In today’s complex business world, data is the life elixir of every and any company. Data, however, does not equal data. A particular role is occupied by so-called master data. Such data forms the foundation for smooth processes and informed decisions. What’s behind the concept of master data management (MDM) and why is the well-defined master data administration so decisive for your success?
Master data encompasses the most important and foundational information of your business objects. This includes, for example, customer data, material master data, supplier information, and, of course, product data. These kinds of data usually have a long lifetime and are utilized by various systems and corporate departments. In short: Master data forms the backbone of numerous business processes – from offer creation, through logistics, to customer support. Inefficient management of this data is quick to lead to data inconsistencies and redundancies. The consequences range from wrong reports to slow-moving workflows. This costs a lot of time and money. There is no way around it except for efficient master data management.
Well-implemented master data management creates a central, consistent, and reliable data foundation. This enables you to make strategic decisions, optimize your processes, and improve collaboration between various departments. That is to say: Master data management guarantees order in foundational data processes.
An effective master data management ist much more than only a technical exercise – it directly influences the success of your company. Positive effects can be observed in almost all areas:
In short: Clean master data pays dividends – today and in the future.
A functioning master data strategy is not created overnight – it requires structure, clear objectives, and a system that matches your company. The key lies in small and pragmatic steps. “Quick wins” is the magic formula: Instead of realizing the whole in its entirety in one go, it is recommended to begin with concrete use cases – with product data in e-commerce, for example, or with supplier data in sales.
The important thing not to forget is: This is not just a pure IT project. Collaboration between IT, management, and experts in relevant fields is required. Define clear roles and responsibilities, establish a slim governance structure, and, finally, assure that the data quality is maintained at regular intervals. And: Choose a platform that does not only convince in terms of technology but can also be flexibly adjusted to your requirements – ideally, cloud-native, API-first, and scalable, like ATAMYA. This way, you stay in control, minimize risks, and are quick to see first benefits – and this is precisely what defines a good MDM strategy.
Once the strategic foundation is set up, it comes down to the actual implementation. Especially in the field of product management, the well-thought-out master data management plays a key role. Because it is here that daily data maintenance, marketing requirements, and sales successes come to meet. Clean, consistent product data makes the difference: For successful omni-channel sales, effective marketing campaigns, and satisfied customers.
Best practices for master data management of product data include:
With modern master data management, you create the foundation for a strong, future-proof product information management – independent of channel, language, or target group.
Author:
Robin Demeter
Senior Sales Manager
ATAMYA
Whitepaper Tip: This Is How You Use the Potential of Your Product Data
Do you want to dive deeper into the subject matter of digital product management and learn how to use your product information optimally? Then take a peek at our free whitepaper “Digital Product Management” packed with lots of tips, practical impulses, and strategies for your everyday work life.
Sooner or later, PIM users encounter a frequently underestimated topic: data onboarding. This term refers to importing external data into one’s own systems – for example, into an ATAMYA instance. Depending on the context, it’s also called “supplier data onboarding”.
Merchants and wholesalers typically receive product data from various sources such as manufacturers, suppliers, or data pools. Each data supplier manages their data differently — some use Excel spreadsheets, others use a PIM. In addition, there are many data exchange formats like CSV, XLSX, XML, JSON, and data standards such as BMEcat or ETIM xChange.
What works for the individual supplier often poses challenges for the data recipient. So, how can different datasets be consistently and accurately imported into ATAMYA serving as the central platform for managing structured product information? The answer lies in a clearly structured, efficient data onboarding process supported by middleware acting as a “translator” between data supplier and recipient.
This article explores why data onboarding is more just than a technical necessity, and how to optimize it within your product data management.
Admittedly, data onboarding isn’t exactly a hot topic for small talk. But why is this part of product data management often treated as secondary? Data onboarding is often dismissed as a minor preliminary step before PIM maintenance. However, considering the entire product data journey — from creation to presentation and marketing — data onboarding actually plays a crucial role throughout the content supply chain, from manufacturer to end user.
However, when you consider the entire journey that product data takes from its initial creation to the final product presentation and marketing, this assessment is put into perspective. It quickly becomes clear that data onboarding actually plays a key role along the entire “content supply chain”. This refers to the complete flow of data from the manufacturer to the retailer and finally to the customer or end user.
One reason is the quality assurance function of data onboarding: it ensures that low-quality external data can’t even be imported into internal systems and cause further issues. The reality is: product data management processes in a PIM are only as effective as the quality of the data they rely on.
The takeaway: Those who import high-quality, standardized, and clean data into their PIM system lay the foundation for automated workflows, omnichannel syndication, and sustainable data quality – within the PIM and beyond. Product visibility in search engines, online shops, and marketplaces depends heavily on the freshness, completeness, clarity, and overall presentation quality of products. Essentially, high quality product data helps reduce return rates and increase sales potential.
The need for high-quality product data in the context of data onboarding is closely tied to the very nature of PIM systems. Systems like ATAYMA serve as what is known as a “Single Point of Truth” (SPOT) – a central and consistent source of product information. A cross-departmental use of the PIM also helps prevent the formation of data silos – isolated, disconnected datasets that may contain inconsistent information about the same products. In short: where data silos exist, confusion follows. And PIM systems are designed to prevent exactly that.
Everyone accesses the same centralized data pool, ensuring a uniform and reliable data foundation across the company. Product manufacturers can create data for new items directly in their own manufacturer PIM system. Wholesalers then receive this data and import it into their own PIM environment. Once stored in the system, the data can be continuously updated, enriched, and published. Sales and marketing teams, for example, use PIM data to create compelling product descriptions and promotional campaigns. However, this requires active data management: all product data must be kept up to date, complete, and informative at all times.
