The pattern that captures different signals for different consent states without breaking the whole pipeline when someone withdraws consent. Defines which events fire under no-consent, partial-consent, and full-consent states, and how each state degrades the available recipes. Required under GDPR and increasingly under CCPA, CPRA, and the patchwork of US state privacy laws.
The capability a stack needs to run this pattern, and the vendors that provide it, on Martech Stack Builder.
Record why a particular customer saw a particular experience, in a form a regulator, an internal model reviewer, or the customer themselves can reconstruct months later
Target CTV from your own customer segments and measure the reach you actually added above linear, rather than buying impressions on faith
Measure consent rates as the trust signal they are, watch them for the slow degradation that surfaces when banners get heavier, jurisdictions tighten, or audiences shift, and catch the trend early enough to fix the upstream cause
Make the choice a visitor makes in the banner actually constrain what the server-side pipeline does with their data
Connect the same person across phone, laptop, and tablet using signals you can stand behind, with an honest fallback when you cannot
Show returning visitors what they had going, last-viewed products, cart contents, loyalty progress, without making them sign in or start over
Give the AI a memory of each customer that is curated and decaying, not a raw event firehose it cannot use and should not keep
Collect what the stated purpose needs, decide explicitly before each new field gets added, and treat the customer record as something curated rather than accumulated
Push the segments you own to the ad platforms, as seeds and as targeting, instead of renting the platforms' own decaying interest signals
Emit a server-set first-party identifier the brand controls, so the customer can be recognized after Safari ITP, third-party cookie deprecation, and the next round of browser changes still to come
Resolve several people at one address into a household where the buying unit is the household, without letting one member's data quietly drive another's experience
Detect and retire the identity links that have gone stale, so targeting and suppression stay accurate as the customer file ages
Reconcile a person's anonymous and authenticated states when their consent decisions differ between them, without leaking the un-consented context into the consented one
Measure the lift a channel actually adds by running a holdout, not the correlation between exposure and conversion the channel's own report shows
Turn search queries, chat, support tickets, and reviews into structured intent signals, without mistaking sentiment for intent
Get the unified spend, exposure, and conversion data clean enough for the model to produce decisions you can act on, not directional outputs that need a footnote
Standardize phone formats across every capture point so SMS reaches the whole file, not just the records that happened to be entered cleanly
Cross-platform suppression with consent propagation
Recognize the visitor who came back without making them sign in, and degrade cleanly to a generic experience when you cannot
Make the server the primary record of what happened, with the browser as the backup rather than the system of truth
A three-message email sequence triggered by abandonment, gated by consent and channel eligibility
A single consent record per user, mechanically propagated to every downstream system that activates against it