Resonate is dedicated to providing clients with unique insights and helping them understand what makes an audience's story interesting by identifying the data that stands out. To understand our insights, we rely on two metrics; Index and Composition. You will see an Index and Composition metric for almost every insight in Resonate.
There are two sides to the Index/Composition coin, and the correct way to interpret an attribute value's Index and Composition ultimately depends on the business needs, the use case and the subject you want to learn about.
If the focus of your research is scale, pay attention to Composition. Watch out, though, because if Composition is your sole metric for finding insights, you may only find things you already know, such as "lots of Millennials use Instagram."
On the other hand, if it’s precision and efficiency you’re looking for, rely on Index. It will tell you interesting things about your audience that you may not already know and help you differentiate your approach.
For this guide, we'll use a couple of examples to demonstrate how to analyze these two metrics. For Examples 1 and 3, we'll assume the role of a marketing analyst at an Agency who wants to inform our client about what their audience cares about the most. In Examples 2, 4 and 5, we’ll be working for a Retail brand and will try to understand which TV shows and music streaming channels to advertise on.
What are Index and Composition?
Index measures how likely your audience is to have an attribute as compared to the baseline, e.g. the total adult online population. It answers the question, "How likely is your audience to have these attributes compared to the average U.S. online population, or to your selected baseline?" If the index number is above 100, people in your audience are more likely to have the attribute compared to the baseline. If the index number is below 100, the attribute is less present among people in your audience compared to the baseline. As a guideline, we look for attributes with an Index of 120, or above, to identify attributes that are unique and meaningful to the audience.
For example, if you see an index number of 260 for Family-friendly Product Attributes, it means that people in your audience are 160% more likely than the baseline to value, or choose, products based on whether they are family-friendly.
You can read more about changing your baseline here.
Low-indexing attributes are also worth examining, for they tell you what your audience doesn’t care about. Don’t waste your budget on a creative that won’t click with your audience!
Example 1: As a Marketing Analyst at an Agency
We want to advertise children’s electronics to Millennial Expectant Parents. Our analysis will inform us that this audience is under-indexing for product attributes “durable” and “energy-efficient,” but over-indexing for “fun and exciting.” This means that a creative with a message of “The fun never ends with baby’s first computer” will likely outperform a message of “Now baby’s first computer has a great battery life.”
Composition is the number, or share, of those in the audience who have an attribute or trait. Expressed as a percentage, the percent Composition is the proportion of people in an audience who have a specific attribute value. If your audience has a Composition of 32% for family-friendly product attributes, it means that almost a third of your audience values products that are family-friendly.
Index and Composition in Curated Reports
In most cases, components in our curated reports are shown by Index, with the minimum Composition threshold also indicated nearby. You will see that the minimum threshold can vary between 3% to 15%, depending on the report component. When developing each component in our curated reports, our product management team and professional services team work together to determine the appropriate Composition threshold for each report component to ensure that the data you see is both significant and unique to the audience.
When the minimum Composition is not defined, it’s because all attribute values are listed, and we don't need to rely on the Composition to filter the displayed attributes.
Sometimes, certain report components will display insights by Composition. These include demographic traits and other attributes where we bucket values into categories, expressing what percentage of the whole an attribute value is, like hours spent online per week.
When interpreting data that displays both Index and Composition, you should look for a balance between the two metrics, bearing in mind the specific use case and insight you’re analyzing. As a best practice, look at the Index to bubble up the differences in attribute values, then examine the Composition for a closer look. If the focus of your research is scale, pay attention to Composition. On the other hand, if it’s precision and efficiency you’re looking for, rely on Index.
When to rely on Index?
As mentioned before, you should give more weight to an attribute’s Index when you are aiming for precision and efficiency, or when looking for attributes that are exceptionally unique to an audience. Index is a more telling metric when analyzing attributes that:
- Are multi-select survey questions (meaning that the attributes have numerous values from which audiences can choose),
- are a wide-spread trait for the majority of the population.
Usually, these attributes are retail brands, stores, restaurants, hotels or media consumption traits, such as magazines or TV shows.
Example 2: As a Marketing Analyst for a Retail Brand
Looking at an audience’s TV show consumption habits, filtered by Index (descending), we will see that the Composition is a bit low for the top indexing shows, but the Index is remarkably high. These are the attribute values that make an audience unique compared to the baseline.