The key question is: How can different external product data be consistently and efficiently imported into ATAMYA? To achieve this, companies often rely on intermediary software solutions – so-called “middleware”.
These specialized supplier management tools (e.g. in the form of a supplier portal) enable distributors to define clear specifications for how they accept product data deliveries. Each supplier can align their data with the required data structure (e.g. the field structure in ATAMYA). This can be achieved using a data mapping process that matches the supplier’s source fields to the defined target format.
Versatile data onboarding software also allows distributors to configure how supplier roles are managed – whether suppliers are permitted to manage their data themselves, whether the distributor takes over this task on behalf of the supplier, or whether a hybrid role is preferred.
Before supplier data is transferred into the ATAMYA system via interface integration, middleware users can set up and manage various data management processes, including the
A product data classification in the PIM — whether custom or standards like ETIM or ECLASS — can also be generated and automatically exported this way.
Those who regularly work with (external) product data are likely familiar with common obstacles: Excel files with freely named columns, incomplete mandatory fields, format inconsistencies, or media links leading nowhere. In some cases, data is not updated frequently enough – or the updates are not passed on to data recipients in a timely manner.
These practical examples highlight a typical situation: in addition to clearly defined rules for data enrichment, many companies simply lack the technical infrastructure needed for smooth product data management. Especially when handling large volumes of product data, interface integrations – for example via REST API – with middleware solutions, as well as external and internal systems, are indispensable.
In many data onboarding workflows, another issue becomes apparent: the lack of a clearly defined set of requirements. To address this, PIM users (being the data recipients) can reflect on questions such as:
Experience shows that data management processes tend to function reliably when they are both technically well-designed and clearly communicated.
Once these data structures are clearly defined, the foundation is in place for an automated data onboarding process. However, such a process relies not only on the right middleware but also on clear communication. Only if both sides understand what matters in terms of data delivery, data transformation, and data distribution can potential issues be avoided from the outset.
However, an automated data onboarding process depends not only on the right middleware, but also on clear communication. Only when both sides – the data supplier and the data recipient – know what is important when it comes to data delivery, data transformation, and data export can potential problems be avoided in advance.
An efficient data onboarding workflow typically begins with the appointment of clearly defined contact persons who are responsible for managing and supervising the process. The technical implementation is then based on the definition of user roles and access rights, the connection of data sources (such as a PIM, ERP, or individual files), the integration into the ATAMYA PIM as the target system, the creation of data mapping structures, and the setup of customizable or standardized data validation rules.
Experience from numerous data onboarding projects shows: yes, setting up such a workflow involves an initial effort. But this effort pays off quickly – through higher data quality, fewer follow-up questions, and a shorter time-to-market.
This article makes one thing clear: professional data onboarding is not magic – it’s the result of a well-aligned interplay between technology, processes, and people. In practice, the following five aspects have proven particularly valuable:
When all these elements come together, data onboarding becomes what it truly is: a foundational building block for commercial success in today’s digital business landscape.
Author:
Kevin Mattig
Sales and Business Development at nexoma
Error-free Product Data is No Coincidence
Our checklist demonstrates how you can systematically improve your product data quality in a sustainable manner.
The implementation of a Product Information Management system (PIM) is one of the decisive measures for companies that want to manage their product data efficiently and be successful in e-commerce. A PIM system centralizes all relevant product information, improves the quality and consistency of data, and accelerates the time-to-market. In this article, you learn which steps are required to successfully realize your PIM project and which pitfalls you must avoid.
The PIM selection is the first step in a successful PIM project. There is a large number of providers on the market offering diverse solutions. In principle, a PIM should not only fulfill your company’s current requirements but also be well-prepared to face future developments. It should grow together with you and be flexible when it comes to adapting to market conditions. In the light of this, the following factors are important when choosing your PIM system:
The choice of the right system requires thorough analysis of your requirements and existing functions of the system. A premature decision may lead to later discovering that the system is missing key functionality you need or that it is not scalable with your needs of tomorrow.
Besides deciding on a suitable PIM system, choosing the right implementation partner is also decisive for the success of your PIM project. The partner should not only be a technology expert but should, ideally, also have experience in the specific industry sector of your company and its requirements. Accordingly, look out for the following criteria when selecting the implementation partner:
Make sure that the partner defines clear milestones and communicates project objectives in a transparent manner. A realistic time schedule and a detailed plan for resource allocation are also crucial. The PIM agency NETFORMIC, for example, boasts years’ worth of expertise in PIM implementations and has extensive experience in PIM projects for a variety of industries.
The PIM implementation encompasses a number of central steps that are connected with one another. Each step should be planned with utmost care and executed accordingly in order to avoid problems later on. The following provides you with an overview of the essential steps of a PIM implementation.
The first step of implementation is creating a solid data model. This is about how to structure and categorize product information. This is one of the most important phases since a good data model is the basis for effective management and use of data. Import considerations include:
A well-structured data model guarantees that product information is consistent and easy to manage.
After the data model is created, the data imports are next. To this end, existing product data is transferred from various sources such as Excel, ERP systems, or databases into the PIM system. This step requires:
A PIM system only functions effectively when it is connected to other systems in your IT environment. Of particular importance are:
The interfaces between systems must be efficient and stable in order to secure a continuous and error-free flow of data.
An important step in the PIM implementation is data exports. This is all about distributing the product information into the various sales channels, including online shops, marketplaces, catalogs, or apps. This should happen automatically and at regular intervals so that up-to-date and consistent data is always available everywhere.
