Presence Discovery

The Presence Discovery dimension includes shared data elements about whether a major appliance is present at a customer's household. These shared data elements are tied to customer IDs and can be used as attributes in other subject areas to show customer counts related to Presence Discovery. There is also a Presence Discovery subject area that is based on timeline data and should only be used for historical analysis, such as how the number of major appliances has changed over time.

Note: Use caution when interpreting and applying Presence Discovery data. See Presence Discovery - Usage Notes for more information.

Data Element	Description
Appliance	The type of appliance that may be present at a customer's site. The appliances currently available for presence discovery include: Electric Heating. This represents the presence of electric heating, but does not specify the equipment type (such as electric furnace, heat pump, or baseboard). Level 1 EV Charger Level 2 EV Charger Note: Solar customers are excluded from certain presence discovery processes. This is because the data science models have not yet been trained to produce results for solar customers who have Level 1 EV chargers or electric heating. Therefore, customers who have Level 1 EV chargers will be excluded if the presence of solar technology is predicted to be "very likely" for them. Similarly, customers with electric heating will be excluded if the presence of solar technology is predicted to be "very likely" or "somewhat likely" for them. Type: Attribute
ISO Week	The numeric value of the week of the month in ISO numbering. Example: 3 Type: Attribute
Site Presence	The likelihood that an appliance is present at a customer site. Oracle Utilities uses proprietary data science models to determine the likelihood of an appliance's presence. The values currently available are: Unlikely: The models predict with a high degree of confidence that a major appliance is not present at a customer's household. Somewhat Likely: The models predict with a moderate degree of confidence that a major appliance is present at a customer's household. This information is useful for utilities interested in reaching as many customers as possible where an appliance may be present. Very Likely: The models predict with a high degree of confidence that a major appliance is present at a customer's household. This information is useful for utilities interested in reaching customers who are most likely to have an appliance present. Type: Attribute

Data Element

Description

Appliance

The type of appliance that may be present at a customer's site. The appliances currently available for presence discovery include:

Electric Heating. This represents the presence of electric heating, but does not specify the equipment type (such as electric furnace, heat pump, or baseboard).
Level 1 EV Charger
Level 2 EV Charger

Note: Solar customers are excluded from certain presence discovery processes. This is because the data science models have not yet been trained to produce results for solar customers who have Level 1 EV chargers or electric heating. Therefore, customers who have Level 1 EV chargers will be excluded if the presence of solar technology is predicted to be "very likely" for them. Similarly, customers with electric heating will be excluded if the presence of solar technology is predicted to be "very likely" or "somewhat likely" for them.

Type: Attribute

ISO Week

The numeric value of the week of the month in ISO numbering.

Example: 3

Type: Attribute

Site Presence

The likelihood that an appliance is present at a customer site. Oracle Utilities uses proprietary data science models to determine the likelihood of an appliance's presence. The values currently available are:

Unlikely: The models predict with a high degree of confidence that a major appliance is not present at a customer's household.
Somewhat Likely: The models predict with a moderate degree of confidence that a major appliance is present at a customer's household. This information is useful for utilities interested in reaching as many customers as possible where an appliance may be present.
Very Likely: The models predict with a high degree of confidence that a major appliance is present at a customer's household. This information is useful for utilities interested in reaching customers who are most likely to have an appliance present.

Type: Attribute