From green bananas to ripe products: Why a PIM system is the maturing process for product data
Product Information Management
Who hasn’t seen them – green bananas on the supermarket shelf: not quite visually appealing yet, immature in taste, but with the potential to become a sweet treat in just a few days. This image can be wonderfully transferred to product data in the company. This also often starts out “green”: incomplete, inconsistent, not prepared in a way that is appropriate for the channel or target group. What is needed is a maturing process. And this is exactly where the Product Information Management System (PIM) comes into play.
The banana paradox of product data
Anyone who has spent any time in supermarkets knows that bananas are always harvested and delivered green. This is because they would otherwise overripen on the long transportation route from the producer to the shelf. Only in the familiar surroundings of the fruit basket at home or in the fruit section of a well-air-conditioned supermarket do they ripen into the golden yellow fruit that we associate with enjoyment.
This picture can be applied surprisingly well to an often underestimated aspect of digital transformation: product data. This too usually starts its journey raw, fragmented and unsuitable for end customer contact. It is created in different systems, in different departments, often without a uniform structure or goal. The result: product data that is available, but by no means ready for the market.
The dilemma: companies may have the product, but they sell it digitally with immature information. Missing images, incomplete descriptions, no technical details, confusing variants … These are all symptoms of “green bananas” in the data context.
In this scenario, a PIM (Product Information Management) system becomes a maturing cabinet for product data: It centralizes, structures, validates and orchestrates information in such a way that valuable product information is created from raw data – ready for e-commerce, print, POS or marketplaces.
Where do companies stand today?
A look behind the scenes: Excel instead of efficiency
Many companies still work with Excel spreadsheets, local folder structures or e-mail shares to maintain their product information. That sounds old-fashioned, and it is. The reality:
- The same data is maintained multiple times, leading to redundancies and inconsistencies
- Changes to a product run through numerous lists without central control
- Data is not version-safe and difficult to track
- Automation of playout is hardly possible
The result: high manual effort, high susceptibility to errors and poor data quality, which is ultimately reflected directly in the online presence.
Data silos and media disruptions
Companies without a PIM system usually have a fragmented system landscape: ERP, CRM, DAM, CMS – each system has a part of the truth. The product data has to be laboriously compiled, converted and enriched. This media disruption is not only inefficient, but also drastically slows down the time-to-market.
The product data is often not “omnichannel-ready”:
- The online store requires different texts than the catalog
- Marketplaces require special image formats
- Sales need structured data sheets
- Marketing wants emotional content with storytelling
Without central control, each channel becomes its own construction site and product data becomes a permanent construction site.
The degree of maturity is difficult to recognize
Many companies underestimate how immature their data actually is. Because as long as a product is somehow displayed in the online store, everything seems fine. But the devil is in the detail:
- Incomplete information leads to abandoned purchases
- Outdated data leads to returns and complaints
- Inconsistent descriptions weaken the brand identity
The realization usually only comes when the conversion rate stagnates, customer support is overloaded or catalog printing becomes a test of nerves.
What actually makes product data “immature”?
Not all product information is immediately ready for the digital stage. Companies often believe that their data is “in order” because it has been maintained somewhere. But a closer look reveals that although the data is available, it is not yet complete, not standardized, not attractive – in other words, not marketable. Unripe, in other words. Like a banana that is still green and tastes hard to digest. A PIM system not only recognizes these degrees of ripeness, but also helps to improve them in a targeted manner. But first, it is worth taking a closer look at what actually makes product data “unripe”.
1. Technical incompleteness
The most basic form of immaturity is simply: missing or incomplete information. This includes, for example:
- Incomplete article numbers or variant details
- Missing dimensions, weights or technical specifications
- No assignment to product categories or product groups
- Insufficient information on materials, origin or packaging
Especially in e-commerce, where the customer cannot physically experience the product, such details are essential for purchasing decisions. Incomplete information not only looks unprofessional, it also leads to uncertainty and abandonment in the purchasing process.
2. Weaknesses in content: From boring to meaningless
Another obstacle to maturity lies in the quality of language and content. Many product texts are written in a generic, technical or incomprehensible way. They are often just a list of features with no benefit, no story and no emotion. Immature content can be recognized by this:
- Standard formulation such as “high-quality processing” or “suitable for many applications”
- Lack of benefit arguments (“What’s in it for me?”)
- No target group approach or stylistic orientation
- Contradictions between text, image and application context
A PIM system enables targeted text creation and display according to channel, region or buyer persona. This creates real added value instead of empty phrases.