Note: A Composition of 5% is good for attributes like “TV Shows Watch Regularly” because there are so many shows an audience can choose from.
Example 3: As a Marketing Analyst at an Agency
We've been asked to tell our client where their audience shops for retail apparel. In this specific use case, Composition is less meaningful than Index because we can expect that a large portion of the average online population has shopped with similar brands. We want to know whether shopping with a brand is unique to our audience, not whether they have shopped for it at all – that’s why we’ll consider Index over Composition.
Example 4: As a Marketing Analyst for a Retail Brand
The “Download/Stream Music” attribute is also a good example for demonstrating that, in certain use cases, the Index should be the deciding metric. In our next example, we want to advertise to our target audience on a streaming service. Our analysis reveals that 20% of these people are 5% more likely to download or stream music on Spotify and 19% of them is 8% more likely to stream music on Amazon Prime Music. While these Composition numbers are solid, the Indexes are low, hence these attributes are not that unique to our audience. On the other hand, our audience is indexing at 128 for SoundCloud, with a 7% Composition, which makes this attribute value more unique to them. So we recommend that if you’ve been allocating your streaming budget to Spotify and Amazon Prime Music, you should now consider SoundCloud as well.
Once you have identified the Indexes worth considering in your analysis, take a look at the Composition to verify that the insight is valuable to your research. What do we mean by that? The audience is over-indexing for "Tidal" in the image above. However, its Composition is <1%. This tells us that less than 1% of our audience actually uses this streaming service, so our marketing efforts would not be as efficient on this channel.
You can use the filter function to change the order of your insights and place the most relevant ones on the top of your list. You can filter alphabetically and by Index or Composition number. The black highlight informs you which filter you are currently applying.
Pro-tip: Finding meaningfulness in the Index metric varies based on data type and business case. For example, as a rule 110-120 is considered a meaningful over-index value for survey data because there is more differentiation between survey values, while 105 can be meaningful for behavioral or tag data.
The range of Index values is also important. If there is a broad range, like 80-305, then an Index of 105 is not meaningful because there are much higher index values. If the range is between 95 and 105, then an index of 100 probably becomes meaningful.
These are general guidelines, but finding meaningfulness in Index ultimately depends on your business context.
When to rely on Composition?
Composition is your go-to metric when the aim of your research, or campaign, is scale.
Scale is important in advertising, and so is Composition. Composition helps you determine how large of a net you’d be casting if you were to activate against an audience based on one of its attributes.
Recall Example 4 about advertising on music streaming services. Our advertising on SoundCloud was an effort of precision and efficiency, while ads on Spotify and Amazon Prime Music gave us a better reach.
Example 5: As a Marketing Analyst for a Retail Brand
Similarly, if you had to decide on which social media channel to run your ad, look at your audience’s social media membership and identify the attribute value with the largest Composition. The higher the percentage is, the larger portion of your target audience you will reach with your ad. But! If we only rely on Composition here, we'd report back to our boss that we should run our social budget on Facebook...which is probably something they already know! If we also look at Index, we can see that our audience is 21% more likely to use Pinterest, and this attribute value also has a healthy Composition. This tells us that, if we're not already doing so, we should incorporate Pinterest into our social media planning and budget.
Bringing it all together
The best practice for interpreting Index and Composition is to consider both metrics and weigh their significance according to your business needs, use case and the insight you’re trying to understand.
Index can help you find the needle in the haystack: It will allow you to identify attribute values that stand out from others and make your audience unique compared to the online adult population. Focusing on attributes that are unique to your audience will ensure that your targeting is precise and efficient. This strategy can help you find ways to break through the clutter and reach your desired audience.
At Resonate, we say that Composition is a great metric when you want to “get more juice out of the squeeze” because it tells you what percentage of your audience has the trait you're interested in targeting. Composition offers important and decisive data, but we recommend that you consider it after filtering your insights by Index. Most times, if you’re solely looking at Composition, almost everyone will look the same; consequently, you will have a hard time identifying what makes your audience unique.
The key to cracking the "When to use Index vs. Composition" question is that you keep your business goal in mind and analyze your audience's insights accordingly.