Identity & data graphs

Before Personalization can target anyone, it needs to know who they are and what to recommend to them. Two Data 360 building blocks answer that:

• Identity resolution stitches records from different channels — an anonymous web visitor, a logged-in app user, a CRM contact — into one unified profile per person, instead of treating each channel visit as a stranger.
• Data graphs are the query structures built on top of that unified data. Personalization reads them at decision time: a profile data graph for the person, and an item data graph for the catalog it recommends from.

Get this right and every downstream feature — segments, recommenders, experiments — resolves the correct person and the correct catalog. Get it wrong, and Personalization quietly makes decisions against duplicate or stale profiles. This matters most to data architects and Data 360 admins setting up a new org, and to anyone debugging a “wrong profile” or “wrong recommendation” issue later.

What’s on these pages

Work through them in this order:

1. Identity resolution — build the ruleset that matches and merges records into one profile.
2. Profile and item data graphs — create the real-time profile data graph and the standard item data graph Personalization reads from.
3. Default data graph — pick which data graph each data space uses by default, so decisions resolve against the graph you expect.