Data integration
Your product data lives in four systems, and you need all of them at once
A single description may depend on attributes from the PIM, imagery from the DAM, compliance data from the PLM, and fields maintained by hand outside all three. The same record then has to serve product pages, category pages, CRM campaigns and seasonal retail material. That makes this an integration and normalization problem before it is a generation problem, and it looks different in every organization’s landscape.
How the platform handles it
Import paths stay simple. The normalization work sits on our side.
That model is defined for you at the start of the engagement, by the engineers assigned to your account - not mapped by your teams into a fixed schema.
Ingestion from PIM, DAM, PLM and manual sources into one working model of your catalog.
Custom pipelines
Producing content is not one step
Content is generated across the levels of your data model — e.g. category, product, color variant — and then translated, reviewed and exported. Each step depends on the one before it. The sequence is not the same everywhere: some programs run import through export as a single job, others need review to sit before translation, after it, or in both places.
How the platform handles it
Pipelines: the sequence is configured per client — import, generation at each level, translation, review, export.
Generation runs level by level, each level using the attributes held there with the level above as context.
Every step reads from and writes to the content registry, so review can sit anywhere in the sequence and any stage can run on its own.
Locale precision
A language is not a locale
Configuration set at language level is insufficient for markets that share one. Vocabulary, register and search behavior differ between them, and because no translation step is involved, nothing in a conventional localization workflow catches it.
Category terms show it most clearly, because the whole page depends on the word. "Trousers" in the United Kingdom are "pants" in the United States, while the British term for "pants" is "underwear". A "jumper" in the UK is a "sweater" in the US, where a "jumper" is a "pinafore" dress. Same language, different garment, different search volume, different page.
How the platform handles it
Configuration is set per market, not per language.
Tone, register and constraints are defined market by market.
Search demand is resolved for the target market before content is generated, rather than adjusted afterward.
Continuous accuracy
Content is correct on the day it ships
A season lands. Attributes change, products are discontinued, guidelines are revised. The product pages are usually caught eventually. The training deck still featuring a discontinued line, or the CRM template built on last season's positioning, is not - because nothing is tracking it. Producing content once is a project; keeping a large multilingual content estate accurate is an ongoing operation.
How the platform handles it
The platform holds the state of your content estate: what exists, in which languages, at what status, and under which version of your rules.
When product data or a rule changes, the affected content is identified.
It is reproduced without reprocessing everything around it.
Channel-wide consistency
Governance often ends at the website
Product and category pages are governed. CRM templates, seasonal training material and wholesale documents are produced elsewhere, by agencies or local teams, under whatever rules apply locally. Newtone ensures consistency across all your content assets.
How the platform handles it
One set of rules, lexicons and glossaries governs every channel.
Channel-specific optimization is applied on top where a channel requires it.
The same verification applies wherever the content is destined.
We take your product data and return finished content, in the languages and formats you work in.
