Marketing data integration for the actual multi-location operator stack
Pull data from POS, Google Business Profile, Yext, BrightLocal, HR, CMS, and CRM into one record per location — with the source-by-source schema differences handled for you.
The problem
You have data in 14 systems. The POS knows menus and hours. Google Business Profile knows what Google thinks you offer. Yext syndicates whatever you last gave it. The marketing spreadsheet is two weeks behind reality. HR has the manager bios that never made it to the website.
You tried Fivetran but it dumps everything into a warehouse and your marketing team cannot operate against a warehouse. You tried Zapier and the chains broke at 50 locations. You tried Funnel.io and it understood ad spend but not store hours. You hired a dev to build adapters and the deprecation maintenance ate a third of an engineer's week forever.
The deeper problem is that generic ETL tools assume customer or product data. They were built for moving operational data into a warehouse for analytics. Marketing-specialized tools blend ad-platform data for reporting. None of them produce one operational record per location with adapters built for the actual multi-location stack — POS, HR, Google Business Profile, Yext, BrightLocal, listings, CMS, CRM.
What success looks like
Every system that holds part of your operational truth has an adapter that already knows its schema. Data flows into one record per location automatically. A POS hours change picks up in real time. An HR bio update flows to the website. A new service in the CMS refreshes Google Business Profile categories. A new location opening seeds data into all 14 downstream systems.
Whatever shape each source exposes — Square POS service rows, Yext attribute strings, Google Business Profile enums, Notion properties — gets converted into the format your master record uses. Industry-specific validation (HIPAA, license status, ABV, FDA) runs before anything goes live. Systems that emit webhooks get picked up in real time. Legacy systems fall back to hourly sweeps.
Marketing operations stops being a data-firefighting role.
How most operators solve this today
A few categories of tools touch this. None of them were built for the actual multi-location operator stack:
Generic enterprise ETL (Fivetran, Airbyte, Hightouch, Census)
$300 to $50,000+/month
Built for moving operational data into a data warehouse for analytics. Assumes customer or product data shapes. No adapters for the operator stack out of the box, and marketing teams cannot work against a warehouse anyway.
Marketing-specialized integrations (Funnel.io, Supermetrics, Improvado)
$69 to $7,000/month
Blends ad-platform data (Google Ads, Meta, TikTok, GA4) for performance reporting. Strong on ad spend, weak on operational data. Produces reports, not the underlying record.
Workflow automation (Zapier, Make, Workato)
$20 to $5,000/month
Point-to-point hooks. The "source of truth" still lives in whichever spreadsheet you picked. Chains break at 50-plus locations across 4-plus source systems.
Custom-coded API integrations + dev team
$80,000 to $150,000 per engineer + ongoing maintenance
Vendors deprecate APIs constantly. Maintenance burden eats roughly a third of an engineer permanently. Every new source system is another project.
Build it in-house
Senior engineer ($130-220k) + ongoing maintenance
A six-to-twelve month build for v1 across the common stack. Custom POS or HR adapters are separate projects on top.
What changes when this is an agent skill
Adapters for the systems you actually run, on day one — Google Sheets, Airtable, Notion, Salesforce, HubSpot, Google Business Profile, Yext, BrightLocal, POS (Square, Toast, Lightspeed, Clover, Shopify POS), and the common HR platforms.
Each adapter already knows its source's quirks and the multi-location field conventions. Whatever shape the source exposes gets normalized into a single schema. Industry-specific validation (HIPAA, license status, ABV, FDA) runs before any record goes live. Modern sources stream in by webhook. Legacy sources fall back to hourly sweeps.
When two sources disagree on the same field, the conflict surfaces for reconciliation against rules you configure — source priority plus freshness, with a human review queue for anything the rules cannot resolve. Custom adapters for proprietary CMS or POS systems can be added through the engagement.
The total cost replaces $80,000 to $150,000 a year of engineering time plus $1,000 to $5,000 a month of generic ETL subscriptions. Marketing operations stops firefighting and starts shipping.
Agents that include this skill
Skills live inside agent rentals. To get this skill in production, hire any of the agents below — context-tuning at onboarding is included in the first month.
Master Record Canonicalization Agent
Ingests every operator source system, resolves per-location fact conflicts, and emits the canonical master record downstream agents consume.
FAQ
- What does the data integration actually do?
- Pulls data from every system that holds part of your operational truth — POS, Google Business Profile, Yext, BrightLocal, HR, CMS, CRM — and feeds it into one record per location. Each source has an adapter that already knows its quirks.
- How is this different from Fivetran or Airbyte?
- Those tools move data into a data warehouse for analytics. Marketing teams cannot work against a warehouse. This pulls data into one operational record per location, with adapters built for the actual multi-location stack instead of generic ETL primitives.
- How is this different from Funnel.io or Supermetrics?
- Those tools blend ad-platform data (Google Ads, Meta, TikTok) for performance reporting. This pulls operational data (addresses, hours, services, manager bios, license status) into the record your downstream marketing systems actually consume.
- Which sources are supported at launch?
- Google Sheets, Airtable, Notion, Salesforce, HubSpot, Google Business Profile, Yext, BrightLocal, Square POS, Toast POS, Lightspeed POS, Clover POS, Shopify POS, plus the common HR platforms. Custom adapters for proprietary systems get added as engagements require them.
- How is real-time versus batch handled?
- Systems that emit webhooks get picked up in real time. Systems that do not get hourly sweeps. Both feed the same downstream record.
- What happens when two sources disagree?
- The conflict surfaces and resolves against rules you configure — which system wins for which field, what counts as fresh enough. Anything the rules cannot resolve routes to a human review queue. The system learns from past decisions so repeat conflicts auto-resolve.
- Does this replace our existing Zapier or Make?
- For multi-location data ingestion, yes — Zapier chains break at 50-plus locations across 4-plus sources. For other automation (Slack notifications, cross-app triggers), keep what you have. The two work side by side.