3. Lack of localization and translation
In a global sales world, localization is not a nice-to-have, but a must. However, a lot of product information is only available in one language, often untranslated, automatically generated or simply inappropriate. Immature data in this context means
- Missing or poor translations (e.g. via machine translation without correction)
- No adaptation to country-specific standards or units of measurement
- Culturally inappropriate terms or imagery
PIM systems with integrated translation management and multilingualism are worth their weight in gold here. They ensure consistent, market-oriented content worldwide.
4. Visual deficits: a picture is (not) worth a thousand words
Product data does not only consist of text! Images, videos, 3D views or application scenarios are also part of data maturity. But this is often exactly where it is lacking:
- There are no or only outdated product images
- Image formats are not correct for marketplaces or channels
- Media are not linked to articles
- Image rights and license information are missing
A PIM system, especially in combination with a DAM system (Digital Asset Management), ensures that every product information receives the appropriate visual support – in the correct format, up-to-date and legally compliant.
5. lack of context: data without meaning
Product data without context is like a banana without a peel: it looks strange, unprotected and incomplete. No matter how well an item is described, if it is not clear to the customer what they need the product for, how they can use it or what added value it offers, they will be left behind. Typical examples of lack of context:
- No application examples or scenarios
- Lack of sustainability or origin context
- No connection to brand values or USPs
- Lack of sustainability or origin context
Modern PIM systems enable the structured contextualization of products: Through intelligent links, text modules, automatic recommendations and semantic classifications.
6. Lack of consistency and governance
An often underestimated problem is inconsistency: if a product is presented differently in different channels, the credibility of the brand suffers. This is also referred to as a “data governance problem”. Characteristics:
- Different item descriptions in store and print
- Different prices, dimensions or colors
- Different delivery times or availability information
- Version conflicts with several caregivers
With clear approval processes, role models and checking rules, a PIM system creates governance structures that prevent such inconsistencies and thus create trust.
In summary: immature product data is expensive
Each of the weaknesses mentioned above costs money, be it through lost sales, increased returns, higher support costs or loss of image. A PIM system not only helps to recognize these maturity hurdles, but also to overcome them systematically and scalably. Just like OMN PIM!
From data fragments to product identity
In times of digital purchasing decisions, product data is far more than just technical information; it has become a carrier of brand identity. Customers inform themselves intensively, compare products and expect relevant, emotional and consistent content across all channels.
Unstructured, purely functional data (“green bananas”) is no longer enough. What is needed are product-related experiences that create trust and motivate customers to buy. This is where storytelling comes into play: it makes products tangible, emotionalizes them and differentiates them from the competition.
This is exactly what a modern PIM system makes possible:
- It links technical data with emotional content, images and application contexts.
- It allows channel-specific playout, e.g. texts of different lengths or image formats for the online store, marketplace, print or app.
- It ensures that every product appears consistently and in line with the brand – whether in German, English or Chinese.
This targeted preparation creates a holistic product identity from fragmented individual pieces of information. And not just a sales text, but a digital brand ambassador that works everywhere.
PIM systems as a maturing cabinet for product data
Like a banana, product information needs the right environment, care and control to reach its full maturity. A product information management system (PIM) creates precisely this environment. It not only provides structure, but also the organizational and technical framework to optimally develop product data from its creation to its display.
1 What is a PIM system?
A PIM system is a central platform for managing, enriching and distributing product information. It acts as a hub between the internal data sources (e.g. ERP, DAM, PLM) and the external output channels (e.g. online store, print, marketplaces, POS, apps). In contrast to decentrally maintained Excel lists or CMS-dependent data structures, a PIM:
- Centralization of all relevant product data in one place
- Structuring of the data in a flexible data model
- Versioning, roles and approval processes for maximum control
- Automated quality assurance through rules and workflows
- Multichannel management with targeted playout per channel
2. The maturing process in PIM – step by step
A PIM system turns raw product data (green bananas) into saleable information. This maturing process can be divided into four phases:
Phase 1: Centralize
Various data from ERP, Excel, CRM or DAM are brought together – redundancies, media breaks and inconsistencies become visible.
Phase 2: Structuring
Products are created according to a clear data model: with attributes, categorizations, relations. The basis for consistent and scalable content.
Phase 3: Enrich
Texts, images, translations, marketing claims, certificates, videos and SEO-relevant content are added – tailored to the target group and channel-specific.
Phase 4: Testing and go-live
Data quality rules ensure that only “mature products” are displayed. Distribution takes place automatically to stores, catalogs, marketplaces or apps.
3. What characterizes mature product data in PIM
A PIM system brings structure, context and control to product communication. Mature data is:
- complete and valid
- uniform and consistent across all channels
- emotionalized and channel-optimized
- can be found, updated and versioned at any time
- ready for international markets
This not only creates a professional external image, but also internal efficiency, for example during campaigns, launches or seasonal adjustments.
