Most businesses reach the same point during their PIM selection processes: Too many demos, too many opinions, and the sensation of not being any clearer about a choice than when they started. It’s certainly not because the market lacks capable platforms but the fact that most selection processes begin before the business has actually defined what it needs in operational terms.
Our article explains why so many PIM selection processes end up stalled, what really drives the ‘paralysis of analysis, and how to make a final decision more achievable by grounding what features you need in the reality of your product data management.
The market creates cacophony, not clarity
The PIM market is crowded. Enterprise platforms, mid-market tools, open-source options and broader commerce suites all lay claim to solving the same problems. Their websites tend to use the same language. Their demos show the same polished workflows. Their feature lists all appear comprehensive. All in all, it creates a false sense that your decision should be straightforward. In practice, it makes comparing systems more challenging.
Every vendor sounds plausible when the potential client’s requirements are left as vague aspirations. Every sales team can map your language onto their platform. Every demo can be tailored to show just enough of the workflow to appear credible. The impact on you is not to create confidence. It ends up in ‘process fatigue’.
This is where many businesses fall into one of three traps:
- Choosing the ‘safest brand’ rather than the best fit
- Choosing the cheapest entry point and underestimating implementation risks
- Delaying the decision because every option appears both possible and dangerous
The underlying issue isn’t the number of vendors in itself, but the fact that the majority of buyers are trying to evaluate the software before they’ve defined the problem in enough detail.
A problem which starts before vendor evaluation
Most PIM projects begin with a large spreadsheet full of diverse requirements. It looks structured. It feels rigorous. However, it often turns out to be a wish list assembled from different functional areas of the business, each describing its own pain points. Take a look:
- Marketing wants faster enrichment and multi-language support
- IT wants robust integration and control
- Merchandising wants flexibility
- Operations wants fewer manual fixes
- Compliance wants stronger approval gates
None of these qualities is wrong but the problem is that they are usually collected before anyone has mapped the current product data landscape properly. You then end up with a selection process driven by assumptions rather than empirical evidence.
Take this instance: A business may ask for complex workflow automation without understanding where the real bottleneck occurs. It might prioritise advanced data modelling before it’s resolved its problems with inconsistent attribute definitions. It could insist on supplier portal functionality when the actual issue is poorly-designed supplier templates and no validation rules at source.
All the above is why choosing a PIM feels well-nigh impossible. The business is attempting to invest in a system in order to solve problems it has yet to clearly and accurately describe.
Vague requirements è “Every platform looks like a good fit.”
‘User-friendly’ is not exactly a requirement which is going to help separate vendors. Neither are marketing-oriented phrases like ‘scalable’, ‘flexible data model’ or ‘good supplier integration’. These sound more like aspirations than testable criteria.
Solidly-grounded requirements look different. They emerge from the actual mechanics of how product data moves through a business. They describe specific use cases, constraints and pain points when it comes to failures. For example:
- onboarding supplier data from multiple spreadsheet formats
- managing variant structures across complex product families
- enriching category-specific attributes before channel publication
- enforcing approval gates for regulated or high-risk product data
- syndicating records to marketplaces with different validation rules
These scenarios require clarity because they reveal which capabilities are genuinely needed, which are optional, and which problems are not actually software problems at all. Without this level of detail, any and every vendor can fill your matrix with green ticks. Shortlisted vendors become indistinguishable from one another, and the decision-making grinds to a halt…again.
Internal friction makes the process worse
A PIM inevitably affects multiple teams, so selection is rarely just a decision about the most suitable system. It’s also a decision about data governance, about workflow design and about ownership of data.
This can lead to predictable friction among teams. Each one feels the pain of bad product data differently, so each defines ‘success’ and ‘suitable’ differently:
- The eCommerce team sees missed sales
- Customer service sees avoidable query backlogs
- Operations sees the bind of constant rework
- IT sees the complexity around system integration
And of course:
- C-Suite; leadership sees the cost
If no-one’s aligned all these views into a single operating model, the selection process turns into a series of interdepartmental negotiations rather than substantial diagnosis.
The symptoms are familiar:
- long demo cycles with no clear underlying direction
- conflicting opinions on “what matters most” (a hierarchy of needs)
- Over-engineered scorecards, creating the illusion of ‘control’
- Compromises that don’t truly satisfy any business function
As the selection reaches its conclusion, it’s often the case that the chosen platform reflects victors in an internal power struggle rather than whether it’s actually the right organisational fit.
Confused by PIM Vendors?
With 100s of PIM software vendors worldwide, choosing the right PIM solution can be a daunting & confusing task.
Use our guide to assess PIM solutions against the right capabilities to make an objective and informed choice.
Why tooling cannot fix an undefined process
Many organisations hope the right PIM will bring order to a messy data environment. It will certainly help, but only if the business has already defined the rules the platform is intended to enforce.
A PIM solution isn’t the panacea for unclear ownership. Neither can it resolve conflicting attribute definitions on its own. It cannot compensate for unmanaged supplier onboarding, inconsistent enrichment workflows or approval processes buried in email chains and spreadsheets. And crucially, if data governance is weak, a new PIM system simply becomes a faster way of moving poor-quality data around the business.
That’s why the sequencing of activities in a selection process is so important. First, you need to stabilise the operating model. Then, standardise requirements. Finally, you’re in a better position to evaluate the PIM’s tooling against these requirements.
How to make the choice possible again
The way out of paralysis of analysis isn’t watching yet more demos – It’s better preparation for making an informed choice.
Our product data management ‘as is’
Start with the current state. Map where product data originates, who touches it, where it breaks down and which workarounds people are using, because these normally mask the real issues. Conduct an audit on a sample of categories, supplier files and channel outputs. Identify the attributes and workflows creating the most rework, feed errors or delays in publishing.
Our product data management ‘as would be ideal’
Now you can define the future operating model. Be clear about ownership, approval gates, supplier inputs, enrichment steps and channel requirements. Once the model is in place, you can build requirements around real use cases rather than abstract features.
This is now the point where your evaluation of vendors becomes far more practical. You‘re no longer asking which platform is best in theory. You are probing to discover which platform can support your data model, workflows and governance with the least possible friction. That’s a much easier question to answer!
Clarity before platform choice
For such a substantial investment, choosing a PIM ought to feel weighty. But it shouldn’t feel impossible. If the selection process is firmly grounded in your operational reality, you’ll quickly narrow the field. The weaker fits become obvious. The trade-offs become visible. And, most importantly, your decision-making moves from educated guesswork to critical judgement.
Next steps
If your PIM selection is mired in indecision, the solution isn’t going to be yet another features comparison. The solution is having a clearer definition of the data problem(s) you are trying to solve.
If you need expert help turning product data pain into grounded PIM requirements, Contact us today at Start with Data, and we will support you in assessing your readiness before you commit to a platform.