B2B Product Management: The Use Cases That Outgrow Spreadsheets And Four Tools Compared

B2B buyers now do most of their homework alone. In a Gartner survey of 646 B2B buyers, 67% said they prefer a rep-free buying experience, and 45% used AI during a recent purchase. So your product pages and distributor feeds carry the conversation a sales engineer used to have.

An earlier Gartner survey found that 69% of B2B buyers see inconsistencies between a supplier's website and what its sellers tell them. Most of those inconsistencies start in product data, long before anyone talks to a buyer.

Key Takeaways

• B2B product data gets hard because of attributes with units, classification standards like ETIM, relations between products, and the number of output formats. SKU count is a weaker signal.
• The strongest triggers for a PIM are distributor feeds, staged launches across engineering and marketing, generated datasheets, and compliance data for the EU Digital Product Passport.
• A PIM sits next to the ERP. The ERP owns commercial and logistics data. The PIM owns the description of the product.
• Akeneo and Inriver fit companies that want SaaS from a large vendor. Pimcore fits teams with in-house or partner developers. AtroPIM fits teams that want a configurable open-source system with published prices and a choice between on-premise and SaaS. Each has trade-offs, described below.

Why B2B Product Data Breaks In Different Places

A B2C product page can get by with a title, photos, a price, and some copy. A miniature circuit breaker can't. Its buyers filter by rated current, breaking capacity, number of poles, and tripping characteristic. A wrong value means the wrong part on a construction site.

Attributes carry units and fixed value lists. The same flange dimension appears in millimeters for one market and inches for another. Products rarely stand alone: a pump has seal kits, a successor model and accessories that fit only certain variants. And the data has many readers. Your own shop, wholesaler systems, marketplaces, printed catalogs, configurators and tender platforms all need the same facts in different shapes.

Lifecycles are long too. A discontinued valve still needs complete data for years, because customers order spare parts for installed units.

The ERP is usually where this data starts, and it's usually where it gets stuck. ERP item masters are built for transactions: article numbers, prices, stock levels, production bills of materials. They aren't built for 150 attributes per product class in eight languages, with approval steps and channel-specific exports. Teams fill the gap with spreadsheets. Then the spreadsheets multiply, each owned by a different department, each slightly out of date.

Catalog size matters less than people expect. A manufacturer with 3,000 technical SKUs and ten distributor formats already has a problem that spreadsheets can't hold.

Product Information Management Use Cases In B2B

Technical Products Classified By ETIM Or ECLASS

In electrical, HVAC, plumbing, and building technology, wholesalers expect product data classified by ETIM. The standard is large. ETIM 10.0, released in December 2024, contains 5,640 classes and 16,728 features. Each class defines which features describe a product and which values and units are allowed. ECLASS does a similar job across a wider range of industries.

You don't need all of ETIM. You need the classes that match your assortment, filled. A PIM with proper ETIM support assigns a class to each product, pulls in that class's feature list, enforces value lists, and stores numeric values with their units.

Keep your own category tree separate from the ETIM classification. Your website navigation and a wholesaler's classification serve different readers, and forcing them into one structure breaks both.

Treat release changes as projects. Between ETIM releases, classes get added, deprecated, or reshaped, and features move between classes. Some customers ask for one version while others already want the next, so the system should hold more than one classification version per product during a transition.

Feeds For Distributors And Wholesalers

Most B2B manufacturers sell through distributors, and every distributor wants data in its own shape. Some accept BMEcat, the XML catalog standard maintained by the German purchasing association BME. Some ask for ETIM xChange, the JSON-based exchange format ETIM International launched in 2024. Many still send an Excel template with their own column names and value codes.

Each template looks like a small task. Together they become a part-time job. Errors come back weeks later as rejected imports or as products that don't show up in a distributor's filters.

A PIM turns this into configuration. You keep one product record and define an export per channel: which products, which attributes, which value mappings, which file format. When a distributor changes its template, you change one mapping. Completeness rules can also differ per channel, so a wholesaler that requires every mandatory ETIM feature gets checked against that standard, and your website against its own.