Prior to the definite launch, the PIM system should be thoroughly tested. This entails:
After the system is tested and all adjustments are implemented, it can go live. The transition from the old processes to the new PIM system should be smooth without any gaps. Factor in sufficient time and resources to be able respond to any unforeseen variables quickly.
After the PIM implementation, the project is not yet completed. There are some important tasks that must be carried out continuously:
Carrying out a PIM project is a complex affair with some potential pitfalls you need to watch out for:
Conclusion
A PIM project is a complex long-term process requiring careful planning and execution. When you choose the right systems, find the suitable implementation partner, and diligently carry out all phases of the project, you will come to profit from the benefits of a PIM system: improved data quality, faster time-to-market, and even higher efficiency for your company.
Author:
Timo Weltner
CEO & Co Founder at NETFORMIC
Why Do We Need a PIM?
The requirements for product data are ever-increasing – now is the right time to convince your stakeholders of a PIM system. This presentation delivers suitable arguments for a well-founded decision.
Customer expectations increase, sales channels are becoming more diverse, and competition intensifies – companies stand under ever-growing pressure. Those who want to successfully market their products and services today, must do one thing before anything else: you must have a firm grip on your product data. This is because only when such product data is correct, consistent, appealing, and available on several sales channels will convincing customer experience come to life. And this is precisely where modern software solutions such as PIM systems (Product Information Management) and CMS (Content Management Systems) come into play. Both come with their own respective strengths, but only in their interplay do they unfold their full potential – as the foundation for a continuous and harmonious market experience across all touchpoints.
A Product Information Management system (PIM) is the central platform for all product-related data in companies as well as the alpha and omega when it comes to managing product data efficiently. While a CMS first and foremost controls and publishes content, a PIM software primarily covers the efficient collection, enrichment, and channel-overarching distribution of product information.
In short: A PIM is profitable for every company that wishes to efficiently manage its product data and maintain both high data quality and error-free product communication. In particular, companies with complex product portfolios, many variants, an international outlook, and many sales channels profit from a PIM. Be it manufacturer, retailer, platform operator, travel and tours operator, or service provider – a high-performance PIM like ATAMYA creates structure and efficiency while also decisively securing your competitive edge.
A Content Management System (CSM) is the central platform for efficient management, organization, and publishing of digital content – from websites and blog articles to letters and landing pages.
CMS systems such as WordPress, Typo3, or Joomla are some of the conventional systems that are commonly used. As soon as it comes to consistent product data, however, even these systems come to their limits.
Complex product data, variant management, translations, or the connection of various sales channels are classic weak points of a CMS. It is here where the specialized data structure and flexibility of a PIM is missing.
PIM and CMS: The Decisive Differences for Your Product Data Management
| Property | PIM | CMS |
| Focus | Product data management | Content / Website Management |
| Typical Content | Product descriptions, specifications, images, variants | Texts, images, videos, blogposts, pages |
| Target Group | Product managers, e-commerce, sales | Marketing, technical writing, web teams |
| Multichannel Capacity | Very high (shop, marketplace, print, etc.) | High (web, newsletter, social media) |
| Data Complexity | High (variants, languages, attributes) | Low to medium |
| Integration | Interfaces to shops, ERP, CMS, marketplaces | Interfaces to web, socials, DAM |
Let’s summarize: A CMS is ideal for the management and publishing of marketing content and websites. As soon as complex, multi-dimensional product data enters the equation, to the contrary, a PIM is the superior choice – in particular when you are active in multiple channels and markets.
The true strength unfolds in the collaboration of PIM and CMS: the PIM delivers enriched and consistent product data that is always up to date, while the CMS embeds this data in appealing, context-sensitive content and web pages.
The choice between PIM and CMS depends on your individual requirements. For the efficient management and distribution of even complex product data, there is no alternative to PIM. CMS, however, remains indispensable for creative and flexible content creation. Together, both systems create the basis for consistent, convincing customer experience – securing your sustainable success in the digital competition.
If you are currently contemplating how to efficiently manage your product data, the next logical step is to research state-of-the-art, future-proof PIM systems. ATAMYA Product Cloud offers you precisely this: a cloud-native, API-first, and composable platform that grows together with you. Discover how simple and flexible PIM can be today.
Author:
Florian Kuhn
Senior Partner Sales Manager
ATAMYA
Why Do We Need a PIM?
The requirements for product data are ever-increasing – now is the right time to convince your stakeholders of a PIM system. This presentation delivers suitable arguments for a well-founded decision.
Digitization poses a challenge to companies regardless of size – but it also opens up great opportunities. For medium-sized enterprises, in particular, spare resources are hard to come by, be it time, budget, or personnel. At the same time, small and medium-sized enterprises (SMEs) face ever-growing pressure: they must react to changes in the markets in a flexible manner, efficiently launch new products, develop innovative services, and communicate all this and more consistently across an increasing number of channels. When it comes to both marketing and product management, this often times means: managing product data under the highest pressure, Excel chaos, and matching data sources in a time-consuming manner.
A great many medium-sized enterprises grow successfully – until the processes revolving around product information starts retarding their growth.
And it is precisely here where state-of-the-art PIM systems (Product Information Management) come into play – ready to unfold your full potential as real efficiency drivers.
A PIM such as ATAMYA offers a central platform for managing, administrating, and distributing all product information. For marketing and product management, this translates into a visible relief in everyday work life:
Product data is the centerpiece of modern corporate communication. No matter if it’s the web shop, marketplaces, catalogs, or sales: customers expect complete, up-to-date and consistent information everywhere and at any given time.
A PIM creates the foundation for this. It guarantees that all product information is managed centrally and easily maintained, translated, as well as exported in a targeted manner.
