Profiles
How Profiles work
On a selection of our tools, we have an additional functionality called Profiles. Profiles help to do a lot of the heavy lifting of filtering by pre-grouping them into a single click. For example, "All adults under 55." Profiles filter the entire dataset using the selected segment: when you select a Profile for Males, the norm that is shown in Reporting is also a Male norm.
It’s important to note: Profiles and the norms they reference are tied to the category, so a profile created for "Beer" could not be applied to "Wine." If you intend to analyze multiple categories, it will require consistent testing in each category to create a profile for each category.
The different types of Profiles
There are two types of profile used by the Zappi platform:
Global Profiles
Global Profiles are available to all customers as a platform feature. We do not support the addition of new Global Profiles for individual customer requests.
Here’s why:
Global Profiles use basic demographic filters (age, gender, region) that we offer across the entire database. These are hardcoded into the platform and available to all users.
Each time we create one of these profiles, we duplicate the entire norms DB with the filter applied. For example: if there are 1 million Amplify norms, when we create a Global Profile, we create new records with the filter applied. This results in 2 million norms. If we have 10 Global profiles we would have 10 million norms, and so on. The more norms we have, the greater the impact on the whole norms database.
This is why we try to minimize the number of Global profiles we make available.
- Global Profiles are not constrained by category, as they are the standard offerings from Zappi which only cut respondents by Age and Gender, which are the standard Zappi profiles that are offered by the platform.
- Although Global Profiles have a larger scope of data, in practice this gives the user more flexibility, as they can curate a norm scope on top of a Global Profile that allows them to zoom in on the data they want.
- We are able to offer these across all studies due to the uniformity of the Age and Gender question - i.e., it's easy for the platform assume that across these two measures, they are the same for all studies.
It’s only possible to compare with all adverts in our database - rather than using only customer data - when using a Global Profile.
Full list of Global Profiles:
- Adults Under 25
- Adults Under 36
- Adults Under 45
- Adults Under 55
- All Midlifers 35 +
- All Older Midlifers 45 +
- All Over 55
- Male
- Male Under 25
- Male Under 36
- Male Under 45
- Male Under 55
- Male 25 - 35
- Male 25 - 45
- Male Midlifer 35 +
- Male Older Midlifers 45 +
- Male 55 +
- Female
- Female Under 25
- Female Under 36
- Female Under 45
- Female Under 55
- Female 25 - 35
- Female 25 - 45
- Female Midlifers 35 +
- Female Older Midlifers 45 +
- Female 55 +
User defined Profiles
- Customer Created Profiles require the user to pre-select a country + child category in order to create it. This gives the customer more flexibility and a larger measures list (brand_usage, ethnicity...) to choose from, but these profiles are constrained to the pre-selected country and category as there are harmonization issues across different categories for different measures
- Norms will be available for any profile created when the criteria of the profile has at least 20 adverts available to it, with a minimum base of n=30 per concept/advert.
- When a profile gets created and sent to reports, it is sent in the form of a filter query. Each study that matches that query will use the profile. This means that if the query is simple that it will apply to studies outside of the category the profile was specified for.
How Profiles work with Norms
Profiles are tied to normative data for the grouping selected. The key difference between Filters and Profiles is that applying a filter only affects the selected stimuli data you are analyzing, while applying a Profile affects both the stimuli data and the norm you are analyzing.
This means that if you select "All adults under 55," you will not only filter the data you're looking at down to all adults under 55, you will also see the norm change to reference the benchmark for that measure among adults under 55. This can be especially useful when you want to determine if a group that tends to skew in a certain direction (i.e., males 18-55 tend to have higher purchase intent in the beer category) is responding even more than you'd expect to the current stimulus.
This behaviour differs, depending on if you're using a Global Profile or a Customer Created profile and your norm scope. A few examples:
- A Global Profile such as Adults 18 - 25 is not constrained by child category. Thus if you configure a Country norm and select a Adults 18 - 25 profile, you will get a norm for all ads across that country, segmented by your profile that is selected
- If you take example 1) but you select a client + country + category norm, then that norm will be further segmented by client and category
- Since a Customer Created Profile is always scoped to the country + child category that was used to build it, some norm scopes won't impact the Reporting when this profile is selected. i.e., since we're automatically scoping on country + child category due to the profile, using a country or child category norm would yield the same result.