Count your outbound formats and the hours spent on each per month. That number makes the business case faster than any vendor slide.

Spare Parts, Accessories And Other Product Relations

Repeat orders in B2B often start with a relationship. A buyer replacing a worn seal needs the right seal kit for a pump installed nine years ago. An installer needs the mounting bracket that fits one specific housing size.

The ERP's bill of materials doesn't cover this. It describes how a product is built, including internal components the customer never sees. Customer-facing relations are a separate layer: compatible spare parts, accessories, successor models, sets with quantities. Each relation type needs its own data, like a quantity or a position in an exploded drawing. Some relations apply only to certain variants.

Test relations early in any evaluation. Ask how the system models a relation with its own attributes and how relations get exported to your shop and to distributors.

Staged Launches Across Engineering And Marketing

New product introduction in B2B rarely happens in one step. Engineering finalizes technical data first. Certificates, marketing copy, translations, and photography arrive later, each on its own schedule. Without staged publication, the whole record waits for its slowest part.

In projects we implemented, this was often the first problem a manufacturer wanted fixed. One event technology manufacturer with several brands came to us from another enterprise PIM. Technical specs, marketing content, and images were ready at different times, and the old system had no support for publishing in stages. We configured workflows so technical data goes live first and enriched content follows when it's approved. The system now generates datasheets from the structured data, so they're current the moment the data is.

That migration also taught a lesson worth repeating. Not all data came out of the old system's export cleanly, structured or unstructured, and part of it needed manual rework. Budget for that in any PIM switch.

Datasheets And Printed Catalogs

PDF datasheets are still how B2B products travel. They get attached to quotes and uploaded to tender platforms. When someone maintains them by hand in Word or InDesign, they drift away from the website data.

Our customers turn to us with a version of the same story. A German manufacturer of industrial blades kept product data in Excel sheets, ERP exports, and marketing documents. Every catalog update meant repeating the same edit in several systems, and version control was difficult. After the move to a central PIM, technical specs, descriptions, media, and documents sit in one place with versioning and access rights. Validation rules and completeness checks run before any publication or export. Datasheets and catalogs come out of the structured data, and the team manages translations centrally, which makes other markets easier to serve.

The practical point: generate documents from data. Templates per market or brand handle layout, and the PIM handles the facts.

Supplier Data For Distributors

Distributors face the problem from the other side. They receive data from hundreds of manufacturers, in every format described above, and need it in one consistent structure. The PIM work here is import mapping and validation. At a larger scale, it adds a supplier portal where manufacturers upload data and see what's missing. Vendors often price supplier onboarding as a separate module, so check what's included before comparing quotes.

Compliance Data And The Digital Product Passport

The EU Digital Product Passport moved from policy to infrastructure this year. The European Commission launched the DPP Registry on 20 July 2026. The first fixed deadline comes from the Battery Regulation (EU) 2023/1542: from 18 February 2027, EV batteries, light means of transport batteries and industrial batteries above 2 kWh need a battery passport.

Construction products follow under the revised Construction Products Regulation. The ESPR working plan for 2025 to 2030 lists further priority groups, including steel, aluminium, textiles, furniture and tyres, with requirements set product group by product group through delegated acts.

A PIM is the natural home for model-level passport data: materials, recycled content, repair instructions, declarations of conformity. Item-level data is another matter. Depending on the product group, a passport applies per model, per batch, or per item, and battery passports are issued per individual battery. Serial numbers and production batches usually live in MES or ERP systems. A passport also needs a unique identifier, a data carrier such as a QR code, a registry entry, and a hosting service.

So the realistic setup is a PIM plus a DPP service, with the PIM feeding the static part. Ask vendors exactly which part they cover.

The same structure helps with today's compliance work. CE declarations, REACH and RoHS documents get attached to the right products, with validity dates someone actually checks.