A current real-life example demonstrates how ATAMYA can sustainably improve the success of a medium-sized enterprise: A manufacturer for household devices integrated ATAMYA into their processes and was able to reduce the time-to-market of the new product line by 30 %. At the same time, they managed to optimize the product data quality which, in turn, translated in a boost in sales.
Many medium-sized enterprises are hesitant when it comes to the implementation of a PIM system – because of worries concerning complex workflows, high costs, or long project runtimes. And here is where ATAMYA enters the equation: the PIM software is developed specifically to meet the needs of SMEs. It boasts intuitive use, a fast implementation, and can be scaled in a modular manner – excluding months-long IT projects or over-scaled systems and functions.
The great benefit we offer: software that grows with your company. This means that you start with the functions you need today and, then, expand the system step by step once your requirements grow. Be it 1,000 or 100,000 products – ATAMYA maintains high performance and flexibility since it is a cloud-native SaaS solution. No extensive IT infrastructure is required on your end while maintenance updates are rolled out automatically without interruption of operation. Learn more about our cloud solution in our overview under ATAMYA Technology.
Besides the continuous development of the solution, additional functions can be integrated or connected on the basis of the MACH principle (microservices, API-first, cloud-native, headless), for example your shop system or a MAM/DAM system tailor-made to suit your requirements.
Thanks to the multi-domain data model as a unique selling point, not only product data but also the complete “data supply chain” including supplier, customer, and manufacturer data can be collected and managed.
Additionally, intelligent workflows can replace manual processes. Who has the permission to approve product information? How can data be automatically exported to the web shop? Even AI applications can be integrated in order to accelerate processes even further and free up resources. For example, marketing texts or datasheets can be automatically generated out of collected facts about a product which then only need to be double-checked once more before release.
And that’s still far from all, since ATAMYA can also be utilized to check product data based on its data quality (DQM) for completeness or correctly formatted input values and content, etc.
In contrast to complex and expensive enterprise solutions, this PIM software was developed specifically for the needs of mid-sized firm sector. What makes ATAMYA so special?
ATAMYA, therefore, is not only a tool for your short-to-mid-term requirements, but also a future-proof solution that will support your company on a long-term basis.
Conclusion: The Right Time is Now
A PIM system is no longer a luxury, but a necessity – this includes, in particular, medium-sized enterprises. With a solution like ATAMYA, getting started is easy, fast, and efficient. You profit from cleanly structured product data, optimized processes, and more time for the things that truly matter: your core business.
Author:
Claus Vöhringer
Senior Sales Manager
ATAMYA
Why Do We Need a PIM?
The requirements for product data are ever-increasing – now is the right time to convince your stakeholders of a PIM system. This presentation delivers suitable arguments for a well-founded decision.
Be it in retail or in the industries, those who want to provide their customers with a contradiction-free and convincing customer experience will find that a Product Information Management system – in short: PIM – is indispensable.
A PIM simplifies and automates all processes revolving around your product data: All product data and information is pooled centrally, refined, and, lastly, distributed to the various target channels such as online shops, online marketplaces, social media, websites, or print outlets.
This offers countless benefits to companies:
In our digital world, a PIM system is an absolute must-have for companies which want to stay streets ahead of the competition. In the field of e-commerce, the demand for PIM solutions is especially high – and where there is demand, there is also a rich supply of tools and providers. It’s a true jungle of requirements, functions, and pricing models out there. Indeed, it’s rather easy to lose the overview. But no worries! In today’s blog entry, we’ve put five selected providers for PIM systems under the magnifying glass.
The PIM made by Akeneo is an open-source PIM solution which is especially suited for retailers and manufacturers. With its “Akeneo Product Information Cloud,” the French company offers a compatible Software-as-a-Service solution – in short: SaaS – with an intuitive user interface. The simple interface appeals to users, in particular, who aren’t much of a technophile. Over the years, Akeneo has advanced to the position of an internationally well-positioned company offering its software in three different editions: the free “Community Edition” with considerable limitations when it comes to the scope of functions, the “Growth Edition” best suited for small businesses, as well as an extensive “Enterprise Edition” for which the fees involved are determined on an individual basis.
One highlight of Akeneo is its focus entirely on Product Information Management instead of splitting it into numerous half-finished e-commerce solutions. The open-source PIM, however, also comes with a decisive drawback. The range of functions of the free “Community Edition” is reasonable – yet, all the exciting PIM features are only included in the costly “Enterprise Edition.” Additionally, users of the open-source PIM variant are, to a large extent, left to their own devices – without expert PIM consultation or support service.
With the so-called “Product Experience Cloud,” the provider Contentserv offers its users a scalable, flexible, and user-friendly PIM solution, including Master Data Management and Digital Asset Management functions. Contentserv is a global player with a wide partner network and counts more than 300 companies across 89 countries as its customers. The “Product Experience Cloud” features besides its central data management a variety of adjustment options, a data quality function which guarantees high-quality data throughout the entire product life cycle, as well as collaboration services for data onboarding and services for exporting data. In short: Contentserv has a great set of useful functions and options to offer for strategically improving your customer’s product experience on an emotional level.
It’s precisely this great selection of features, however, which invites critique by some users: since it affects the user’s ability to always keep an overview of the many modules, resulting in a higher degree of complexity. This makes it a bit more difficult for Contentserv users to immediately find the right functions for the given use case. Furthermore, the software does not always fully match requirements of state-of-the-art technologies.
