Using a double index is a great way to move beyond percentages and gain a more nuanced understanding of your results. Indices can be particularly useful when assessing brand performance where percentages can be misleading because they don't account for important contextual factors. Use indices for strategic insights and to understand brand differentiation, but they should be used cautiously for small brands.
In this article
1. Double Index - IND∣2
A double index is a statistical technique used to analyze data to reveal the relative strengths and weaknesses of, for example, a brand compared to its competitors. It is a way to level the playing field, especially when you're comparing brands of different sizes. Its primary goal is to eliminate the brand size effect. Larger or more well-known brands often get more associations for all the attributes, and this can mask their true strengths or weaknesses.
In Harmoni, the double index calculation is applied to an analysis by clicking the calculation type option, IND|2, in the modify menu. Double index is not a default setting and if you require this calculation type, please contact support@infotools.com.
2. How Does it Work
The calculation of a double index involves a multi-step process. Harmoni calculates the single index and then, using the average across all the items, a second index is calculated. Once multiplied by 100, scores can be evaluated on whether they are above or below 100.
When looking at double index scores, here's a general guideline for interpretation:
- Index above 120: This indicates performance that is well above average for that specific attribute and brand. It suggests a strong relative strength or association.
- Index between 80-120: This suggests average performance. The brand's association with this attribute is in line with expectations, considering its size and the attribute's overall prevalence
- Index below 80: This points to performance that is below average. It may indicate a relative weakness or a less prominent association for the brand with that attribute.
It's important to note that small brands can sometimes show higher variance in their double index scores due to lower average selection percentages, which can lead to inflated or misleading scores. Therefore, results for small brands should be interpreted with caution and within the context of the specific brands being compared.
3. Why Use Double Index
- Fair Comparisons: It allows for a more "apples-to-apples" comparison of how brands are perceived relative to their size and the specific attributes being measured.
- Strategic Insights: It helps identify areas where a brand can build on its strengths and where it needs to focus attention.
- Understanding Differentiation: It's crucial for understanding how different brands are perceived and positioned against competitors. While Double Indexing is powerful for understanding relative performance, it's generally recommended to use raw scores or single index scores for certain analyses, like driver analysis, as Double Index scores can sometimes be misleading in those contexts.
Examples using Double Index
Example 1:
In the following example, we'll look at ice-cream brands and how they perform across a range of image statements using percentages and then switch to double index scores. We can also use DIFF and rank a brand to clearly see the result.
- The split grid displays the brands and attributes with the default calculation type of percentages
- Visualize to display a bar chart
- Select the double index INDΙ2 calculation type
- Display DIFF to focus on the over and under indexing scores
Example 2:
In this example, we'll look at total expenditure to form a clear picture of who are the big spenders. After visualizing and changing to a horizontal bar graph, we'll switch the calculation type to double index and use the difference (DIFF) to show which countries stand out. By ranking by the highest expenditure group, it's easy to see that the UK and USA over-index in this group.
- Create the analysis and Visualize
- Select IND|2 and then DIFF
- Select the highest expenditure group from the legend
- Rank (one click for highest to lowest)
4. Double Index Models
There are two Double Index models available in Harmoni. The default setting is a standard double index, while the option to set a sequential double index is also available.
The main steps of the double index calculation for each model are as follows:
Standard Double Index
Step 1: Calculate the average for the row/column
Step 2: For each cell, divide by the average value calculated in Step 1
Step 3: For each non-total cell, divide by the corresponding total cell calculated in Step 2
Sequential Double Index
Step 1: Calculate the average for the column
Step 2: For each cell, divide by the average value calculated in Step 1
Step 3: Row-wise average of cell values calculated in Step 2
Step 4: For each cell, divide by the average value from Step 3
If you require Harmoni to use the Sequential Double Index model in your analyses, please contact support@infotools.com.
Where to from here?
Learn more about Harmoni:
- Change calculation types in your analysis
- Discover Overview
- Create New Items using the Expression Editor