PIM: stop searching for “the best tool” and choose the right solution for your organization.

Experience shows that a PIM can be a powerful performance driver... or a costly failure if the solution is chosen out of context. After 25 years of PIM projects led by our team, our conclusion is simple: there is no such thing as the “best PIM,” only solutions that are more or less suited to a given environment.

1. Why choosing a PIM is a strategic decision

A PIM is not just software, it is a central link in the product value chain.

• It structures product data to serve the business (time-to-market, e-commerce, marketplaces, B2B self-care, paper catalogs, retail, etc.).

• It impacts the organization (roles and responsibilities, governance, validation processes, supplier relationships).

• It determines operational performance (data quality, scalability, integration costs, maintenance).

In practice, a poor choice of PIM is not apparent during the demo, but becomes evident within 12 to 24 months: additional project costs, makeshift workflows, painful integrations, users who bypass the tool with Excel.

2. Understand the customer's context before discussing solutions

Before comparing solutions, it is important to understand the actual context of the organization. This is the most often overlooked aspect, even though it accounts for the majority of failures.

2.1 Use cases and business model

Some key questions:

• What are the key channels today (e-commerce, marketplaces, distributor network, sales force, catalog, POS) and tomorrow?

• Is the business B2B, B2C, D2C, or hybrid?

• Is the model volume-oriented (hundreds of thousands of SKUs) or value-oriented (more limited portfolio but very rich in content)?

What are the priority use cases for PIM: marketing enrichment, supplier onboarding, translation management, complex portfolio management (configurators, bundles, variants), regulatory compliance, etc.?

The solution suited to a pure-play e-commerce textile retailer is not the same as that for a B2B manufacturer selling spare parts on several continents.

2.2 Product data typology and complexity

The type of data to be managed strongly influences the choice:

• Depth of the product structure: simple (SKU, variants) or highly hierarchical (ranges, families, options, configurations)?

• Media richness: need for strong integration with a DAM, management of multiple visuals, videos, instructions?

• Technical data vs. marketing: importance of standardized technical attributes (ETIM, UNSPSC, GS1, etc.) vs. product storytelling, SEO content, sales pitches?

• Multi-country/multi-language: how many languages, how complex is local adaptation (regulatory, marketing)?

A PIM system that is heavily geared towards e-commerce may show its limitations when faced with extremely complex technical structures, whereas a more “industrial” PIM system will be better suited.

2.3 Data sources and application architecture

PIM is a link, not an island. It must be part of a controlled architecture:

• Is there already an MDM (customers, suppliers, products)? Who is the “master” of the product data?

• Is there an existing DAM, a central ERP, business systems (PLM, configurators, pricing systems)?

• How does data flow today: batch, near real-time API, flat files, EDI feeds?

• What is the target architecture: decoupling, microservices approach, event-driven, or a more monolithic architecture?

A PIM that connects well with APIs but poorly manages massive batch flows will not be perceived in the same way in an organization that is already very “batch-oriented.”

3. Strengths, weaknesses, and areas of expertise of PIM solutions

With experience, typical PIM solution profiles begin to emerge. The classic mistake is to contrast “good” and “bad” tools; in reality, each solution has its natural playing field.

3.1 Recurring solution profiles

Without naming names, we generally encounter:

• “E-commerce first” PIMs

  Designed to speed up web publishing, well integrated with CMS, very front-end oriented (marketing attributes, category management, SEO). Often excellent for large catalogs but with limited technical complexity.

• “Industrial/B2B” PIMs

  Robust on complex structures, nomenclatures, technical data, and compliance with standards. Sometimes less sexy on the UX side but very solid on modeling.

• Full data platform PIMs

  Solutions that flirt with MDM, with advanced modeling, governance, and complex workflow capabilities. Sometimes more cumbersome to implement but powerful in multi-domain contexts.

• Mid-market PIMs

  Targeting medium-sized organizations, simpler to deploy, lower TCO, but with limitations on very complex or high-volume scenarios.

  
  

3.2 Organization size and maturity

The same PIM can be a blessing for a structured international group and a nightmare for a medium-sized company in the process of structuring itself.

Points to consider:

• Investment capacity (licenses, integration, TMA, scaling up).

• Data & IT maturity: is there data governance, an enterprise architect, a structured IT department?

• Ability to absorb complexity: some PIMs require dedicated teams (data stewards, PIM product owners, functional administrators).

In an SME or mid-market company, the “perfect” tool that is too cumbersome or too complex will end up underutilized.

4. A methodical and ROI-focused approach

Choosing a PIM should be approached as a strategic investment, not just a simple software purchase.