The provider Pimcore offers open-source software ideal for e-commerce. It’s up to the users whether to work with the Pimcore PIM system on its own or in combination with Master Data Management (MDM), Digital Asset Management (DAM), Web Content Management (WCM), and/or Customer Experience Management (CXM). As a multi-channel-publishing suite, Pimcore enables you to manage and export product data and information in the form of documents, videos, text content, or images – in a simple manner with drag-and-drop.
The positive side is, once more, that the open-source version is completely free. And once again, however, the same argument as before also applies to this provider: for those who want to use the full scope of functions of the enterprise version including support based on the respective company’s individual requirements, they have to dig deeper into their pockets. This is why the open-source version of Pimcore is most suitable for companies which can allocate sufficient resources to a tech-savvy team with a lot of know-how for facilitating both implementation and operation of the software.
The PIM provider Plytix introduces its PIM system as a simple solution from content people to content people, so that no IT expertise is required. Given its fair pricing model, Plytix is a good choice for SME companies in particular. The Plytix PIM is available in three different versions: the free version is suitable for small businesses which want to kiss chaotic Excel datasheets goodbye, whereas the standard version provides companies with the basis for their own Product Information Management. The pro version, in turn, is geared towards multi-channel publishing, equipping growing companies with all necessary PIM functions.
With the system made by Plytix, you receive a simple yet still comprehensive range of functions for creating and managing product catalogs, multi-channel sales, and central data management. Since Plytix is still a young player on the PIM market, however, some functions still need some finishing touches. For this reason, it may not be the optimal choice for large enterprises with complex product assortments.
“If there is a problem, then there is a solution!” – this is our credo when it comes to our customers’ requirements for our PIM system. Thanks to our flexible, AI-assisted data models, our system can map any kind of product portfolio. Accordingly, ATAMYA Product Cloud is ideal for both retailers as well as manufacturers from all sorts of sectors – be it e-commerce, travel and tourism, or the industries. In short: Our system adjusts to your requirements, not the other way around. All in all, you profit from a highly performative, cloud-native PIM solution with maximum flexibility.
ATAMYA Product Cloud unifies PIM, DAM, and AI-based processes in one solution, offering you among other features:
ATAMYA Product Cloud is distributed and provided based on the SaaS model – including all benefits that come with a modern, highly scalable Cloud platform. Our prices are individualized to match your requirements. Learn more in our overview of editions.
You know how the saying goes: with great choice comes great responsibility – the agony of choice. The selection process for the right PIM system is far from easy – too many options to choose from, too many promising alternatives. In this article, we have presented to you a small selection of PIM systems from various providers made to master different challenges. The market, however, is much bigger. If you want to gain a comprehensive insight, how about visiting well-established, English-language PIM comparison portals such as OMR Reviews, Capterra, or GetApp.
Author:
Yana Zabolotna
Copywriter
ATAMYA
In a world where up-to-date, complete, and consistent product information decides about success or failure when it comes to convincing customers and staying afloat in the face of ever-growing competition, a Product Information Management (PIM) system occupies the main role: It centralizes and structures product data so that it can be distributed to all sorts of channels. Not every PIM system, however, delivers the same performance – in particular when it comes to structuring the data. A real gamechanger in the world of product data is the so-called multi-domain data model. Now, what does this concept mean and what differentiates it and sets it apart from conventional, static data models?
Simple, static data models used to be the go-to standard for companies utilizing a PIM system in the past. More often then not, they are based on strictly defined attributes such as product names, descriptions, prices, or sizes. This usually one-dimensional concept is made to fit a specific set of data. This, in turn, means that every product has the same attributes and everything follows the same rigid definitions.
This works smoothly, as long as you have a clear overview of your product data and the requirements for your data structure are moderate. Wherever a company works with simple product information, such a model is sufficient. As soon as the products are more complex or serve different categories and use cases, however, static models are quick to hit a wall. The requirements concerning flexibility and adjustability grow – and here is where multi-domain comes into play.
A multi-domain data model follows a dynamic method which can be adjusted to a diverse range of data types and requirements. Instead of focusing on a single, set-in-stone structure, it allows for a flexible organization of product information across multiple “domains”.
A domain within a multi-domain model can, for example, be centered around specific product attributes such as technical specifications while others focus on information for customer analysis or supply chains. Each domain can be organized separately and adjusted on demand. This way, companies can manage different kinds of information side-by-side and put it to use in a strategic manner depending on target group or channel. Therefore, a multi-domain data model enables the parallel management of different worlds of data using an all-in-one approach.
The multi-domain data model sets new standards in product data management and offers clear benefits compared to static models:
The multi-domain data model provides enormous benefits for marketing since it is heavily reliant on up-to-date and precise product information. It allows you to structure product data in a more targeted manner and process it for different channels and target groups, in turn boosting customer success. Where static models are quick to hit the wall when it comes to both flexibility and data diversity, multi-domain models offer a dynamic and sustainable solution for modern product data management.
Companies who trust in multi-domain data models for PIM systems can meet the ever-increasing requirements of product data and are quick to respond to changes. This does not only render product information complete and consistent but – before anything else – flexible.
Author:
Marko Stuka
Senior Sales Manager
ATAMYA
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The ever-increasing diversity of product variants poses a two-pronged challenge to companies. On the one hand, companies can fulfill the customer’s wish with customized products, while, on the other hand, the resulting diversity of products comes with difficulties for production. A continuously growing variety of variants is becoming more and more of a competitive advantage because it allows you to satisfy the customer’s demand for individualized products. However, this also increases complexity and costs in production in turn. Batch-sized production doesn’t allow for reducing costs because you suffer from so-called scale effects as a consequence. In order to get a firm grip on the complexity of variant management and all processes involved, companies should make use of two things: a methodological approach when selecting the variants you want to produce as well as suitable technologies that can support you in doing so.
