Connectors
The last mile, wired in
Connectors give Narrative a native presence in every system you already run — warehouses, CDPs, DSPs, activation tools, and more. Data moves between them the way it should have all along.
The modern stack doesn’t actually talk
Every tool promises interoperability, but the last mile — wiring them together — still falls on your team.
Custom by default
Every new platform is another bespoke pipeline to build, monitor, and maintain
Data stuck in place
Whatever lands in the warehouse stays there; whatever leaves still needs reformatting
The loop never closes
Activation runs in one system, measurement in another, and the round-trip is on you
What changes when every system speaks
Here’s what the stack looks like when the connections are already made and the data is already normalized.
Skip the custom work
Pre-built connectors handle authentication, formatting, and delivery across every source and destination — no engineering backlog
Data where you need it
Move data out to ad platforms, DSPs, and CRMs, or bring it in from your cloud, clean and ready on both ends
Close the loop
Activation and measurement run on the same normalized foundation, connecting reach to outcome
Stop repeating work
Ready for deployment the moment you need it, without custom code, custom monitoring, or custom maintenance
THE SOLUTION
Normalized in, normalized out.
Connectors deliver pre-built integrations in and out of the platforms that power your business. Because data is already normalized, every connector works the moment it’s deployed.
THE SOLUTION
Skip the integration project
Auth, schema mapping, error handling, and recovery logic come built in, so a new platform on Monday is a new connector live by Monday afternoon, not a sprint.
THE SOLUTION
Nothing to babysit
Authentication, monitoring, and recovery all run as a managed service, so your team stops checking dashboards for failed syncs and starts shipping what comes next.
Your stack. Different teams. One flow.
Put a fully connected stack to work under a single governance layer.
For marketers
Activate everywhere, from one place.
Push resolved audiences and enriched data to any destination without filing an engineering ticket or waiting for the next sprint. The campaign runs where the customer is.
Point-and-click Query Builder
Reach meets outcome — finally.
Bring signal in from across the stack and send data back out to where it’s needed. Activation and measurement run on the same normalized foundation, so the feedback loop finally closes.
For engineers
Skip the custom work.
Lorem ipsum dolor sit amet consectetur. Sed blandit donec pretium feugiat imperdiet nisl. Nullam leo sed diam mi nullam. Ipsum id semper eu vel in lectus dolor.
WHY IT’S DIFFERENT
Connector Truths: The Principles Behind Modern Data Flow
Pre-built beats custom-built
Most “connectors” hand you a starting point and leave the rest to engineering — auth flows, schema mapping, error handling, recovery logic. Narrative Connectors are pre-built end to end, and because data is already normalized when it arrives, nothing has to be massaged on the way in or out. Every connector just works the moment it’s deployed.
Normalization is the integration.
The hard part of an integration was never the API. It was making the data on the other side actually usable. Because Narrative normalizes data on arrival, every Connector inherits that work: whatever you push to a destination lands ready to use, and whatever you pull in from your cloud is ready to query. The translation tax disappears because it’s paid once, in normalization, not at every endpoint.
Reach should always meet outcome
Activation in one system, measurement in another, and the round-trip handed off to a spreadsheet — that’s the loop most stacks never close. Normalized data means activation and measurement run on the same foundation, so every campaign reports back where the work happens, and every signal informs the next decision.
Open beats opaque
An integration you can’t see inside of is an integration you can’t trust. Every Narrative Connector exposes its mapping, logic, and configuration, so your team can audit what’s moving, customize what needs to be, and extend where it fits. Your stack, fully visible.
Proven results
Wired in to dial up the possibilities
10+
pre-built integrations across the modern stack
0
pipelines to maintain in-house
100%
managed end-to-end
Proven Results
Reach without compromise
“Partnering with Narrative.io has empowered us to seamlessly scale our offerings across diverse social platforms. Ultimately, this collaboration has been key to achieving our objective: engaging with our customers exactly where they are."
Dennis O'Donnell, Head of Ad Product
The Weather Company
“What I am looking for is a #RosettaStone. I don’t have the resources to pick through endless data sets and clean and harmonize them. I am calling it the great marketing emergency. We’ve got all this data, but we need #AI to stitch it together as a means to help our clients drive growth. We have the ability to have a fluid conversation with the consumer at the different points in their journey.”
Domenic Venuto, Chief Product & Data Officer
Horizon
“Traditional commerce media models often expose brands to unnecessary privacy risks by moving data into third-party environments. Our work with Narrative eliminates that risk while unlocking sophisticated audience-building capabilities that deliver real outcomes.”
Marni Schpario
Block
Resources
Insights, stories, & resources for the teams building modern data infrastructure.
Blog
•
4
Mins
Narrative Reimagines the Marketplace: A Composable Hub for Data and AI Work
Blog
•
4
Mins
With Publicis' Acquisition of LiveRamp, Switzerland Just Picked a Side
Blog
•
4
Mins
Clean Rooms Were Necessary. They Were Never Enough.
Blog
•
3
Mins
Activate Your Audiences Across PubMatic's Sell-Side Platform
Blog
•
4
Mins
Data Marketplaces Should Work Like Infrastructure, Not Catalogs
Ask Us Anything
Straight answers to real customer questions.
Most teams are normalizing live data within days of connecting their first sources — not months. There's no multi-quarter implementation, no professional services dependency, no bespoke build required. You connect your sources, define what coherence looks like for your use case, and Narrative does the translation work. The timeline question is usually less about setup and more about how quickly your team can act on data that's finally consistent.
Those tools move data and act on it. They don't normalize it. They're built on the assumption that the data arriving is already clean, consistent, and semantically coherent — and in most real-world data partnerships, it isn't. Narrative is the layer that makes your existing collaboration and activation infrastructure work the way it was designed to. The teams getting the most from their data stack are typically the ones who've solved normalization first.
Most teams do, at first. The problem isn't the initial build — it's everything after. Every partner schema change breaks it. Every new data source requires rebuilding it. Every team transition means relearning it. The engineering debt compounds faster than the business value accrues. Narrative replaces a perpetual maintenance burden with infrastructure that's designed to absorb that complexity so your team doesn't have to.
Data and analytics teams at companies where external data is a core business input — not a supplement. Typically organizations that are buying data at scale, monetizing their own data assets, or running structured data partnerships with other companies. If your team is spending meaningful engineering time just making external data usable, that's the problem Narrative is built to eliminate.
AI models don't tolerate inconsistency. When a "user" in one dataset isn't recognized as the same "user" in another — different schemas, different taxonomies, different identifiers — your models train on noise and your outputs reflect it. Narrative normalizes data at the source so the AI layer above it is working with signal. Garbage in, garbage out isn't an AI problem. It's a normalization problem.
Your warehouse stores data. Your CDP activates it. Narrative normalizes it — resolving the semantic inconsistencies that make data from different sources incompatible before it ever reaches those tools. We don't replace your stack. We fix the layer underneath it that your stack assumes is already solved.