Trends and challenges

Trends and Challenges of Product Data Management 2023

 

AI, headless or real-time data? What trends and challenges in product data management can you expect in 2023? Where will the journey in the field of data syndication, data onboarding, omnichannel or even PIM go in 2023? We asked our CEO Guido Sauerland and Business Developer Fabian Fischer.

Read the interview to find out what trends and challenges you will face in 2023 and what developments you can expect from us in product data management.

 

What trends and challenges in product data management should companies consider in data syndication?

 

Fabian:

I think it becomes more important with every year, including 2023, that companies continue to adapt to the fact that there will always be different data sources. These are, for example, the ERP for price information and packaging data, and the PIM for product data and technical information. These have to be merged channel- or customer-specific in order to be able to extract them afterwards. In my view, this is a given challenge that cannot be solved because of the relevance of the systems. Accordingly, companies must find a solution here.

There are two other points that go hand in hand with this, one is responsibility and the other concerns processes. Because if several systems have to be taken into account, it is usually the case that several people from different departments or specialist areas have to deal with these. There should be one person – or even better, one role – who pulls the strings, brings them together and keeps an eye on the process.

 

Guido:

I agree with Fabian on that. It’s simply an internal challenge that companies will have because they still have to anchor this organizationally. The question here is where to establish this leading role, either in eBusiness, marketing, or IT. Data syndication is a cross-cutting issue. I think everyone is aware of that. Therefore, it is even more important to have a clear responsibility so that the topic can be successfully driven forward.

On the outside, unfortunately, the previous year will continue. Due to supply chain problems and resource shortages and also staff shortages, there are always various challenges to deliver the product. Conversely, for data syndication, this means that companies need to be much more active in communicating towards target marketplaces or even customer systems. There needs to be much more frequent information and reporting on product availability and changes. This is a trend in data syndication that will continue this year. As a result, it will be necessary to make data syndication processes even more agile or real-time. This is the only way to update data fast enough.

“Headless” will also continue to gain importance for me in 2023. Companies can integrate interface software, such as CatalogExpress, into their systems, store systems or customer portals. The data syndication software runs in the background. It therefore remains completely invisible to the user.

With headless or even an M2M interface, “product data as a service” will thus also be an upcoming trend in product data management. Retailers will be able to configure their own product data catalog. Data suppliers and manufacturers can thus reduce their data syndication efforts.

 

What trends and challenges do we face in data onboarding during the New Year?

Guido:

Basically, there are similar developments here as there are in data syndication. Due to inflation and the huge raw material surcharges, suppliers will adjust their prices more frequently. Also, whether products are available or not will have to be communicated regularly. Conversely, this means retailers will need to receive such product information from their suppliers much more frequently.

It will therefore be more necessary to “onboard” data more often. To do this, companies will need to implement appropriate systems and at the same time automate processes further.

Retailers should avoid having to look at every product update individually, and should only deal with information that is really relevant. It needs to be possible to automate non-critical changes.

 

Fabian:

I think one topic that will accompany retailers in their data onboarding in 2023 is the variety of different product data.

Suppliers and manufacturers are positioned and structured differently. Retailers must be able to respond to this by having the “perfect data suppliers” on the one hand. They deliver their data exactly as it is needed. On the other hand, there are data suppliers who can just fill out an Excel list. This remains a challenge that cannot be solved in 2023 and probably not in the next 5 years.

If retailers want to expand their product portfolio or follow the trend of regionality, they have to adapt to this and offer solutions. They can’t then just say, “Okay, then I don’t want to work with those.”

Therefore, it is important to have several gateways for the product data of the data suppliers. One is via a standardized way, where I can act completely automated or the way that I support “less well positioned suppliers” in data preparation, e.g. by pre-filled EXCEL tables or helping to classify the product data.

Conversely, good supplier data onboarding also pays back into the sales of the retailers. Because if good product data is received there, this naturally has an effect on data syndication. The products in the store or in eBusiness generally become more visible, which makes them easier to sell. Retailers are therefore dependent on the quality of their suppliers’ product data and, in this way, are all sitting in the same boat. It is therefore worthwhile for both parties to work well together right at the very beginning of the content supply chain.

 

What do developments in product information management look like in 2023?

 

Guido:

We see in our customer and also prospective customer environment that PIM systems are once again becoming massively more important. On the one hand, there is a need to include more content in the PIM systems, so that not only product information, but also customer information or even customer-specific prices are stored there.

On the other hand, there are many companies that are re-evaluating their PIM because their needs have changed. But there are also still many companies that want to initially introduce a PIM system because they realize that an ERP system does not offer as much flexibility in product data management (e.g., in terms of classification of product data). Often, the ERP is then combined with the PIM system. Some companies then pull the ERP data through the PIM system, so that the data’s discharge into other channels only has to take place there.

