When you’ve invested a significant amount in a PIM solution, getting down to business with it may appear a bigger challenge than it should. Your current state of play is challenging to say the least: The catalogue is already live, your product data is spread across spreadsheets, ERP fields, supplier files, and eCommerce platforms, and all your people are constantly busy. When product data is fragmented, inconsistent, and hard to trust as correct, the costs rear their heads everywhere: Slower launches, more manual rework, weaker commercial performance across channels, and entirely avoidable friction for your customer services to deal with.
The temptation is just to choose a PIM and get it up and running asap. We’ve drafted this article to give you some tips on why you need to take a deep breath before you get anywhere near choosing your PIM. We’ll outline five easily applicable best practices which will help PIM ‘novices’ start well and avoid the common mistakes which often drag first-time PIM projects down.
1. Define the problem(s) before you choose the platform
The first mistake businesses make is to go straight to vendor demos. PIM platforms are chock-full of features, but feature lists don’t tell you precisely what problems your business needs to solve.
Get your ducks in a row. Start by clarifying:
- Where your product data actually lives today (hint – probably all over the place)
- Which teams create, change, and publish that data on a regular basis
- Where errors, delays, and duplication happen far too often
- What outcomes are most impactful for your business
For most businesses, the underlying issue isn’t “we need a PIM,” but something more concrete: It may be that supplier onboarding is slow, or your marketplace listings frequently fail, or who is accountable for what data is unclear, or that your new products take too long to reach market, making you fundamentally uncompetitive.
That’s why you must get that diagnosis right first because it’s going to shape your requirements, your business case, and your shortlisted PIM solutions. A PIM chosen to solve a clear operational problem is far more likely to deliver value than one chosen because its array of features came across as really impressive in a demo.
2. Make sure your data is clean before you migrate it
A PIM isn’t capable of repairing broken product data by itself. It’ll simply give structure to what you load into it. So, if you migrate duplicate SKUs, vague attribute names, missing fields, and inconsistent values, you’re basically creating a more sophisticated home for the underlying problems which already exist.
Before implementation, be sure to focus on the following cleansing basics:
- Standardise attribute names and meanings
- Remove duplicate data and obsolete product records
- Define a single system of naming conventions and units of measure
- Identify missing mandatory data
- Decide what’s worth migrating and what isn’t
It’s not a particularly glamorous part of a PIM project, but it’s certainly one of the most important. When you import bad-quality data early in a PIM implementation project. You’re setting yourself up for expensive and time-consuming rework later. Clean foundations make everything that follows much easier: Modelling, workflows, syndication, and enrichment.
3. Start small and expand in a planned way
In our experience of advising on and fixing PIM user problems, ‘beginners’ have often tried to migrate all their product data at once. Every category, every supplier, every channel, every market. This approach almost always ends up creating complexity faster than the organisation can control it.
A phased approach works better. You should start with a pilot scope such as:
- one product category
- one priority supplier
- one marketplace or channel
- one product line with known data issues
This fulfils three useful purposes. It gives you an early win (never to be underestimated!). It enables you to test your data model against real products. Finally, it limits the potential cost of mistakes. A small and manageable first phase helps you refine workflows, validate integrations with other systems, and train your teams without risking a full-scale failure.
Therefore, the goal of phase one isn’t completeness. It’s proof that the model actually works in your real-world context.
4. PIM should be treated as an operating model, not just another software install
Businesses experiencing their first PIM project often fall into the trap of framing it as an IT deployment. This is a reliable way of underdelivering on the investment.
A PIM enables a step-change in how the business works. It has an impact on supplier onboarding, attribute ownership, enrichment workflows, approval gates, and channel publishing. If these wide-ranging decisions are left in a state of vagueness, the system will go live, but old behaviours and protocols (or lack of) will stay in place.
You need to have clear outcomes for the following key areas:
- Clear ownership of data by the business, not just IT
- Role-specific workflows and responsibilities
- practical training for the teams using the system
- Cross-functional alignment across ecommerce, product, marketing, operations, and IT
A newly-implemented PIM succeeds when it becomes part of the operating model. Otherwise, it’s destined to fail if you treat it as just another piece of software on top of old habits.
5. Build in data governance from day one
So many businesses postpone the ideation, construction and implementation of a governance framework because getting the solution live feels more urgent. It may well be so, but lack of governance is still where a lot of problems originate.
Without governance, the new PIM fills up with the same inconsistencies that existed before: uncontrolled values, unclear permissions, weak approval processes, and records that no one is prepared to take ownership of.
In fact, the essentials for governance aren’t rocket science:
- defined user roles and permissions
- mandatory fields for key data
- controlled vocabularies where consistency matters
- validation rules at the point of ingestion
- approvals workflows before publication
- audit trails for any changes and exceptions
Neither do you need to overengineer governance. A pragmatic framework is enough to start with. The main point is to establish control early and then refine it as the business grows and its product data management evolves.
The watchword is clarity (not complexity)
The common thread across all five best practices is straightforward: The PIM project isn’t about installing software as a solve-all. It’s about a mindset change in how you manage, structure, own, and maintain some of your most valuable customer-facing assets – product information.
To recap, look before you leap!
- Define (clearly and specifically) what business problem(s) you want the PIM to solve
- Cleanse your product data before migrating it
- Pilot how your product data works in the new system before scaling to the entire catalogue
- Treat PIM as a business operating model, not just an IT / Tech area
- Build governance in before you go live
Do the above and you’ll reduce rework, avoid scope drift, and give the system a fair chance of delivering the ROI you’ve promised all the stakeholders.
Next step
If you’re starting your first PIM project, don’t take your first step alone with vendor demos. Start with your data, your workflows, and your real pain points. Get in touch with us today at Start with Data for a discovery call. We can support you to define a clearer PIM starting point, as well as guiding you on how the right foundations make PIM implementation smoother, faster, less risky, and more likely to deliver what your business needs.