In order to define what variant management means we should, before anything else, clarify what a variant even is.
Variants (as in product variants) are specific articles which differentiate your general product on the basis of defined properties. Let’s illustrate this with the help of an example:
Variant management, accordingly, is all about the efficient selection, creation, maintenance, and handling of variants. It is integral to the fields of production, marketing, and sales.
Concerning effective variant management, the first question is: Which products do even need variants to begin with? The answer may depend on the demand voiced by you customers and the actual implementation. For example, is it economically profitable to respond to individual customer wishes? Once these questions are out of the way, you can start with putting theory into practice and realize processes for variant management.
For the efficient management of product variants, consequently, it’s decisive to determine how complex the products which need to be managed are. To this end, you can divide variants into three different groups:
First Group (e.g., t-shirts): There are only a few variants for the product and they are made up of only a few properties without a particularly complex set of rules. In the case of t-shirts, for example, this simple rule set may define that there are three sizes, each of which can be combined with one of four colors.
Variant Management: The variants can be easily created and maintained in a PIM system. Since a simple rule set is in place which defines the exact number of variants, it would be comfortable if you would only have to define the rule set itself in the system rather than set up every single variant individually.
Second Group: While there may only be few properties out of which the variants are formed, each comes with a large range of values — resulting in a corresponding number of variants per product (circa > 100). Examples for this second group are customized products such as, say, planks from the building supplies store, given that they’re manufactured to match every required length and width. If an oak wood plank with a length ranging between one to five meters can be cut to shape centimeter by centimeter, then you’re looking at a total of 401 variants. Consequently, if the plank has a width ranging from one to two meters which can be potentially cut to shape at every ten centimeters, there would be a total of 4.411 variants.
Variant Management: In this case, we have a lot of variants. Here, it’s imperative not to create every single variant in the system but rather only the simple rule work which underlies all variants. This rule work can then be provided, for example, to your web shop. Customers then choose from the pre-defined properties and enter required values — in response to which they receive their relevant variant. The system dynamically generates an article with an article number and forwards the purchase to the Enterprise Resource Planning system. If the article numbers are continuous, the article can be clearly identified across all systems.
Third Group: There are variants for a product, but these variants are created on the basis of a complex set of rules. That is to say, contrary to the first group, you can’t simply form variants out of permutations (i.e., all possible combinations of defining properties). For example: blue pants might not be available in the size L, while red pants are available neither in the size S nor M, etc. Such rule sets can contain a lot of complexity, as you know it from the automotive industry. More often than not, a lot of product variants are required here.
Variant Management: The creation of variants of the third group is most efficiently realized in the form of a special product configurator. Such configurations can be self-developed or you can rely on a standard software. The configurator is based on a complex rule set. This requires a lot of effort and an in-depth understanding of the product. Usually, the configurator also comes with visual or 3D support. On the customer’s end, the configurator — which may be operated either by the customers themselves or trained sales personnel — is used to configure the variant. It is often times the case that the configurator directly creates an article number for the specific configuration which is later referenced by the ERP system.
Besides efficient and comfortable product and article data management, a PIM system can help you in making sure that the variant management for the first and second group discussed above won’t cost too much effort. In the case of both groups, as already mentioned, it’s usually not required to manage every single variant but only the set of rules for creating variants. So, whenever a third-party system connected to the PIM via an interface in real time such as, for example, a shop system or an ERP system requires the information of some variants of the first group, the interface simply applies this set of rules and transfers all data. To this end, it’s best practice to automatically generate a suitable and unique article number. Make sure that all selection fields which serve the purpose of individualizing the general product into the specific variant are clearly defined.
Following the previous example for the management revolving around such a rule set for the first group: When creating the product in your PIM system, you set up the selection fields for possible colors and possible sizes.
In the case of variants of the third group, you can at the very least transfer the text-based product data and images from your PIM to the product configurator used by the customer.
Author:
Matthias Gärtner
Project Manager
ATAMYA
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You’d be happy about receiving support in your variant management and you’re looking for suitable software for you company? Then how about making contact with us so that our experts can show you first-hand how you can utilize a PIM system to successfully manage your full range of variants.
The implementation of Product Information Management software (in short PIM) is a crucial step towards preparing yourself for the competition of today’s digital world. Thanks to the digitization of your product data and information, your company can run the interfaces linked to shops and channels in real time and in a fully automated way. Only through this transformation will companies be able to fully exhaust the potential of digitization on a global scale and provide customers with product content in an efficient and target-group-oriented manner.
The PIM functions as your central datahub for all product data processes. Throughout, all data and information will be imported and unified from input channels such as an ERP system, will then be managed and edited within the PIM system itself, and, finally, distributed to relevant target channels ranging from online shops and apps to B2B marketplaces.
The challenge of a PIM implementation: simply installing a PIM system won’t be sufficient. Switching to an intelligent software solution requires more: it takes a PIM project with the goal to design new processes, develop new concepts, and implementing it all. The objective is that upon project completion, all systems in the company’s IT system landscape can efficiently and effectively collaborate with one another when it comes to product data. To this end, support can be requested from a wide range of service partners. They offer you to carry out the complete implementation as part of a so-called “full-service” project. However, do you really require this? Can’t your team accomplish this on its own?
Yes, your team can! Which implementation model fits best depends entirely on your individual requirements and your team’s skills. Equipped with the right concept and a good project plan, you’ll be able to quickly realize your project in a cost-efficient manner. We tell you what you absolutely need to look out for when choosing between full-service, do-it-yourself project, or a hybrid between the two.
