How to Analyse Matrix (Score)?

Matrix allows respondents to select one or more choices for multiple statements.

  • Matrix (%) analysis is the 1st step, and divides your count values by the answered values to get a percentage for each choice in your statements.
  • Matrix (Score) analysis (this article) is the 2nd step and multiplies the choice percentages with the choice scores and sums them together to give you an overall score (or weighted average) for each statement.

Score Default:

To analyse the Matrix score:

  1. Go to any Matrix question (with statements and choices), e.g.

  1. Change the Values from "Row %" to "Score", e.g.

  1. Analyse the results! E.g.

In above table / chart , we can see "Hot Sauce Frequency" Scores of:

  • 1.0x p/week for Breakfast
  • 2.5x p/week for Lunch, and
  • 3.6x p/week for Dinner, calculated as:
    • 0 x 2% +
    • 1 x 13% +
    • 2 x 19% +
    • 3 x 18% +
    • 4 x 15% +
    • 5 x 13% +
    • 6 x 10% +
    • 7 x 10% =

Simple, right?

Score Crosstab A:

Score Crosstab A permits you to see the differences in scores for all your statements in the rows / chart axis (e.g. Breakfast, Lunch, Dinner), across your segments or demographic filters in the columns / chart bars (e.g. Completes vs. Males vs. Females)

To create Score Crosstab A, simply:

  • keep Rows as "Statements",
  • change Columns to "Filters",
  • keep Values as "Score"
  • change Chart Type to "Group Bar"
  • add Filters, e.g. for "Males" and "Females"

We can now see differences in scores across demographic filters for all statements! E.g. Hot Sauce was added to:

  • Breakfast: Completes: 1.0x p/week, Males 1.0x p/week, Females 1.0x p/week
  • Lunch: Completes: 2.5x p/week, Males 2.4x p/week, Females 2.5x p/week
  • Dinner: Completes: 3.6x p/week, Males 3.5x p/week, Females 3.7x p/week

How powerful is that?

Score Crosstab B:

The Crosstab B format is GREAT for BIG score crosstabs as you can fit a lot MORE filters in the table rows / chart axis than you can in the table columns / chart bars. E.g. 15 filters across Completes (1), Gender (2), Age (3), Time (4), and Country (5) in the table rows / chart axis.

Chart:

Table:

To create Score Crosstab B:

  • change Rows to "Filters"
  • change Columns to "Choices"
  • a new Dropdown for "Statements" will automagically appear, e.g. "Lunch"
  • keep Values as "Score"

E.g. for Statement: "Lunch", we can now see differences in Hot Sauce Frequency scores for each Filter of:

  • 2.5x p/week for Completes
  • 2.4x p/week for Males
  • 1.5x p/week for 61-99s
  • 1.9x p/week for Q4
  • 3.0x p/week for AUS

Score Crosstab C:

However, instead of one statement at a time in Score Crosstab B above, in comparison, Score Crosstab C below lets you see differences in scores across all 15 filters for all 3 statements.

Chart:

Table:

To create Score Crosstab C, simply:

  • keep Rows as "Filters
  • change Columns to "Statements"
  • keep Values as "Score"

We can now see differences in Hot Sauce Frequency scores across all 15 filters for all 3 statements of:

  • Completes: Breakfast: 1.0x p/week, Lunch 2.5x p/week, Dinner 3.6x p/week
  • Females: Breakfast: 1.0x p/week, Lunch 2.5x p/week, Dinner 3.7x p/week
  • 18-40s: Breakfast: 1.6x p/week, Lunch 3.3x p/week, Dinner 4.2x p/week
  • Q2: Breakfast: 1.1x p/week, Lunch 2.7x p/week, Dinner 3.9x p/week
  • NZD: Breakfast: 0.8x p/week, Lunch 2.3x p/week, Dinner 3.5x p/week

This is the most complex matrix analysis possible, but how easy was that?

Score Time Series:

Finally, to track trends over time, simply:

  • add time filters (e.g. Q1, Q2, Q3, Q4) to your table rows and
  • keep Columns as "Statements" (e.g. Breakfast, Lunch, Dinner)
  • keep Values as "Score"
  • change Chart Type to a "Line Chart"

We can now see scores in each quarter for all statements of:

Matrix Score Recap

To recap, these are the 5 most common combos that cover 99% of use cases for Matrix (Score) analysis.

  1. Score Default: Statements x Choices with Score and Group Bar Chart
  2. Score Crosstab A: Statements x Filters with Score and Group Bar Chart
  3. Score Crosstab B: Filters x Choices x Statement with Score and Group Bar Chart
  4. Score Crosstab C: Filters x Statements with Score and Group Bar Chart
  5. Score Time Series: Filters x Statements with Score and Line Chart

Matrix (Score) analysis done! 🎉

In the next article, we'll show you how to analyse Rank (%).

Did this answer your question? Thanks for the feedback There was a problem submitting your feedback. Please try again later.