Data Quality

Overview

Data Quality cleans customer records before they reach the systems that act on them. Submit a list in whatever shape you have it — webinar registrants, trade-show leads, an inherited CRM export — and get back records where emails, phone numbers, addresses, job titles, and person names have been parsed into structured fields, normalized to consistent formats, and checked for structural validity.

Beyond cleanup, Data Quality classifies each record into your own segments and scores it against your own criteria, so a list arrives ranked and segmented rather than raw.

Results are returned to you. Data Quality does not route records and does not write back to your CRM or any other end system — the segments and scores it returns are inputs your own routing and prioritization rules act on, so you stay in control of what gets pushed.

Supported Attributes

Each attribute supports its own set of operations. Operations in the Free column cost no credits; operations in the Credit charged column are billed per result returned.

Attribute	Free	Credit charged
Email	Parse, Validate, Normalize	—
Phone	Parse, Validate, Normalize	Line type, custom normalization
Address	Parse, Normalize	Verification, custom normalization
Job Title	Normalize	Custom normalization
Person Name	Parse, Validate, Normalize	Custom normalization

Email has no optional operations. Email supports parse, validate, and normalization only — there is no email verification or bounce checking, and no custom normalization for email. Addresses have no validate step; verification verifies deliverability of the address. Job Title returns normalization only.

Validation is structural, not deliverability. Validation confirms a value is well-formed — that an email has an @ and a domain, that a phone number has a plausible digit count. Address verification is the only deliverability signal available. Data Quality does not check whether an email will bounce, and does not report whether a phone number is active, inactive, or disconnected.

How to Use?

Use the three functions together: clean the records first, then classify them, then rank them.

Function	What it does	Typical use
Prepare	Parses, validates, and normalizes values across the five supported attributes.	Clean a list of trade-show leads so emails, phones, and addresses are usable before import.
Segment	Sorts records into buckets across one or more dimensions, using rules you define.	Classify inbound leads by territory or persona so your routing rules can act on the result before a rep sees them.
Score	Applies a scoring model you define and returns a number per record.	Rank an account list against your ICP so reps work top-down instead of alphabetically.

Recommended flow: Prepare the records → Segment them into your buckets → Score them against your model → export the results to your end system.

Limits

Every call is synchronous and returns results inline. Batch size is capped per function, and the request rate is shared across your whole tenant.

Function	Max records per request
Prepare	30
Segment	100
Score	100

Rate limit: 25 requests per second, tenant-wide. This ceiling is shared across every endpoint and every caller in your tenant — it is not per-function, per-user, or per-credential. A bulk job running at full rate will compete with any other Data Quality traffic in the same tenant, so leave headroom and retry on 429.

Credits Usage

You are charged only for the results returned. Core cleanup is free; the optional operations you opt into are billed.

Operation	Uses Credits?
Parse, validate, and standard normalization	No
Custom normalization	Yes
Address verification — returns verification status, address type, and coordinates together	Yes
Phone line type	Yes
Segment run	Yes
Score run	Yes
Creating, reading, updating, or deleting a config	No

You are not charged for what fails. An item that errors is not billed; the successfully processed items in the same batch are billed normally. An input that cannot be enriched is not charged for that enrichment, and an address in a country where address type is unsupported is not charged for address type.

Availability

Capability	Available
API	Yes
MCP Server	No
CLI	No
SDKs	No

Data Quality is in Beta, available with GTM.AI Self Serve via the Builder Bundle. Beta usage is billed at full rate; there is no introductory credit allowance.