same views—or build new ones—on demand.

Key parts of the dashboard

The exact layout of your dashboard can vary by study type, but most projects include the following components:

Topline summary

A high-level overview of response counts, key metrics, and overall performance. This is often the best place to start for stakeholders who need a quick read.

Question plots and charts

Each survey question (or group of questions) is displayed as a chart or table, using the visualization that best fits the data type—bar charts for attributes, line charts for trends, and so on.

Filters and segments

Filters allow you to slice results by:

• Demographics (age, gender, income, etc.)
• Behaviors (category usage, purchase frequency, satisfaction)
• Custom segments (e.g., personas, attitudinal clusters)

Applying filters updates charts in real time, so you can quickly see how different audiences respond.

Waves or time dropdowns (for trackers)

For trackers and repeated studies, you can often choose which wave or time period to display, or compare multiple waves side-by-side. This helps reveal trends and shifts over time.

How to read a study in the Insights Dashboard

Here’s a simple, repeatable way to use the dashboard when you open a project for the first time:

1. Start with the topline
   Confirm the basics—sample size, field dates, and any quotas—so you understand who you’re looking at.
2. Scan key outcome metrics
   Identify the 3–5 metrics that matter most for this project (e.g., purchase intent, ad appeal, concept ranking) and see where they land overall.
3. Apply a few core filters
   Compare results for your most important segments: heavy vs. light users, current vs. non-customers, key demographics. Look for meaningful differences.
4. Drill into drivers and diagnostics
   Once you see high- or low-performing concepts, use attribute and reason-why questions to understand the “why” behind the scores.
5. Capture views for storytelling
   Export or screenshot the most important charts. These become the backbone of your narrative for stakeholders.

Using filters and segments effectively

Filters are one of the most powerful features in the Insights Dashboard—but they’re also easy to overuse. A few tips:

• Start with predefined segments: such as brand users vs. non-users, or personas created from earlier work.
• Limit comparisons: comparing too many segments at once can make patterns hard to see. Focus on 2–3 priority cuts.
• Watch base sizes: always check that you have enough respondents in each segment before leaning on a difference.
• Look for consistent patterns: a difference that appears across multiple related questions is more meaningful than a one-off spike.

Working with multi-wave or tracker data

If you’re running trackers or repeated waves on AYTM, the Insights Dashboard can help you move from “static snapshots” to true trends:

• Select individual waves to see that period’s results.
• Compare two or more waves to see movement on key KPIs.
• Combine filters and time to see how specific segments are evolving.

This is especially useful for agile brand tracking, campaign measurement, and iterative product work where context over time matters as much as the latest datapoint.

Exporting and sharing

The dashboard is designed to reduce manual reporting workload, not add to it. Common ways teams use exports include:

• Chart exports for direct use in presentations
• Data exports (e.g., CSV or Excel) for deeper analysis in statistical or BI tools
• Standardized “read-outs” created from a small set of core views that stakeholders learn to recognize

By bookmarking or noting which views you rely on most often, you can quickly recreate or update them for future waves or similar projects.

Best practices for getting value from the Insights Dashboard

• Design with reporting in mind: think about how each question will appear in the dashboard before you field.
• Keep scales and wording consistent: especially across waves or related studies, to make comparisons easier.
• Create a “playbook” of standard views: for brand health, concept testing, pricing work, etc., so teams know where to look first.
• Train stakeholders on reading the dashboard: a short walkthrough can dramatically increase adoption and reduce ad-hoc requests.

FAQs

Can I customize which charts appear in the Insights Dashboard?

Within the constraints of your study design, you can influence how questions are displayed through the choices you make when building the survey (e.g., question types, answer formats, and scales). Many teams standardize on a set of question types that report cleanly for their most common use cases.

Do I still need to export the raw data?

It depends on your needs. Many day-to-day decisions can be supported directly from the dashboard. For specialized modeling, advanced statistics, or internal BI integration, teams often export data as a complement to visual reporting.

How do I make sure stakeholders use the dashboard?

Introduce it as part of your normal read-out process. Show stakeholders how to answer their own follow-up questions and provide a small set of “starter” views they can bookmark. The easier it is to get value in a few clicks, the more likely they are to return.