I'm trying to...
Enrich
Augment your first-party data with the attributes that make targeting precise, segments meaningful, and outcomes measurable. Narrative makes enrichment a single normalized join with no per-provider plumbing and no technical heavy lifting.
trusted by global leaders
Today
The data is there. The plumbing is the problem.
Every enrichment provider ships a different schema, a different ID strategy, a different format. Joining 30 sources to one customer file becomes a custom-engineering project, and by the time the join works, the segment is already stale. The math was never the problem; normalization was.
JOINABLE BY DEFAULT
ONE NORMALIZED MARKETPLACE
ENRICH IN PLACE
ACTIONABLE ENRICHMENT
JOINABLE BY DEFAULT
Every attribute or ID matches the way your data does.
Rosetta Stone reconciles schema, naming, ID and value variations so when an attribute lands in your warehouse, it joins to your file the way it should.
ONE NORMALIZED MARKETPLACE
Providers and attributes, ready to query.
The Marketplace brings the breadth of third-party data into one governed environment with every attribute already normalized to a common schema.
ENRICH IN PLACE
No replication and no second environment.
Narrative runs inside your cloud so enrichment happens at your data, not in a third-party staging environment. Your customer file never moves. Instead, the attributes come to it, governed under the same controls as everything else.
ACTIONABLE ENRICHMENT
Distribute without the heavy lifting.
Discover, license, and join external attributes through a single workflow, then push enriched profiles to every destination via Connectors. The data team gets time back, the marketing team gets segments that actually work, and nobody has to learn a new query language to make it happen.
Why Narrative?
Sharpen every customer profile, in place.
Marketplace
Rosetta Stone
The layer that makes enrichment work.
Normalize schemas, naming, and value conflicts across every provider feeding enrichment so attributes land in your warehouse already aligned to your customer file.
“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
OTHER USE CASES
Enrich every use case.
CLASSIFY
Turn raw data into structured signal.
Normalize, label, and categorize data inside your warehouse — with ML, LLMs, and human feedback in one loop. Cleaner inputs make every downstream use case sharper.
harper.
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SECURELY COLLABORATE
Share data without ever shipping it.
Run collaboration in place — your data, your cloud, your governance. Make secure sharing the default, not the exception.
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BUILD MY OWN IDENTITY GRAPH
Own the spine your business runs on.
Configure match logic, swap providers on demand, pay only for net-new identities resolved. Your graph, deployed inside your cloud, under your control.
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ACTIVATE AUDIENCES
Get audiences from definition to delivery in hours.
Push resolved-person audiences to every DSP, ad platform, and CRM with pre-built Connectors. Compliance rides along; activation lag goes away.
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MONETIZE
Sell your data, keep your control.
Package, price, and license data on your terms. Buyers query it in place under your contracts and access rules with no bulk shipping, and no per-buyer custom prep.
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Resources
Insights, stories, & resources for the teams building modern data infrastructure.
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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.