For every new visitor to your site, a new profile is created. If visitors do not return within a reasonable amount of time, their profiles lose value. If these profiles do not contain any unique identifiers and visitors have not returned, the likelihood that these profiles ever will be activated are close to zero. In addition, these profiles can be included in segment counts and take up costly database space.
To help you manage this growth and maintain a healthy, efficient database, BlueConic offers profile cleanup functionality. By defining rules to remove low-value profiles, you can ensure accurate data insights, optimize costs, and adhere to your contracted Profiles Under Management (PUM) limit.
Before you begin
Understanding profiles under management (PUM)
PUM represents the 365-day rolling average of the number of profiles (both active and inactive, anonymous and known) stored in your BlueConic tenant. This rolling average is used to calculate your platform usage and is tied to your contract with BlueConic. Exceeding your contracted PUM limit can lead to overage fees. Therefore, implementing profile cleanup rules is crucial for managing your PUM and avoiding potential overages.
Known vs. anonymous profiles
Anonymous profiles: These profiles lack data that uniquely identifies a consumer or visitor.
Known profiles: These profiles contain data that allows you to identify individual consumers or visitors, such as an email address, user ID, or other unique identifier.
Set profile cleanup rules
Profile cleanup, managed in General Settings, automates the removal of customer profiles. Rules, based on inactivity duration or empty profile property criteria, dictate which profiles are deleted. This is a continuous process, ensuring that any current or future profile matching a cleanup rule is removed from the database.
BlueConic applies a default profile cleanup rule to old profiles that do not have a known unique identifier. The system-defined cleanup rule removes any profile that has a very old (>400 days) last visited date (or no last visited date), and no values for a unique identifier profile property. This default profile cleanup rule cannot be edited or changed.
Prepare for profile cleanup
Before defining your profile cleanup rules, you need to determine which low-value, unknown profiles are not contributing to your use cases. Some strategies for this may include:
Create the inverse of Known Visitors: If the "Known Visitors" segment uses non-unique identifiers, define accurate identifiers with stakeholders. Create the inverse of this refined segment as the basis for deletion rules.
Identify Unknown Visitors with No Visit in Last 365 Days Segment: Using the "Visitors not in segment 'Known Visitors'" as your base segment, create a segment to identify all unknown visitors who haven’t visited in the last 365 days.
Exclude Visitors Outside Your Target Audience Segment: If you are only interested in specific regions, you can consider removing profiles outside those areas.
Remove bounced profiles: Using the “Visitors not in segment ‘Known Visitors’” as your base segment, create a segment to identify all unknown visitors who do have a ‘first visited date’ and do not have a “last visited date".
High-value profile considerations
Prioritize retaining profiles vital to current/future use cases. Avoid deleting known visitor profiles (e.g., those with email addresses) crucial for lead generation or identity resolution. Set last-visit date thresholds based on typical visitor frequency, considering the 365-day cookie expiration.
Create cleanup rules
To create your own profile cleanup rule:
Open the BlueConic General settings page, and click Add profile cleanup rule in the Profile cleanup section.
Create a name for the cleanup rule.
Select one or more conditions to select profiles to be purged.
(Optional) Specify the number of inactive days to trigger profile cleanup. Inactivity is based on the "lastvisit" property, updated on various visit types.
(Optional) Select Are not identifiable profiles to exclude profiles with unique identifier values from cleanup.
(Optional) Select Have an empty value for defined profile properties to delete profiles lacking values in specified properties. Profiles are deleted only if all selected properties are empty (AND logic).
(Optional) Select Meet the profile criteria to set filtering conditions to select the profiles to be purged.
To the right of the cleanup rule, the rule's impact (number and percentage of affected profiles) is displayed. A red warning appears if the rule affects over 1% of total profiles.
Save your changes. A pop-up appears to confirm whether to delete the number of profiles in the cleanup statistics. Click Delete to confirm the cleanup, or Cancel to cancel the deletion.
Using multiple cleanup rules
If you create more than one cleanup rule, they have an "OR" relationship with each other which means that multiple rules can be in force at the same time.
Deleting a cleanup rule
To delete a cleanup rule, hover the mouse over it and click the Delete icon that appears to the right of the rule. Confirm the deletion in the pop-up window that appears.
FAQs
Why is cleanup important?
A clean tenant increase your data quality which leads to higher quality data and segmentation.The total number of profiles is related to your BlueConic subscription.
How often do cleanup rules run?
Cleanup rules are executed every hour, contributing to ongoing PUM management.
Will newly imported profiles be immediately deleted by profile inactivity cleanup rules?
Potentially, yes. If a profile is imported via a connection and has never visited a channel, its "Last visit date" property will be empty. This can cause it to match inactivity cleanup rules. To prevent this, add conditions to your cleanup rules that exclude imported profiles, such as requiring unique identifiers or specific profile property values.
How can I use a dashboard to help define cleanup rules?
The following insights can be used to create a Profile Analysis Dashboard that may be useful when defining cleanup rules:
Profile Identifiers Insight: Use this insight to identify spurious identifiers such as GA Client ID.
Segment Over Time Insight: Use this insight to measure the sizes of the segments you created above.
Segment Overlap Insight: Use this insight to help estimate the number of profiles that can be cleaned up.
What should I do if I have questions about profile cleanup or want a final review of my proposed cleanup rules?
You can contact your BlueConic Customer Success Manager for assistance.