HubSpot
Salesforce
Pipedrive
Intercom
Mailchimp
Records governed
How many records are being evaluated at all, based on the scope of your observable templates.
Data IntegrityObservability
Know when your CRM data stops conforming.
Reports show a snapshot. Observability continuously evaluates records against your Blueprints and preserves coverage and drift over time, so you can pinpoint when conditions changed and focus the investigation on that moment.
Integrity over time
Coverage and drift trends
Coverage
96.8%
Recovered since Aug 10Drift
1.7%
Down since Aug 10CoverageDrift
Aug 10 · Change detected
Coverage fell as drift rose
Proof over time
A report shows where the data is now. Observability shows when it changed.
Blueprints define the logic. Data Logic applies it. Every ingestion cycle evaluates the result and adds to a history your team can use to measure, diagnose, and improve data integrity over time.
Three measurements, tracked over time
Know the reach, completeness, and conformance of your strategy
Plus whether each is improving, deteriorating, or changing unexpectedly.
Coverage
Of governed records, the percentage that match a Blueprint row. Unmatched values reveal gaps in the strategy or the data.
Drift
Matched records whose output fields no longer hold what their Blueprint row assigns, the signal that reality moved away from intent.
From trend to the exact moment
See what changed, when it changed, and what needs attention.
Run summaries
Review every evaluation cycle, including matched rows, fallbacks, exclusions, no matches, errors, and the exact Blueprint version used.
Coverage gaps
See the exact unmatched values and how many records each affects, so the highest-impact additions rise to the top.
Drift by field
Identify which output fields diverged, how many records are affected, and whether update conditions allow correction.
History and trends
Track coverage and drift across evaluation cycles, pinpoint when a metric moved, and distinguish a one-off change from a recurring process.
Declare what right is
Surface the unknown unknowns, the problems no one thought to check for.
A filter catches only the wrong you enumerated. A Blueprint declares what right is, and everything outside it reveals itself, including the unknown unknowns no one thought to check for. New source values, undecided segments, and unexpected agent outputs become visible as gaps or drift.
- Unmatched values ranked by affected records
- Drift by output field and update condition
- Total records outside the Blueprint
- Unexpected fallback volume
- Templates that need attention or have regressed
- Coverage falling or drift rising over time
From trend to investigation
Move from the moment something changed to a focused investigation.
Spot the movement
Use Data Integrity Overview to see where coverage or drift moved and pinpoint the evaluation cycle when the change began.
Investigate the change
Open Observability to inspect reach, gaps, drift by field, recent history, and the exact Blueprint version for the affected template.
Correct and re-evaluate
Expand the strategy in Blueprints when legitimate values are missing. Correct drift with Data Logic when records no longer hold their assigned outputs. The next evaluation shows whether the changes worked.
Drift is more than a cleanup queue
See when a governed value stops holding again.
If a field returns to drift after Data Logic corrects it, the timeline shows when it was fixed and when it diverged again. That pattern signals that something else may be rewriting the field and gives your team the precise time window to investigate, instead of repeatedly cleaning the result.
Territory · Drift by field
Corrected by Data Logic
431 records
10:15 AM
Drift returned
86 records
2:40 PM · check field owner
Common questions
Observability, explained.
What is CRM data observability?
CRM data observability is the repeated evaluation of records against defined data standards and business logic. Unlike a point-in-time report, it preserves coverage and drift over time so teams can pinpoint when conditions changed and investigate what happened at that time.
What is CRM data drift?
CRM data drift occurs when a record matches a Blueprint row but its output fields no longer hold the values that row assigns. It means the current state has diverged from the declared strategy.
What is a coverage gap?
A coverage gap is an in-scope record whose values match no Blueprint row. Observability groups the exact unmatched values and ranks them by the number of records affected, helping you determine whether to add a valid value to the Blueprint, adjust the matching, or correct bad data.
What can Observability find that a conventional data quality report misses?
A quality report checks for problems someone already defined. A Blueprint declares what right looks like, allowing everything outside the strategy to reveal itself. This surfaces unexpected source values, undecided segments, agent outputs, and other unknown unknowns as coverage gaps or drift.
Does Observability automatically correct drift?
No. Observability evaluates and reports; it never writes to CRM records. Corrections are applied through Data Logic on demand, on a schedule, or through existing CRM automation. The next evaluation shows whether the correction worked and continues to hold.
How often does Observability evaluate data?
Records are re-evaluated throughout the day, during hourly CRM syncs and whenever data is changed through Insycle, including Data Logic runs and other operations. Template diagnostics reflect the most recent ingestion, so coverage gaps and drift update as those changes are processed. Account-wide metrics, template summaries, and trend charts use a stable daily snapshot for consistent reporting over time.
See integrity over time, not just a snapshot
Know when your CRM conforms and when it starts to drift.
Make one Data Logic template observable and begin building the history that reveals when conditions change and where to begin investigating.