4.1 Clarify business objectives and expected ROI

You don't choose a PIM to “better manage product data,” but rather to:

• Reduce time-to-market (launch a new range faster, list a supplier more quickly).

• Increase conversion and average basket size (better content quality, better search, fewer returns).

• Reduce internal costs (less re-entry, fewer errors, less back-and-forth between departments).

• Facilitate the opening of new channels (marketplaces, partners, countries, networks).

From the outset, a few target indicators must be set: time to market, completeness rate, speed of supplier onboarding, error detection rate, etc.

4.2 Structuring the analysis: context, needs, constraints

An approach that our team applies systematically:

• Mapping the existing situation

  Current processes, systems, flows, concrete pain points (where time is lost, where errors occur, who re-enters what).

• Defining priority use cases

  We prioritize: what absolutely must be addressed in the short term vs. what falls under phase 2 or 3.

• Macro modeling of product data

  Product types, essential attributes, variants, languages, relationships between entities (products, families, kits, parts).

• Architecture analysis

  Target positioning of the PIM: master or non-master, relationship with ERP, MDM, DAM, e-commerce, PLM.

• Non-functional constraints

  Volume, expected performance, SLA, security, hosting (cloud, on-premises, sovereignty), reversibility.

This framework then allows PIM solutions to be “read” from a business and technical perspective, rather than through a simple list of features.

4.3 PoC, benchmarks, and informed decisions

Two common pitfalls:

• Benchmarking based on a checklist of features, without real-world scenarios.

• A “showcase” PoC that does not reflect the true complexity of the customer's environment.

A good approach:

• Define a realistic PoC scenario, with “real” products, real data, and a few slightly challenging cases (borderline cases, exceptions).

• Involve business representatives (marketing, e-commerce, offerings, data) from the PoC stage onwards, not just IT.

• Measure the configuration effort, the clarity of the modeling, the ease of integration, and the ability to manage real processes (workflows, validations, translations, supplier imports).

The decision must be made by considering at least four factors: functional suitability, technical/architectural suitability, the teams' ability to adopt the solution, and projected TCO/ROI.

5. Data governance and value chain

Choosing a PIM without discussing data governance is like building a highway without considering who will be allowed to use it and at what speed.

5.1 Reliable sources, roles, and responsibilities

Some key elements:

• Identification of “sources of truth”: ERP, MDM, PLM, suppliers, internal files, third party application (like Data Punks - Fuse).

• Definition of roles: who creates, who enriches, who validates, who publishes (and to which channels).

• Implementation of management rules: attribute requirements, completeness rules, version management, archiving.

The PIM must align with this governance: some tools provide in-depth support (advanced workflows, data quality rules), while others are lighter and require completion by the organization or additional components.

5.2 Responsiveness, reliability, and performance

Depending on the sector, the responsiveness of the product value chain is a key factor:

• Retail/e-commerce: need for fast cycles, high seasonality, promotions, campaigns, near real-time responsiveness.

• Industry/B2B: importance of reliability, traceability, stability of repositories, sometimes over longer but highly regulated cycles.

PIM sizing, hosting mode, integration strategy (APIs vs. batch), and monitoring must be consistent with these requirements.

6. Our role: supporting informed choices, not selling tools

After numerous projects, we have learned that the real key to success lies not in the name of the solution chosen, but in how the choice is made and implemented.

Although we are agnostic when it comes to vendors, our team has detailed functional and technical knowledge of PIM solutions, which allows us to provide in-depth advice on the choice and guarantee feasibility in implementation.

Our support is based on a few strong convictions:

• Be agnostic when it comes to vendors

  The goal is to find the solution best suited to the client's context, not to push a pre-selected tool.

• Working with both business and IT

  PIM is at the crossroads of business (time-to-market, product experience) and IT (architecture, integration, security) challenges. Both must be involved from the outset.

• Combine strategic vision and feedback

  Drawing on decades of PIM projects allows us to anticipate pitfalls: overly theoretical modeling, over-parameterization, architectural choices unsuited to the reality of the teams, and underestimating the scale of change management.

• Think ecosystem, not “isolated product”

  We don't limit ourselves to PIM: MDM, DAM, ERP, e-commerce platforms, translation tools, marketplace connectors... Value comes from the coherence of the whole.

In summary, choosing a PIM solution is not about sorting through publishers' marketing brochures: it's about aligning product strategy, architecture, governance, and human resources around a tool that will be central to the company's commercial performance. Our experienced support allows you to transform this decision into a controlled investment, with a measurable ROI and a clear path for future development.