Clean Data In. Clean Data Out.
Bad data doesn't just live in your CRM. It travels — into your MAP, into your segments, into your lead scores, into your campaigns. Paminga gives you the tools to intercept and correct it at every point it enters or moves through your instance.
Native Normalization at the Point of Capture
Standardized before it ever hits your database.
Some data standardization happens automatically in Paminga before you ever have to think about it. US state and country values captured through Paminga forms are normalized natively — so what enters your database is clean and consistent from the moment of submission.
Form Submission
Contact fills out a Paminga form with raw input valuesNative Normalization
State and country values standardized automatically on submissionField Mapping
CRM field translation handled automatically — no manual interventionClean Record
A standardized, consistent record lands in your database and CRMField Type Integrity & Picklist Enforcement
Rogue values stopped at the door.
Paminga honors the field types defined in your CRM — including picklist and dropdown values — and enforces them at the MAP level. Dropdown fields can be locked to a defined set of values, mirroring the picklist constraints in your CRM.
That means a rogue value can't enter your MAP through a form submission, an import, or a manual update — and it can't propagate to your CRM and cause a field rejection downstream.
Platforms that don't honor CRM field types create a category of data quality problem that's invisible until it breaks something — a sync failure, a field rejection, a campaign that silently excludes records because the value doesn't match. Paminga eliminates that class of problem at the point of data entry, not after the fact.
Action Sets
Build once. Apply everywhere. Update once.
An action set is a saved collection of actions — field updates, normalization rules, standardization logic — that you build once and reference from anywhere. CSV imports, workflow triggers, Zapier actions, API calls — any entry point that can trigger an action can reference an action set.
Action Set — "New Record Standardization"
If your team performs the same sequence of data cleanup steps every time a new record enters the system, an action set turns that process into a single reusable object. Update it once and the change propagates to every place it's referenced.
True Order of Operations
Actions run in the order you define. Every time.
Data cleansing logic only works if it executes in the right order. In platforms where actions process simultaneously — or where execution order requires explicit manual configuration — cleansing rules can conflict, producing unpredictable results. In Paminga, actions execute sequentially by design. Every action completes before the next one begins.
No race conditions. No hidden system logic overriding the order you defined. Set up your cleansing logic in the order it needs to run. It runs in that order. Every time.
Google Ads Integration
Your MAP data driving your paid media. No spreadsheet handoffs.
Paminga connects natively to Google Ads, enabling you to use your MAP data to drive paid media targeting and measurement — without manual audience exports or spreadsheet handoffs.
Add to Google Ads Audience
Use Google's Customer Match to add contacts from Paminga directly to a Customer List — enabling retargeting across Google Search, Shopping, Gmail, YouTube, and the Display Network.
Remove from Google Ads Audience
Automatically remove contacts from a Customer List when they no longer meet the criteria — converted customers, unsubscribes, disqualified leads.
Record Google Ads Conversion Action
Track and measure valuable customer activity across Google Ads by recording conversion actions directly from Paminga workflows, triggered by the contacts and conditions you define.
Google Tag Manager Data Layer Push
Push data to GTM's Data Layer when a Paminga form is submitted — enabling seamless coordination between your MAP and your tag management layer.
See It in Action
See how Paminga intercepts and corrects bad data at every point it enters your instance.
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