Use this article to understand what Data Integrity monitors, how its five views fit together, and where to go for each task.
Data Integrity is an Insycle feature set that helps you monitor and improve the effectiveness of your Data Logic and Blueprints across your CRM. It addresses two main types of issues: records that a Blueprint was designed to catch but missed, and records where a Blueprint's output was correct at one time, but the database has since drifted from the Blueprint design. Data Integrity proactively identifies both types of gaps, so you don't discover issues only after they've already spread downstream.
Where to Find Data Integrity
Data Integrity lives in the left navigation as its own expandable section, sitting above Data Management and RevOps Acceleration.
To navigate to Data Integrity:
- In the left navigation, click Data Integrity to expand it.
- Select the view or module you want to open: Overview, Observability, Recommendations, Data Logic, or Blueprints.
Each of the five items has its own dedicated page, and the next section explains what each is for.
Data Integrity also appears on your Welcome dashboard (Dashboards > Welcome), where a card shows headline numbers and the four templates most in need of attention—a quick way to check status each day as you log in to Insycle.
Views and Modules Within Data Integrity
Data Integrity includes three views and two modules, each serving a different part of monitoring and improving your Data Logic coverage.
Overview
The Overview provides an at-a-glance health check for Data Integrity, showing four headline metrics—Coverage, Records Drifting, Fields Governed, and Records Governed—each with a plain-language comparison to a prior period, plus two trend charts (Coverage Trend and Drift Trend) broken out by object type. The Overview provides a quick, high-level snapshot that you can easily scan or screenshot, with a link to Observability for more details.
See Understanding the Data Integrity Overview for a complete walkthrough of Overview's metrics and trend charts.
The image above shows the Data Integrity Overview page for a demo HubSpot account, displaying four headline metrics — Coverage at 83% (down 12.3pp vs. 2 days ago), Records Drifting at 159 of 196 (unchanged), Fields Governed at 18 (down 5), and Records Governed partially visible at 196 (up 30) — alongside a Coverage Trend chart and the beginning of a Drift Trend chart, both covering the period 7/26/2026–7/28/2026, with the Data Integrity section of the left navigation expanded to show Overview, Observability, Recommendations, Data Logic, and Blueprints, with Overview selected.
Observability
Use the Observability view to investigate a specific Data Logic template. Observability lists every Data Logic template enabled for Observability in a table, showing its object type, records in scope, a Coverage/Unmatched/Flagged breakdown bar, a trend sparkline, a drift count, and a status badge (Stable, Needs Attention, or Regressed). Selecting a template opens a detail panel showing its Blueprint input/output mappings, a Coverage breakdown with its own trend charts, and three tables—Coverage Gaps, Drift by Field, and Blueprint Inconsistencies—each with an action to export or analyze the underlying records.
See Using the Observability View for a complete walkthrough of the template table, detail panel, and action tables.
The image above shows the Data Integrity Observability page for a demo HubSpot account, displaying three headline metrics — Coverage at 52%, Records Drifting at 133 of 196, and Attention at 12 of 15 — with a template list below showing three visible Data Logic templates: Near-Miss Detection (Companies, 118 in scope), Broken Country & State Normalization (Contacts, 70 in scope, selected with a yellow checkbox), and lead source harmonization (Contacts, 108 in scope) — each with a color-coded Coverage bar showing matched, unmatched, and flagged record counts alongside a trend sparkline.
Recommendations
The Recommendations view provides a single priority queue across all enabled templates. Recommendations takes the same three findings Observability surfaces per template — Top Opportunities (coverage gaps worth adding to a Blueprint), Top Output Drift (fields drifted from their assigned Blueprint output), and Top Blueprint Inconsistencies (Blueprint rows with contradictory logic) — and flattens them across all templates, ranked by actual record count rather than organized per template. Each row includes a Review button that opens the relevant template in the Observability view.
See Using the Recommendations View for a complete walkthrough of how items are prioritized and reviewed.
The image above shows the Data Integrity Recommendations page for a demo HubSpot account, displaying the Top Opportunities panel — coverage gaps worth adding to the Blueprint — with three Contacts templates listed: Near-Miss Detection showing one coverage gap (Field Name → <Empty>), lead source harmonization showing three gaps (Lead Source (Contains) → <Empty>, Lead Source Original partially visible, and Referrer Domain (Ends With) → IMPORT), and US Zip to City & State (an Insycle-provided template) showing one gap (Zip → M6K 1A7).
Data Logic
The Data Logic module defines how a Blueprint's logic matches your CRM fields and applies to your records. Data Logic controls input mapping, output mapping, update conditions, and filtering, and is where you configure, run, and schedule the templates that Data Integrity monitors. A template becomes observable — tracked across Data Integrity's reports — by turning on its Observability toggle in the template toolbar.
See Module Overview: Data Logic for the complete configuration reference.
The image above shows the Data Logic module for a demo HubSpot account, filtered to the Contacts object type, with the "Job Title Normalization & Persona Assignment" template selected in the template toolbar and 1. Pick Blueprint expanded — showing three Blueprint source options (Generate with AI, Explore Examples, and Use Reference Data) — with Explore Examples selected and the Job Title Normalization + Persona Assignment Blueprint chosen from the dropdown.
Blueprints
Blueprints are CSV-based tables that store the business logic—the conditions and outcomes a Data Logic template applies. From the Blueprints page, you can create a new Blueprint by uploading a CSV or generating one with AI; Blueprints are versioned and managed independently of Data Logic, so the same Blueprint can be reused across multiple templates.
See Blueprints for details on authoring and versioning a Blueprint CSV.
The image above shows the Blueprints page for a demo HubSpot account, with Upload and Generate buttons for creating new Blueprints, and a list of three existing Blueprints — Country to ISO2 Code Standard (281 rows, 2 columns, version 1), Job Title → Seniority Classification (33 rows, 3 columns, version 1), and Deal loss reason normalization (6 rows, 2 columns, version 1) — each displaying its source file name, version number, and unique ID.
How Data Integrity Measures Coverage and Drift
Coverage tells you whether a record is actually being handled by your Data Logic logic — a record has Coverage when it matched a Blueprint row and received that row's output values.
Drift tells you whether a record's output still reflects what your logic assigned — a record has Drift when it previously matched a Blueprint row correctly, but the field has since changed to something else, so what's in your CRM no longer matches what Data Logic wrote.
Both come from the same underlying process. Every time your CRM data flows into Insycle — on every sync and every time an update operation runs — an ingestion cycle evaluates the in-scope records of your observable Data Logic templates (templates with Observability turned on) against their Blueprints.
Only records found by an observable template's filters are evaluated at all — these are your Records Governed. Records outside that scope aren't checked, so nothing about them will ever appear in a Data Integrity report. Within that governed population, each record lands in one of three states:
- Coverage — The record matched a Blueprint row.
- Unmatched — The record's values didn't match any Blueprint row. These are your coverage gaps.
- Flagged — The record is set aside because applying the Blueprint to it would create an inconsistency, typically when a field is used as both an input and an output and the value the Blueprint would write isn't recognized by any input row.
Coverage and Drift trend charts, on both Overview and Observability, are built from a daily rollup of these per-record results, so any number you see can be traced back to a specific population of real records rather than an estimate.
Additional Resources
Frequently Asked Questions
- Check out the Data Logic & Blueprints FAQs to find answers to common questions about creating, editing, and applying Data Logic and Blueprints.
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