4. Advantages over classic data maintenance
Compared to maintenance in Excel or CMS, a PIM system offers significant added value:
Classic maintenance
- Decentralized, error-prone
- No versioning
- Media breaks
- High maintenance effort
- No quality control
PIM system
- Central, rule-based
- Audit-proof documentation
- Seamless connection to third-party systems
- Automated processes
- Validation rules & workflows
In short, a PIM system is not just a tool – it is a strategic maturity process that takes product information to the next level.
5. A look at the practice
Let’s take an example: A company sells 1,000 products in 3 languages on 4 channels. Without PIM, this means
- Manual maintenance of 12,000 individual items of information
- Error-prone translations
- Lack of consistency in prices, images and descriptions
With PIM:
- Central maintenance with language inheritance and channel assignment
- Quality rules prevent incomplete data from being displayed
- Automatic connection to online store, marketplaces and print systems
- Productivity increases, errors decrease
The result: faster time-to-market, better customer experience, less effort.
To summarize: A PIM system is much more than just a database! It is the place where high-quality, brand-enhancing product information is created from raw data, the maturing cabinet for your product communication, so to speak. It creates structure, order, quality and thus the basis for successful sales in all channels.
The maturity levels of product data – a model
Not every banana is immediately edible, just as not all product data is immediately usable. Companies are often faced with the challenge of being able to assess the maturity of their product information. A clearly defined model helps to make data quality transparent, clarify responsibilities and make targeted improvements. To illustrate this, we continue to use our symbol from the world of fruit – the ripeness of bananas as a metaphor for the quality of product information.
Maturity level 1: The green banana (raw data)
In the first maturity level, the product data is usually unstructured and distributed in different sources such as ERP systems, Excel lists or emails. The content of the information is often inconsistent, not standardized or only partially maintained. There is no consistent categorization, linked images or channel-related content. The data is therefore neither complete nor usable for external playout.
Risks:
- Not usable for customer channels
- High internal effort for each publication
- No reliable database
What helps now:
A PIM system that centralizes all product data in one place and thus creates the basis for structured data maintenance. Initial categorizations, basic attributes and a consistent data model form the foundation for further optimizations.
Maturity level 2: The yellowish banana (enriched, but not checked)
At this stage, a lot of product information is already available, it has been enriched and supplemented, for example with initial description texts, images or technical details. However, there is often a lack of validation: the content is not consistent, translations may be incomplete or machine-generated and terminology varies between products or categories. Without clear checking processes, inaccuracies and errors creep in, which can endanger a professional display.
Risks:
- Potential damage to customer image
- Publications lead to incorrect product presentations
- Marketplaces or stores show incomplete or contradictory content
What helps now:
To ensure the quality of the enriched product data, validation rules should be activated in the PIM system that automatically check for completeness, consistency and format specifications. In addition, it is important to establish clear workflows for quality assurance and approval processes to ensure that only checked and approved content is published.
Maturity level 3: The golden yellow banana (market-ready)
Product data at this level is complete, consistently maintained and quality-checked. All relevant information – from technical attributes and emotionalized texts to images, videos and application notes – is integrated. Translations have been entered correctly and the content has been prepared in a targeted manner for the respective channels. The product is ready for display – whether in the online store, on marketplaces or in print materials – and strengthens the brand presence with a professional appearance.
Opportunities:
- High conversion rates in e-commerce
- Reduced returns thanks to clear information
- Consistent brand presence across all channels
What is important now:
Once the product data is ready for the market, it is automatically played out in all relevant channels – from web stores and marketplaces to print and POS. At the same time, ongoing maintenance processes and feedback loops should be established to ensure that the data remains up-to-date and can be continuously improved.
Maturity level 4: The overripe banana (outdated or unusable)
Although the data appears formally complete, it is outdated, no longer brand-compliant or technically obsolete. Product changes have not been updated, images no longer comply with current standards and legally relevant information such as delivery times or prices are no longer correct. This situation harbors considerable risks – from customer complaints to legal consequences – and undermines trust in the brand and sales channels.
Risks:
- Customer complaints, claims, legal consequences
- Loss of trust in the brand and quality of information
- Frustration among internal teams
What helps now:
To avoid overripe or outdated product data, permanent update maintenance is required along the entire product life cycle. In addition, archiving and depublication processes should be defined in order to systematically remove content that is no longer valid. Effective expiry control using versioning and time-based rules ensures that only current and approved information remains visible in the channels.
Organizational requirements for mature data
A powerful PIM system is only as good as the organization that uses it. Even the best technology cannot be effective if responsibilities are unclear, processes are not defined and accountability is not practiced.
