# 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:

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

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

- 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.

- Score Default: Statements x Choices with Score and Group Bar Chart
- Score Crosstab A: Statements x Filters with Score and Group Bar Chart
- Score Crosstab B: Filters x Choices x Statement with Score and Group Bar Chart
- Score Crosstab C: Filters x Statements with Score and Group Bar Chart
- Score Time Series: Filters x Statements with Score and Line Chart

Matrix (Score) analysis done! ðŸŽ‰

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