Dataium ID

A unique identifier associated with a consumer. The identifier is a hash based on a browser cookie, which is unique for each device and browser used on each device.

First Activity Date

The date of first activity on the network of websites – to the millisecond. This date is relative to the central time zone and is in the form yyyy-mm-dd hh:mm:ss.

Last Activity Date

The date of the most recent activity on the network of websites – to the millisecond. This date is relative to the central time zone and is in the form yyyy-mm-dd hh:mm:ss.

Days in Market (Current Shopping Period)

A shopping period is defined as a set of behavior exhibited over the course of minutes, hours, and days, with at least 30 days of inactivity between the next set of behavior. This then creates two or more defined shopping periods. Days in Market looks at the most recent shopping period for a shopper and uses the number of days in that period as their days in market. For Example: Sam has two shopping periods. The first was over the course of 3 days and the second 14 days. Sam’s days in market value is therefore 14 days since the first shopping period is ignored in the calculation.

User Intensity Rank

An integer score of 0-5 indicating a user’s shopping intensity on our network. A rank of 0 indicates no shopping activity within the last 30 days. A rank from 1-5 indicates shopping activity in the last 30 days with 1 indicating the least intense behavior and 5 indicating the most intense behavior.

Things such as: days in market, shopping periods, and vehicles viewed, behavior which is indicative and non-indicative of a purchase, and more. Scores depreciate over time based on inactivity and the range of scores quintiles before determining a shoppers final intensity score.

User Intensity Trend

User Intensity Trend is a directional indicator for the User Intensity Rank (UIR). In other words, this value indicates whether the User Intensity Ranks is trending down, trending up, or holding steady. This is represented through the following values: -1 (UIR is trending down), 0 (UIR is holding steady), 1 (UIR is trending up).

Top 3 Vehicles

All the vehicles a shopper has viewed in their shopping history are assessed. A formula of ranking this data is applied to determine the shopper’s top three preferred vehicles. For each of the three vehicles, year, make, model, average price and vehicle rank will be included. Average price for each of the top 3 vehicles is calculated by assessing the price that a specific shopper “saw” for that year, make, and model combination. Then, averaging those prices together to get a final value.

Vehicle rank is available for each of the top 3 vehicles. This score indicates the relative ranking / difference between the top 1, 2, and 3 intended vehicles. These vales are expressed as a percentage of the shopper’s interest toward each of the three vehicles. Example: Vehicle #1 received 45% of the shopper’s interest, vehicle #2 received 40% and vehicle #3 received 15%. Due to rounding values, the sum of all three values may vary slightly above or below 100%.