Data catalog
App user likelihood
Likelihood that an individual uses 11 or more mobile apps daily, based on household app usage.
Coverage
For how many people does Faraday have a value for this attribute? Depending on the type of attribute, Faraday could know a value for people at the individual level, or infer it based on values it knows for each person's address. Finally, in some cases, we can estimate a value for a person based on what we know about other people in their area.
231,196,884
individuals with known value
0
additional individuals with value imputed from their address
0
additional individuals with value imputed from their geography
231,196,884
individuals with known or imputed value
Time series
Faraday collects observations for this attribute over time. This chart shows how many observations we collected at different times.
Data distribution
Technical details
These technical details describe how Faraday represents this attribute internally.
| Property | Value | API value |
|---|---|---|
| API name | app_ | |
| Category | Lifestyle | fig/lifestyle |
| Unit | Rank | rank |
| Type | Integer | long |
| Statistical type | Ordinal | ordinal |
| Allowed values | Not applicable | null |
| Deprecation | Not deprecated | false |
| Derivations | Modeled | ["modeled"] |
| Directionality | Higher number means a greater ranked likelihood. | |
Popularity
How much Faraday's models lean on this attribute.
| Industry | Popularity rank | Average share of weight |
|---|---|---|
| Marketing | 460 of 500 | 0.1% |
| Solar | 188 of 194 | 0.1% |
| Ecommerce | 172 of 279 | 0.1% |