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Two questions tell you whether an analysis can be trusted. Is the data current? Is marketing traffic being tracked? The Slack AI Analyst answers both on demand. These are separate problems. A table can be fresh while attribution is poor, and tracking can be fine while a table is stale. Check Data Health first. If the data is fresh but the numbers still look wrong, check Attribution Health. You can also click Data Availability Report in the opening message of a new DM thread. It lists your tables, their status, and your available stores.

Data Health

Data Health reads the freshness metadata for every SourceMedium table in your warehouse. It does not query the tables themselves. When every key table is fresh, the report says core analytics are ready. When a key table is stale or empty, it names the table and the analyses that are affected. The data health report also includes a short attribution health summary, so one question covers both.

When data updates

Most tables refresh daily. Data is fresh through the previous day in your reporting timezone. Today’s data is incomplete, so do not use it for analysis or reconciliation. Some sources lag longer. See Data freshness.

Why 14 days

Core tables such as orders, customers, sessions, and ad spend should refresh every day. The 14-day threshold exists for secondary tables that may not see daily activity. Examples are a new subscription program, a refunds table with low volume, or an integration that only fires on specific events. If a core table is stale, that is almost always a pipeline issue. If a secondary table is stale, ask whether you would expect activity there.

If data is degraded

  1. Ask “Which tables are stale?” to see whether one source or several are affected.
  2. Scope your analysis to dates the data covers. If orders stopped syncing on the 15th, do not analyze the 16th onward.
  3. If staleness lasts more than a day or two, open a support request. It usually means a connection needs attention.
Example questions:

Attribution Health

Attribution Health runs a live audit of your online DTC orders from the last 30 days. Marketplace orders from Amazon, TikTok Shop, and similar platforms are excluded. Those orders are attributed to the marketplace by definition, so there is no UTM to capture.

The status

The headline status is the share of acquisition orders that carry a valid UTM. A valid UTM excludes (direct), (none), self-referrals, and sessions broken by a payment provider redirect.

What the report includes

The report also lists your top source and medium pairs, landing pages, referrer domains, discount codes, and zero-party survey responses, plus recommended actions based on what it found. The report has no trend. To see whether coverage is improving, compare it with a report you ran earlier.

Common causes of poor coverage

  • Missing UTM parameters. Campaign links without UTMs arrive as direct traffic.
  • Payment provider redirects. Checkout through shop.app, PayPal, Klarna, and similar providers can start a new session and drop the original source.
  • Self-referrals. Your own domain gets credited as the source after a redirect.
  • Cookie and tracking blockers. Browser privacy features prevent the session from being recorded.

How to improve it

Attribution Health toolkit

UTM setup, checkout attribute capture, post-purchase surveys, and more.

UTM setup

Standardize UTM tagging across campaigns.

Why (direct) / (none) happens

Causes of missing attribution and how to fix them.

Checkout attribute capture

Capture UTMs at checkout so a redirect cannot drop them.
Example questions:
When numbers still do not match after both checks, see Troubleshooting.