Data quality is not a purely technical issue, but an interdisciplinary task that must be structured, supported and continuously developed. Clear roles, reliable processes and a company-wide data culture are required for product data to truly mature.
1. Clarify roles and responsibilities
A common stumbling block in practice: nobody feels responsible. Or – almost worse – everyone feels responsible, but no one is responsible. This leads to duplication of work, inconsistent data statuses and frustration.
Important roles in the PIM context are, for example
- Data owner: Responsible for the technical accuracy of certain product groups
- Content Manager: Responsible for descriptive content, images, texts, videos
- PIM Admin: Technical support of the system, assignment of rights, rule management
- Marketing/sales: Briefing on campaign content, feedback on data quality
- Translators/agencies: maintenance of language variants directly in the PIM or via connected tools
Transparency about these roles is crucial, as are clear approval processes to ensure that only checked content is published.
2. Promote collaboration between departments
Product data is not created in a silo. It is the result of collaboration between product management, purchasing, marketing, sales and IT. It is therefore important that these departments work together rather than side by side.
Helpful measures:
- Joint workshops on data structure and attribute logic
- Regular reviews on data quality
- A central governance team for product information
- Transparent prioritization according to business goals (e.g. focus on top sellers, seasonal products, etc.)
A successful PIM project is therefore also a change project: it changes processes, responsibilities and requires communication at eye level.
3. Define and live processes
The introduction of a PIM system is not a sure-fire success. Sustainable added value can only be created if processes are clearly defined and practiced on a day-to-day basis.
Typical process questions are:
- Who creates new products in the PIM?
- What content needs to be maintained by when to ensure a successful launch?
- When is a product considered “ready” for launch?
- How are corrections, feedback or translations managed?
Such processes should be standardized and mapped in the system – ideally with automated workflows, reminders and escalations.
4. Establish a data culture
Ultimately, the culture determines how sustainably data quality is practiced in the company. A strong data culture means
- Product data is not seen as a chore, but as a strategic success factor
- Quality is not checked “on the side”, but is an integral part of the work
- Those who are responsible are trained, empowered and taken seriously
- Successes in data quality are made visible and recognized
A well-maintained PIM system is always an expression of entrepreneurial maturity and a reflection of internal cooperation.
No maturity without organization
Technology alone does not make product data mature. Only when clear roles, reliable processes and a practiced culture of responsibility come together can a PIM system develop its full potential. The product data then matures not only technically, but also organizationally – and with it the entire company.
Norbert Weckerle, CEO of apollon
Technological integration
A PIM system is only fully effective when it is seamlessly integrated into the existing system landscape. The connection to ERP, DAM, store and CMS systems as well as marketplaces is crucial in order to avoid manual duplicate maintenance and to automate processes.
Product data can be automatically imported via interfaces and exported to specific channels. Especially in combination with a DAM system, a complete picture of the product is created – with texts, images, videos and documents, centrally controlled from the PIM. Today, PIM and DAM form the backbone of professional, media-supported product communication. Many providers integrate both systems or offer them as a seamlessly integrated solution, as structured data and digital assets are inextricably linked when it comes to consistent brand experiences and efficient playout across all channels. This is precisely the approach taken by OMN, which combines both PIM and DAM functionalities in one platform.
AI-based functions such as automatic text creation, translations and quality assurance are also becoming increasingly popular and support data maturity. The important thing here is that every tool must simplify the maturing process – not complicate it. Here too, OMN has numerous AI services (e.g. Deepl, Google Translate or Retresco for translations).
Conclusion: Maturity is no coincidence – it is a decision
The banana has accompanied us – from the green, hard fruit to the ripe delicacy. It’s the same with product data: it doesn’t ripen on its own, but through structure, care and the right environment. A PIM system is not just a tool, but the foundation for data-driven brand communication, efficient processes and sustainable growth.
Mature data is created where companies take responsibility: For quality, consistency, relevance and user experience.
After all, the maturity of your product information is not just a technical state – it is an expression of your entrepreneurial attitude.
Those who consciously shape this maturity process create trust, differentiation and conversion. And this is exactly what makes the difference in digital competition.
How mature is your product data?
If you want to take your product communication to the next level, we will be happy to support you – with experience, technology and an eye for the essentials. Get in touch now and experience OMN live >>
OMN: Integrated maturity model for quality analysis
OMN PIM is our PIM system. One of the amazing features is that it has a maturity model. This is a function that, among other things, checks your product data fields for missing values and closes these gaps. This quality analysis helps you to ensure that your product data is both complete and correct before it is sent to your channels.
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