As part of a full-service project, a third party is tasked to take care of the implementation for the company. In this case, your partner carries out the complete integration as well as the switch to the new system in your place. Such partners can be the software developer of the PIM system itself or a service partner who specializes in carrying out software implementation projects.
The advantages are clear as day: You save internal resources – which are, as is generally known, always hard to come by – and you directly collaborate with the experts for the system. With years’ worth of experience to back them up, partners know all the wrinkles of a successful PIM implementation and will make sure to make good use of this great foresight in the planning of the software environment. Naturally, the provider will demand an adequate fee for such service, which is why full-service counts as the most expensive model.
The most decisive difference, however: You let go of the steering wheel! In case of doubt, the third party which takes over may only have a surface-level understanding of your product portfolio and related processes. This is why the missing project control options of a full-service project pose various challenges and involves corresponding risks. If new processes and workflows are dictated by an outsider, it may be the case that they’ll find less acceptance and willingness to adjust accordingly by employees. If the new processes are conceptualized directly by your team, they’ll be quick to realize the added value and will look forward to the new software environment which can, thus, guarantee an improved work life. Lastly, the know-how for adjustments and modifications will fall outside of your own field of competence, hereby suffering from a one-sided dependency on your implementation partner – even after the completion of the project.
Full-Service Projects: Advantages and Disadvantages
+ Saving internal resources
+ Service partners are experts for the technological potential of systems
+ Service partners have project experience and know all best practices
– Full-service is costly
– Service partners don’t know your organizational structures
– Less project control tools
– Dependency on service partners for adjustments
– Loss of know-how after project completion
When it comes to the independent PIM implementation, it’s you who is taking control. Your unique advantage: The various corporate departments can each contribute to the implementation of the PIM system with their expert knowledge. First and foremost, this concerns the Product Management with its expertise in the requirements of technical data – ranging from the company’s print catalog to e-commerce platforms and partners. The marketing, in turn, knows exactly how products are presented in the best possible light in your online shop with the help of just the right texts and digital media assets. Another central spot in the project team is occupied by your IT. With their knowledge of the current software environment, they can set the foundation for all future interfaces connected to the PIM system. Last but not least, the position for the person in response and your taskforce must also be filled to complete the team.
What may always pose as a problem in self-guided projects: When it comes to the integration of new software solutions, there’re far-reaching decisions to be made, especially in the beginning. And this is where the big disadvantage of do-it-yourself projects comes into play: Many uncertainties and mistakes can trick their way into the very foundations of the project. This eats away valuable time and resources, while also weakening team morale. What you’re lacking now is an expert for the strategy and implementation of your system with a tailor-made roadmap to boot. In short, the best solution for a successful PIM implementation borrows a bit from both methods: expert knowledge of service partners combined with the already well-established expertise of your company’s specialists.
Do-It-Yourself Projects: Advantages and Disadvantages
+ Draw from valuable in-house knowledge about the product portfolio
+ You’ll become the expert of your own system
+ Plan and live your own processes
+ Know-how stays within the company
+ High acceptance rate when switching to the new software
– No best-practice experience
– Uncertainties when it comes to decision making
– Unknown or untapped potentials of the new system
As part of the hybrid solution, your project team collaborates closely with the implementation team. Thanks to the active participation of your teams, you create lived processes and satisfied team members. Experience shows: The hybrid solution proves to be particularly crisis-proof since it guarantees both a high acceptance rate and continuous progress.
Throughout, a hybrid project model offers you countless benefits based on close collaboration, tailor-made solutions, a methodological approach, and continuous success. Through the combination of expert know-how and experience, the project participants come to form tight-knit teamwork that enables you to tackle specific requirements and challenges in a targeted manner. This teamwork, in turn, contributes to optimally fine-tuning the solution to match your company’s individual needs.
A well-structured phase plan makes sure that all project participants have an overview of the progress and the next steps at all times. This facilitates the planning and enables your team to stay motivated through small but continuous successes. Additionally, you can optimize knowledge transfer with targeted software training. When trainings are directly connected with the respective relevant phase of the project so that your team always receives the required knowledge at just the right time, you can master the implementation in a masterful manner.
The support provided by both implementation partners and consulting teams makes sure that demanding questions or technical challenges always find their way to the right expert. This comprehensive support makes it possible to progress effectively with the project and gain corresponding momentum. All in all, the hybrid project model leads – thanks to its flexible and adaptive structure – to a high degree of efficiency as well as sustainable results that will be reflect itself in your company’s success story even in the long term.
And the best of all: The entire know-how and all important information stay within your company. This way, you and your team will quickly advance to experts who can adjust their PIM system even after the end of the project in a flexible manner. Decide for ATAMYA as your integration partner – and we will, of course, be at your service even after the successful project completion! We from ATAMYA understand ourselves as long-term partners and accompany you on your path to digital transformation as it suits your needs, so that you can draw from the full potential of your product data.
Author:
Yana Zabolotna
Copywriter
ATAMYA
Here, you find the right partner for your partner for your ATAMYA PIM project.
Welcome to Industry 4.0: The fast-paced development of Artificial Intelligence (AI) has already shaped many sectors, and Product Information Management (PIM) is no exception. AI offers a myriad of applications which can drastically improve your data maintenance, inventory management, personalization, information about customers and target groups, as well as image recognition in PIM. Additionally, the combination of PIM and AI provides your company with groundbreaking functionality – from data organization and analysis to the translation of product data into expressive and personalized information which can be put into action across all channels. This opens entirely new perspectives for a data-driven product management. In this blogpost, we have a look at the various use case possibilities of AI and PIM, identifying the areas in which the use of Artificial Intelligence is most profitable. Have a good read!