Real-time data is also becoming increasingly important in PIM systems. Therefore, it will be a matter of preparing interfaces accordingly. Many PIM systems are already well positioned here with scalable technologies such as Elastic Search, Data Hubs or MongoDB. These are designed to be able to handle many queries so that the systems are not paralyzed during content extraction in real time.

In the future, this will be a continuous product data pipeline.

 

Fabian:

In addition to the developments described by Guido, data security will also play an important role in product information management in 2023. Companies should keep a close eye on this, and not just for GDPR reasons. Product information is sensitive data. If this data gets lost, it would be extremely critical for the business.

 

How will product data evolve in 2023?

Guido:

One development in product data management in 2023 will also be to individualize content on a channel-specific basis. So content will continue to grow. Companies will not be able to manage this high level of product data maintenance economically. Therefore, product data creation will increasingly move towards content automation. Different types of texts and even product features can be generated and keyworded automatically.

As a result, product data will increasingly follow the Product Experience Management (PXM) approach. There, the goal is to create a holistic customer experience. For this, I need valuable and thus also customer-specific content that is precisely tailored to the target systems.

Marketplaces are also taking this approach. They are placing more and more stringent requirements on merchants’ product data. Companies should therefore continue to improve the quality of their product data in 2023, otherwise they risk being unlisted.

Product data is constantly evolving not only through PXM, but through standardizations such as ETIM, BIM or ECLASS. The nature of content will continue to change. Depending on the industry, augmented reality will of course play a role in product data. Furthermore, video content will become more and more important in product data management.

In 2023, companies will once again face the challenge of having to continuously adapt their product data.

 

Fabian:

The final point is that the developments explained by Guido, whether augmented reality, video content, or even standardization, involve data. Some of this data has to be newly generated or combined from existing product data and then stored, e.g. in the PIM system. The amount of product data is constantly growing, becoming more and more diverse, and should still be available quickly. It is therefore important to rely on appropriate technologies to increase performance.

 

What can our customers/prospects expect from us in 2023?

Guido:

We always want to become even better and smarter. That’s why, in 2023, we are addressing the issue of artificial intelligence as part of our product development and several research projects. Intelligence, however, is perhaps not the right word. Rather, it is about algorithms that help to proceed intelligently. For example, we would like to enable automatic mappings in CatalogExpress to a specific target format.

We want to make the analysis of product data in data onboarding much better. So how can it actually be evaluated whether a catalog is really good. Based on hard criteria, such as 90% of the products must be provided with an image, a catalog can already be checked. However, we want to use AI to try to evaluate a catalog in terms of its quality. In this way, we want to determine, if the catalog fits together in total, e.g., does the product text really fit to the described product attributes.

We also intend to help our customers automate further processes in the area of classification. For companies that have to handle hundreds of classes in several classifications and thousands of attributes in each class, this means an incredible amount of work in the preparation of product data. New versions of classifications such as ETIM or ECLASS are released at regular intervals. Then it is necessary to look again where the changes are. This is where we want to offer further automation options. This is then no longer artificial intelligence, but goes in the direction of Robotic Process Automation (RPA). In the future, this will allow companies to save a lot of time in product data classification.

Of course, with all the automation, I also have to let people check again. AI is a learning system in which the database plays a key role. If the database is poor, the AI behind it is also poor. This means that the AI must be fed with good data again and again. To do this, we will always need humans who analyze the data to ensure that everything the AI is doing is correct.

In addition to automation, we will also continue to work on real-time data provision. Here, we can already import data into CatalogExpress very quickly with the standard interfaces from CatalogExpress to MongoDB and also make it available.

 

Fabian:

Our customers and prospects can expect that we are not only software producers, but also customer understanders. We develop our software very closely to the needs and wishes of our customers. That’s why we’re expanding the area of consulting, i.e. customer support, in the coming year.

We would like to support companies with a lack of know-how or resources in product data management. If required, we can completely handle product data provision with marketplaces, data recipients, etc., or just take over individual parts of it, such as mapping. With both options, our customers always have the possibility to intervene themselves if they need to make adjustments to their product data.

Depending on the needs, our customers can handle data syndication and omnichannel distribution completely on their own, or let us handle it, or a hybrid of both.

In 2023, we also want to continue to keep data security high and maintain DSGVO compliance in our systems as well. CatalogExpress and Supplier Portal are hosted in Germany and have the highest security standards.

We are also actively involved in a research project that deals with data trust models. This project involves, among other things, how data sovereignty, data security and the correct data processing can be verified for each user.

 

How to handle trends and challenges in product data management the right way – with nexoma

You would like to know how to cope with the trends and challenges in product data management for your company or you are interested in our software tools CatalogExpress and Supplier-Portal? Then arrange a non-binding consultation with us now.

Wer hat‘s geschrieben?
Julia Neuhäuser
julia.neuhaeuser@nexoma.de

Julia has been part of our marketing team since March 2022. As a Bachelor of Arts in Service Marketing, Julia provides you with content on marketing topics, success stories and the NEXIpedia, among other things.