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

Power BI: League Table

The League Table page (which you may also see labelled as Demographics) helps you understand how different customer segments compare to one another. This is your scorecarding page for identifying which groups are having the best or worst experience. It's built to answer questions like "which age group is most satisfied?" or "which ward has the highest volume of complaints about damp and mould?"


How to use this page

Understanding the layout

The page is divided into two main sections:

  • Right side: A horizontal bar chart showing each demographic group, with colour-coded bars representing the sentiment breakdown for that group.
  • Left side: A table showing specific numbers for each group.

Both sections display the same information in different formats, the right-hand visual for a proportional, at-a-glance comparison, and the left-hand table for precise figures.

Selecting your demographic

In the page inputs at the top right, use the dropdown to choose which segment of your data you want to analyse. This might include age groups, property types, wards, regions, or any other way your customer data is segmented. Select one and the page updates to show how each group in that segment compares.

Choosing your metric

Toggle between three views using the buttons at the top left of the visual:

  • Volume: Which demographic groups are leaving the most feedback.
  • Sentiment: Which groups are most positive or most negative. The bars on the right show the breakdown of very negative through to very positive responses for each group.
  • KPI: Which groups have the highest or lowest score for your selected metric (for example, TSM score).

When reviewing demographic breakdowns, always check volume alongside sentiment. A group showing as most negative is less significant if they've only left five comments. Pair the sentiment view with volume to get the full picture.

Sorting your data

The page inputs also include a sorting dropdown, allowing you to reorder your demographics by different criteria. Sorting by "Very Negative", for example, reorders the groups to show which has the highest proportion of very negative feedback at the top.Important note on sorting: This sorts by proportion (percentage), not absolute volume. A group with 100 responses where 50 are very negative (50%) will rank above a group with 1,000 responses where 400 are very negative (40%), even though the second group has more negative comments in raw terms. This is intentional, it helps you identify which groups are having the worst experience proportionally, not just which groups are largest.

Filtering by theme

To get even more from this page, combine the demographic breakdown with a theme filter. For example, to understand which wards are most affected by damp and mould, select Damp and Mould from the themes filter and choose Ward as your demographic. You'll then see which specific wards have the highest volume or most negative sentiment about that issue. This is useful for targeting interventions geographically.

Viewing trends over time

Above the sentiment breakdown graph, there's a button to switch to a trend view. Click it to see a line graph showing how each demographic group has performed over time for your selected metric. This helps answer questions like "has sentiment for this age group always been low, or is it a recent change?", which can reveal whether issues are long-standing or emerging.

Drilling through to verbatim

As with most pages, you can drill through to read the actual comments. Click on any demographic group in either the bar chart or the table, right-click, and select Drill through to verbatim. This takes you to a page showing all comments from that demographic group, filtered by whatever theme or category you've applied.

Key points

  • Purpose: Compare performance across demographic segments to identify which groups are having the best or worst experience.
  • Demographic selection: Choose which segmentation to analyse (age, property type, ward, region, etc.).
  • Three metric views: Toggle between volume, sentiment, and KPIs to see different aspects of performance.
  • Sorting functionality: Reorder demographics by overall metrics or specific sentiment categories (for example, very negative descending).
  • Proportional ranking: Sorting ranks by percentage rather than absolute numbers, to identify the worst affected groups.
  • Detail table: Left side provides exact numbers and percentages for each demographic and sentiment category.
  • Sentiment breakdown visual: Right side shows colour-coded sentiment breakdown for at-a-glance comparison.
  • Theme filtering: Combine with theme filters to see which demographics are most affected by specific issues (for example, damp and mould by ward).
  • Compare Over Time view: Switch to line graphs to see how demographic groups have performed over time.

  • Drill-through: Access verbatim comments from any selected demographic group.

Use case

This page is particularly useful for:

  • Identifying vulnerable or dissatisfied customer groups who may need additional support.
  • Understanding whether specific issues disproportionately affect certain demographics.
  • Targeting communications or interventions to specific geographic areas or customer types.
  • Evidencing equalities impact: showing whether service quality varies across protected characteristics.
  • Supporting business cases by quantifying the scale of issues in specific customer segments.

Zoe-1    ✍️ Article written by: Zoe, Customer Success Manager 

Still in need of some help? Give us an email on support@wordnerds.ai or reach out to your CSM directly.