💡What is AI?
AI refers to the capacity of machines to simulate human intelligence and carry out corresponding tasks. This may, for example, include learning, decision making, or problem solving. Such simulations are based on various technologies such as machine learning or the processing of natural language.
One big advantage of AI is automated content creation. Today’s AI tools are able to generate unique content. For example, Midjourney can even create new, impressive images based on text requests alone. ChatGPT by OpenAI allows you to create diverse texts or well-structured articles in a matter of seconds. With solutions for content generation such as Retresco, users can transform data from their PIM system into high-quality texts. This saves both time and resources, while also accelerating the process of updating product information.
Accordingly, automated AI-based content generation is an effective tool for optimizing your Product Data Management, saving valuable resources, and, at the same time, establishing a smooth communication with customers that is in keeping with the times. This approach lets companies focus on more creative and strategic aspects of their business, while the high-quality content for efficiently addressing the relevant target group is already taken care of.
In Translation Management, too, AI can provide valuable support. AI-based translation tools such as DeepL, for example, can translate product texts into various languages in an automated manner. By putting these tools into good use in connection with PIM, companies can optimize their translation processes and manage translations more efficiently. AI enables the automated translation of product information into a wide range of languages. For your company, this means a significant saving in time and resources. Additionally, the PIM system can guarantee consistency and correctness when it comes to distributing this translated content to all sales channels and markets. With the combination of AI and PIM, companies can improve translation quality, shorten their time to market, and secure smooth communication with international customers. This allows you to be globally present and successfully market both your products and services in different countries.
AI can also help you in getting to know your customer better. The analysis of customer data enables companies to recognize patterns and trends which can then be integrated into the product and marketing strategy. This way, you can respond better to your customer’s needs. If you transfer the feedback data by customers into your PIM and structure it accordingly, an AI tool can process it and operate with it in real time. This is what you can use to draw well-informed inferences about the purchasing habits, preferences, and behavior of your customers. On the basis of this knowledge, you can design your product and marketing strategy in a more goal-oriented manner. What’s more is that companies can objectively evaluate the efficiency of their product offer and their marketing measures. This, in turn, allows you to swiftly make adjustments and optimizations to the strategy for higher customer satisfaction and customer retention. With personalized offers for related products, tailored advertisement campaigns and targeted recommendations, companies can strategically position their products – which translates into more sales and, ultimately, more profit.
Personalization is a key factor for success in today’s competitive markets. The combination of Artificial Intelligence and Product Information Management (PIM) is particularly useful when it comes to this topic. When customers are offered products and services which best correspond to their needs, they have the feeling of being understood and that they are met on their own grounds. This does not only increase customer satisfaction but also leads to higher conversion rates coupled with lower product returns.
A high-performance PIM system enables the target-group-oriented and channel-specific distribution of content in order to achieve a higher degree of efficiency and relevance. In short: The dream of personalized customer communication with the right content at the right time with the right person – and that in a fully automated manner – becomes reality. Tools such as Retresco even make it possible to reformulate general product texts for individual target groups – automated and in direct connection with PIM.
With the use of a Recommendation Engine, you can also handle targeted recommendations for products. A product recommendation which matches the customer’s individual needs improves the purchasing process drastically and optimizes the Customer Experience. The continuous analysis of customer behavior does also make it possible to better recognize the customer’s wants and to optimize the assortment accordingly. Companies which bank on personalized recommendations are successful in setting themselves apart from the competition and can expand their customer base progressively. At the end of the day, all this manifests itself in an improved conversion rate and maximized customer retention.
A very promising field of application for AI in Product Information Management is the automated image recognition and keyword tagging of products. An AI algorithm can analyze images and identify the products depicted on them by various attributes such as type, color, brand, size, characteristic features, and material.
AI can deliver precise results with targeted training (Deep Learning). On the basis of an extensive collection of product images from a PIM system with informative meta-data (Big Data), an AI can, for example, learn how to classify products on its own. Accordingly, the AI system may recognize a piece of clothing or a machine even if it is depicted in an odd angle on the image, remains partially concealed, or if it is taken under unfavorable lighting conditions. The integration of AI-based image recognition in the field of PIM opens up a new dimension for the automation and optimization of product management processes, so that companies can profit from an efficient data handling and a precise categorization of data.
In the age of Industry 4.0, where technologies like Artificial Intelligence play an ever-increasing role, fascinating perspectives emerge for data-driven product management.
The intelligent use of AI in the PIM field unlocks a wide range of possibilities. This starts with automated content creation that does not only save time and resources but also delivers high-quality information. And it continues with precise translations of product texts into various languages in order to tap into international markets – here, AI has proven itself to be a top-performing partner. Furthermore, AI enables a deeper understanding of customer needs through the analysis of feedback data and holds the key to a great many possibilities concerning personalized customer communication, resulting in a higher satisfaction rate and brand loyalty.
All in all, Artificial Intelligence provides enormous options for optimizing – if not revolutionizing – Product Information Management. By supplying top-quality product data that is always up to date, companies can exhaust the full potential of the AI revolution in PIM with all its benefits, while also establishing their competitive prowess in a continuously more data-driven business world. With the right tools and a solid data basis, companies can increase their efficiency, provide personalized purchasing experiences, and make well-informed decisions. The future of data-driven product management will be shaped by AI, and those who seize the opportunity will stay streets ahead in the competition.
Author:
Eric Dreyer
Head of Product Management and Quality
ATAMYA
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Do you want to learn more about the possibilities of AI in Product Information Management or are you simply looking to discuss this exciting topic with somebody? Contact us now and let’s explore together how we can elevate your Product Data Management to the next level!
