Key Takeaways
PIM projects most often fail before implementation because organizations select software without clear objectives, realistic expectations, or a deep understanding of their data, processes, and integration needs. The reasons for these are:
- Lack of clear business objectives
- Skipping data and process audits
- Expecting the PIM to be a "fix-for-all" solution
- Limited stakeholder involvement
- Selecting a PIM system based primarily on feature checklists and short-term investment
- Overlooking PIM integration challenges with existing systems
- Relying on demos only
- Ignoring Scalability.
Instead of repeating common PIM selection mistakes, organizations should:
- Run a proof of concept project (POC) with real data, for example, using sandbox environments offered by vendors such as AtroPIM or Pimberly.
- Define clear business objectives tied to measurable outcomes such as time-to-market, data quality, or channel growth.
- Audit existing data and processes early and define a target data model before vendor evaluation.
- Establish governance and ownership upfront, including workflows and validation rules.
- Involve all relevant team members from the start to ensure usability and adoption across the organization.
- Evaluate real workflows, not just features, using actual use cases and data, also partly within a POC.
- Assess final total cost of ownership, including integrations, training, and long-term maintenance.
- Evaluate integrations and scalability early to ensure the PIM fits both current and future needs.
- Don't rely entirely on what salespeople say. Ask for proof, references from similar cases, or proof of concept (POC).
Product Information Management (PIM) systems are introduced to solve very real and growing challenges: an increasing number of sales channels and trading partners, multilingual product descriptions, the need to produce data sheets and catalogs quickly, frequent corrections of product data errors, the need for integration with websites, online stores, and external partners. At the same time, organizations are under pressure to improve overall product data quality and consistency and withstand the ever-growing competition.
A PIM system can address all of these requirements, but only if the right system is selected. In practice, many PIM initiatives struggle or fail not because of poor implementation, but because of fundamental mistakes made during evaluation and software selection. These mistakes typically revolve around unclear goals, weak stakeholder alignment, and an insufficient assessment of how well the software fits real business needs.
This article examines the most critical mistakes to avoid when evaluating and selecting a PIM system, and explains the ways to perform quality PIM evaluation.
The Most Common Evaluation Mistakes
Starting Without a Clear Strategy or Objectives
The most fundamental mistake in PIM evaluation is the absence of a clear strategy. Without a defined vision, it is impossible to judge whether a PIM solution is suitable.
Many organizations start the evaluation process because they want to eliminate spreadsheets or centralize product data. While these are valid motivations, they are symptoms rather than goals.
Organizations also assume that any PIM system will automatically improve efficiency, data quality, or market reach, but without understanding what they actually need to achieve, it’s impossible to select the right solution.
Business objectives should be derived from the company’s strategic priorities, operational bottlenecks, and specific challenges in managing product information. For example, teams can look at:
Time-to-market issues
How long does it take to launch new products or update catalogs? Are there delays caused by manual spreadsheet updates, approval cycles, or inconsistent supplier data? An objective could be to streamline these processes so new products can be listed faster without errors.
Data quality gaps
Are product descriptions, specifications, and images consistent across all sales channels? Are translations incomplete or outdated? Objectives here can focus on creating a single source of truth for all product information, to make sure that data is consistent, structured, and reusable.
Market expansion or channel complexity
Does the company struggle to sell in new regions due to different languages, currencies, or local regulations? Objectives could include enabling smooth entry into these markets without requiring extensive manual data work.
Operational pain points
Which repetitive tasks or error-prone processes consume the most time for product managers, marketers, or content editors? Objectives might aim to automate these tasks or improve workflow efficiency.
By grounding objectives in real operational or strategic challenges, organizations can define what success looks like for a PIM project. Without this step, requirements tend to be vague, feature lists become generic, and the selected system often fails to address the problems that truly matter.
Skipping Data and Process Audits
Businesses must conduct a thorough audit of existing product data and workflows, and define a target data model before evaluating PIM solutions.
Skipping data and process audits is closely tied to unclear objectives. Before defining what success looks like, organizations must understand the current state of their product data and workflows. Without this foundation, requirements, migration estimates, and system evaluations are likely to be inaccurate, and gaps only appear after implementation begins.
Without a preliminary audit, organizations lack a realistic understanding of data quality, completeness, consistency, and structure. This makes it difficult to define accurate requirements, estimate migration effort, or test whether a PIM can handle existing complexities.
Similarly, failing to define a target data model before evaluating solutions prevents meaningful comparison. Without a clear taxonomy, attribute structure, and relationship model, it is impossible to assess whether a PIM can support variants, bundles, hierarchies, and localization requirements. These gaps often become painfully visible only after implementation has started.
Unrealistic Expectations about what a PIM can and cannot Do
Expecting the PIM software to “fix” organizational problems is a reliable path to disappointment.
Another common issue in PIM selection is setting unrealistic expectations. Many organizations assume that simply implementing a PIM system will automatically fix data quality issues or streamline broken processes. In reality, a PIM system facilitates the management and distribution of product information, but it cannot replace clear processes, defined responsibilities, and strong governance.
Without processes to validate and enrich incoming data, errors will continue to appear in catalogs and online stores.
PIM is an enabler, not a solution in itself. Success depends on combining the right technology with well-defined workflows, clear roles, and active governance.