Product Data For AI Search And Buying Agents

Nearly half of B2B buyers already use AI during purchases, so the first reader of your product data is often software. Gartner links the heavy client interest in PIM partly to demand for structured, enriched product data that AI agents can use.

Assistants and buying agents compare products field by field. An engineer who asks for a 24 V DC relay with four changeover contacts for DIN rail mounting needs each of those facts stored as a value. Facts buried in a marketing paragraph are harder to match. A voltage stored as the text "approx. 24V" can't be compared with anything.

Some PIM vendors now expose product data to AI tools through MCP servers. MCP, the Model Context Protocol, is the interface AI agents use to query other systems. Inriver has offered an MCP server since September 2025, Akeneo lists one as an add-on, and Pimcore advertises MCP integration in its PaaS edition.

AI also works inside the PIM. The common jobs are extracting attributes from supplier PDFs and spec sheets, suggesting classes, drafting descriptions and translations, and tagging images. In the event technology project described above, the team uses an LLM to tag product images for the online store and to speed up translations.

Two rules keep this safe. Mark every AI-generated value and route it through approval before it reaches a channel. And keep certified or safety-relevant values, such as rated voltage, breaking capacity, or IP rating, out of unreviewed AI enrichment altogether. A clumsy description costs you a click. A wrong breaking capacity is a liability.

For most catalogs, the priority stays the same: fill the attributes before you polish the copy.

Units, Languages And Markets

ETIM distinguishes four feature types: alphanumeric value lists, logical yes or no values, single numeric values, and ranges defined by two numbers. Numeric and range features always need a unit, except counts such as the number of poles. That rule works as a default for any technical catalog, ETIM or not.

Store numbers as numbers, with the unit in its own field. A value typed as "230V", "approx. 5 kg" or "1/2 inch" can't be filtered or converted. A measurement attribute that holds 230 and V separately can. Ranges need two values and one unit, so an operating temperature from minus 25 to 60 °C is stored as a minimum and a maximum.

For other markets, pick a base unit per attribute and convert at export. Set rounding rules per attribute: 25 mm can round to 1 in for a catalog table, while a fitting dimension needs 0.984 in. When a value comes from a certificate or test report, publish it as stated and add the converted figure next to it.

Unit codes differ by output too. ETIM gives every unit a language-independent identifier. Many procurement platforms expect UN/ECE Recommendation 20 codes in BMEcat files. Mercateo, for example, asks suppliers to use only valid UN/ECE 20 codes in the ORDER_UNIT and CONTENT_UNIT fields. ERP systems often use internal codes of their own. A mapping table per output format solves this once.

Packaging units are a B2B specialty. A box of 100 screws has an order unit (the box), a content unit (the piece), and some content units per order unit, and the price can refer to either unit. BMEcat carries this in ORDER_UNIT, CONTENT_UNIT, and NO_CU_PER_OU. These values usually start in the ERP, and the PIM has to pass them on unchanged to every catalog. Get them wrong, and a customer orders 100 boxes when they wanted 100 screws.

Languages benefit from the same identifiers. In ETIM, every class, feature, value, and unit has a language-independent ID, and only the descriptions change by language. A product classified once can go out with standard feature names and value labels in each language your ETIM version covers, and nobody has to translate "breaking capacity" by hand.

Decide at setup which attributes are localizable. Numeric technical values are global. Descriptions and legal texts are local. Locking global attributes against per-language edits stops a translator from "fixing" a dimension. Track translation status per locale and publish a locale only when it's complete. Inheritance helps here: a value set once on the master record flows to every locale unless a market overrides it.

Markets add their own attributes. A product sold in the EU carries CE marking and a declaration of conformity. The same product in North America may need a UL listing and a 120 V variant with a different plug. Assortments differ by country as well. Model each market as its own scope with its own completeness rules, so a product can be ready for Germany while still incomplete for the United States.

When A Spreadsheet Or ERP Is Still Enough

A PIM is overhead if you sell a few hundred products through one shop, have no distributor feeds, and change data rarely. A clean ERP item master and a shop with decent attribute support can carry that for years. Buying a PIM too early mostly buys you a second system to maintain.

