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.
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
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.
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.
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.
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.
Sharpen every customer profile, in place.
Marketplace
The supply side of every enrichment play.
Providers and mapped attributes, all normalized and ready to query. Discover, license, and join external data without per-provider integration work, and without ever moving a row of your first-party data out of your cloud. Billions of data points, all joinable to the data you already have.
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
Enrich every use case.
- Classify
- Securely Collaborate
- Build my own identity graphs
- Activate Audiences
- Monetize
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.
Explore more
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.
Explore more
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.
Explore more
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.
Explore more
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.
Explore more
Straight answers to real customer questions.
How long does it take to see value?
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.
Why does data normalization matter more now that AI is involved?
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.