Of course, PIM solutions that go beyond the boundaries of PIM, such as AtroPIM, which is built on top of AtroCore (an MDM and System Integration software), or Pimcore (an all-in-one solution for PIM, DAM, E-Commerce, and MDM), can definitely offer you more than any "classic" PIM software.
Delaying Governance and Workflow Decisions
One related mistake that often stems from unrealistic expectations is delaying discussions about data governance and workflows until after PIM software selection.
Without clear governance rules, validation mechanisms, and ownership models, even the best PIM system will quickly accumulate inconsistent, duplicated, or unreliable data. Weak workflows lead to unclear responsibilities and reduce trust in the system.
Governance and workflow requirements should influence PIM selection from the beginning, not be treated as an implementation detail.
Involving All Relevant Teams and Users
PIM systems affect nearly every department that touches product information: product management, marketing, sales, e-commerce, operations, customer service, and often external partners. Yet evaluation processes are frequently driven by a single department, most commonly IT or marketing.
When one area dominates the selection process, the resulting system tends to optimize for that group’s needs while neglecting others. This creates friction after go-live, when teams discover that the system does not support their day-to-day work effectively.
The employees who will use the PIM system daily, such as product managers, content editors, translators, and catalog managers, are often not involved in defining requirements or testing solutions. As a result, usability issues are discovered too late, leading to low user adoption and workarounds outside the system.
To avoid low adoption, involve all teams affected by product information in the PIM evaluation process.
Critical Mistakes in Comparing and Choosing a PIM Solution
Even when strategy and stakeholders are addressed, many organizations make critical errors when comparing PIM platforms and selecting the one that fits their needs.
A common mistake is choosing a PIM system that doesn’t meet essential functional needs, such as managing multiple languages, integrating with other systems, or handling complex product catalogs and digital assets. These limitations may not be apparent in demos but can cause major issues in daily operations.
Another common issue is focusing on features rather than processes. Evaluating vendors based on feature checklists (“Does it have workflows?”) says little about whether the system supports specific business processes (“How does it support our product launch or supplier onboarding process?”). A feature-rich platform can still be a poor fit if it does not align with how the organization actually works.
Before making your final decision on PIM vendor, map your real workflows by talking to the teams who handle product data daily. During demos or proof-of-concept tests, use actual data to see how the system handles multilingual content, integrations, and complex catalogs. Involve representatives from all affected departments early to uncover gaps and ensure the PIM truly fits your business processes.
Cost evaluation is also frequently flawed. Many organizations focus primarily on license fees while underestimating the Total Cost of Ownership. Long-term costs like maintenance, support, training, and system integrations are often overlooked during selection. This leads to unexpected budget overruns later on.
Closely related is the tendency to over-customize too early. Requesting extensive customizations before data models and processes are clearly defined leads to inflated quotes and rigid solutions. In many cases, these customizations turn out to be unnecessary once the organization better understands its actual needs.
Underestimating Integration Requirements
A PIM system does not exist in isolation. It must integrate with ERP systems, e-commerce platforms, CRM solutions, websites, marketplaces, and sometimes partner systems.
Standard APIs may not cover all the ways a company uses its systems, such as syncing complex product catalogs, connecting multiple sales channels, or automating updates between ERP, e-commerce, and PIM. Without testing real integration scenarios, the PIM may fail to work smoothly with existing workflows.
A proper evaluation should assess not only whether APIs exist, but whether they are robust, scalable, and proven in real-world integrations with the ERP, e-commerce platform, or CRM your company actually uses.
Relying on Demos Instead of Hands-On Testing
Beware that vendor demos are designed to show best-case scenarios.
Relying solely on them is another common evaluation mistake. Without hands-on testing or a proof of concept, usability issues, performance limitations, and data modeling constraints often remain hidden. These issues tend to surface only after contracts are signed, when changes are costly and difficult.
Running a pilot or proof of concept with real data and realistic workflows is one of the most effective ways to validate whether a PIM system truly fits the organization’s needs.
Reputable PIM vendors, for example, AtroPIM and Pimberly, support pilots or proofs of concept, and offer trial environments or sandbox instances where you can import real product data and test workflows without affecting production. Therefore, before starting a PoC, confirm with the vendor what environment, data, and features you can test. Ensure it supports your real workflows, not just demo data, so you can validate usability, integration, and process fit.
Focusing on Short-Term Fit Instead of Scalability
Many organizations choose a PIM system that works for their current situation, but cannot scale with future growth.
Be aware that, like ERP, only one PIM solution should be implemented over the long term. To achieve the best results, you should not change it every couple of years.
Technical scalability issues arise when systems struggle with large product volumes, complex relationships, real-time integrations, or high numbers of concurrent users. Organizational scalability issues appear when the PIM cannot support multiple regions, teams, role-based access, or automated workflows at scale. Ignoring scalability during evaluation often leads to performance bottlenecks, governance problems, and eventually costly re-platforming projects.
Dealing with Limited Adoptability
This is obviously the most challenging topic to evaluate. Salespeople of any PIM software would probably say, "Everything is possible," just to make a sale. In real life, many users would realize that not everything is possible and, of course, not always at a reasonable cost. Custom development may lead to higher update costs in the future. With cloud software, it's possible that customization won't be offered at all.
Early on, evaluate how far you can go with adoptability and at what cost.
To remove any doubts, you could ask for a demo session showcasing your "very special" feature or have it implemented in a POC project.