The signals that you've outgrown that setup are practical ones:

• The same product data gets typed into more than one system.
• Distributors return your feeds with errors or ask for ETIM data you can't produce.
• Datasheets are edited by hand in Word or InDesign.
• Launches wait because marketing needs engineering data that sits in someone's spreadsheet.
• Nobody can say which file holds the current version.

In our experience, two of these are enough to justify a proper evaluation.

How We Chose The Four Systems

The PIM market is crowded. Gartner published its first Magic Quadrant for PIM solutions in October 2026. Vendors that have announced Leader placements include Akeneo, Inriver, Salesforce (Informatica), Stibo Systems, and Syndigo. We used it as one input. The Magic Quadrant rates vendors on ability to execute and completeness of vision, which includes vendor viability and sales execution. Those factors matter, but they say little about whether a system can hold ETIM classes and spare-part relations for a mid-size manufacturer.

Our criteria for B2B product management:

• Data model depth for technical products: typed attributes with units, classification standards, and relations that carry their own data.
• Deployment choice, since many manufacturers run their ERP on-premises and have rules about where engineering data lives.
• Licensing and pricing a buyer can understand before the third sales call.
• B2B outputs such as distributor formats, generated datasheets, and partner portals.
• Active development in 2026 and a vendor with a track record.

Several well-known names didn't make this list for B2B reasons. Salsify and Syndigo center on syndication to large retailers and serve consumer brands best. Stibo Systems is a multi-domain MDM platform aimed at large enterprises. Plytix targets growing brands with simpler catalogs. That leaves Akeneo, Inriver, Pimcore, and AtroPIM.

Four PIM Systems For B2B Product Management Compared

Akeneo

Akeneo is a French vendor and one of the best-known names in PIM. Its paid offering, Akeneo Product Cloud, comes in three SaaS packages: Growth, Advanced, and Premium. The packages page lists Growth as starting at $0 a year, next to a free-trial button, and doesn't publish what a paid Growth contract costs. Advanced and Premium are listed as "call for quote", so expect a sales conversation on every tier. Collaboration workflows and advanced rights management start at Advanced. Each package includes one activation channel, and Supplier Data Manager, Shared Catalogs, and the commerce platform apps are add-ons on every package.

The paid editions now run as SaaS only. Akeneo ended support for its PaaS and on-premise 7.0 editions on 30 September 2026. The open-source Community Edition remains available under OSL-3.0, and Akeneo states that it continues to support it. Partners and integrators have published conflicting assessments of its future, so teams self-hosting it should plan their upgrade path with care.

Each product belongs to one family, which defines its attributes. Akeneo models variants as product models with up to two levels of variation. Its packages page also lists composable products for variations and bundles, plus a new product compatibility and fitment feature, which is relevant for spare parts. Associations can carry quantities, and reference entities hold structured records such as materials or brands. ETIM classification is available through a third-party app from Calago on the Akeneo marketplace.

Strengths for B2B: an interface that marketing and product teams pick up quickly, a large app marketplace, AI enrichment features added in 2026, and a Leader placement in the Magic Quadrant. Limits: the compatibility and fitment feature is new, so test it with your own spare-part data before relying on it. Paid editions run only as SaaS, and with add-ons and quotes on every tier, total cost is hard to estimate early.

Best fit: SaaS-minded companies with many digital channels and fairly regular product structures.

Inriver

Inriver is a Swedish vendor running a multi-tenant SaaS platform on Microsoft Azure, aimed squarely at manufacturers and brands. It reports more than 1,600 brands as customers and was also named a Leader in the 2026 Magic Quadrant.

Its B2B strengths are workflow and distribution. The Spring 2026 release added a visual workflow builder that lets business users design approval and enrichment flows without code, including steps run by AI agents. Syndicate Advance connects directly to large retailers such as The Home Depot, Walmart, and Wayfair. Brand Store gives distributors and partners a self-service portal for product data and assets. The Summer 2026 release added print and digital publishing automation.

Limits: Inriver is SaaS only and priced by quote. The Inspire AI agents are an add-on. Retailer syndication matters most to manufacturers selling through big-box retail, such as building products or power tools. A manufacturer selling mainly through electrical wholesalers will use less of it and should test classification handling closely in the demo.

Best fit: enterprise manufacturers with large catalogs and retail channels who want SaaS and are ready for an enterprise contract.

Pimcore

Pimcore, from Salzburg, Austria, is a data platform as much as a PIM. It combines PIM, MDM, DAM, and CMS functions on a PHP and Symfony stack. You define data classes in the admin interface, and its classification store handles standards such as ETIM and ECLASS. The Data Hub exposes data through GraphQL, and InDesign connectors cover print.

Since version 2025.1, the free Community Edition uses the Pimcore Open Core License instead of GPLv3. The license limits free production use to organizations with up to €5 million in annual revenue, plus non-profit and non-production use. Companies above that threshold need a paid edition. Pimcore's pricing page lists Professional at $9,900 a year and Enterprise at $29,900 a year for on-premise use, and prices the managed PaaS edition by quote. The license doesn't cap products, assets, or users. More than four independent production instances require Pimcore's Unlimited Edition.

Strengths: very flexible modeling, full control over hosting, published prices, and a broad partner network. Limits: integrations, workflows, and custom logic need PHP developers, so most projects run through an implementation partner, and the implementation budget often exceeds the license. The license change also ended free production use for companies above the revenue threshold.

Best fit: companies with developers or a trusted partner whose data scope goes beyond products into assets and web content.

AtroPIM

AtroPIM comes from AtroCore GmbH in Regensburg, Germany, and runs on the AtroCore data platform. The core is open source under GPLv3 and free for unlimited records and users, with paid modules and services on top.

You configure the data model in the UI: entity types, fields, relations, hierarchies with inheritance, and measure units. That makes it practical for unusual structures, such as product components or custom entities for spare-part compatibility. B2B pieces come as premium modules, including ETIM classification, a BMEcat adapter, product bundles, components, a PDF generator for datasheets, and an InDesign adapter for EasyCatalog. It runs on-premise or as SaaS in a private cloud.

AtroPIM lists prices on its pricing page. The SaaS Edition starts at €400 a month, including hosting and support. SaaS Premium, with all premium modules, starts at €1,930 a month. On-premise users can run the free edition and buy single modules as one-off licenses, for example €1,250 for ETIM classification, plus an optional yearly update subscription at 20% of the license price.

Limits: fewer independent agencies work with AtroPIM than with Akeneo or Pimcore, and AtroCore handles implementation itself. Integrations are configured data feeds instead of plug-in connectors. The software has no record limits, but support packages scale with catalog size.

Best fit: manufacturers and distributors with complex or unusual data models who want open source and a choice of hosting. Published prices help teams that want a budget before the first sales call.

Side-By-Side Overview

How To Run The Selection

Start with data before demos. Pick your 50 most awkward products: the ones with variants, spare-part relations, ETIM classes, several languages, and a datasheet. Send the same set to every shortlisted vendor and ask them to model it live.

Watching a vendor model your own spare-part relations and ETIM classes in real time is the fastest way to find the limits of its data model.

Then list every output you produce today, from the web shop to the last distributor template, and ask each vendor how that output would be generated. Ask specifically how an ETIM release upgrade works and whether two versions can exist side by side.

Calculate total cost over three to five years. Include license or subscription, implementation, integrations, hosting, and your own team's time for data cleanup. The cleanup happens with any vendor. It's internal work, and budgets often leave it out.

Check the exit path too. Ask how you'd export the full data model, relations included, through the API or as files. The migration story above shows how much depends on a clean export.

Finally, pilot one product line and one output channel before the full rollout. A distributor feed that currently takes days to prepare is a good first target, because the result is easy to measure.