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Always Complex, but Soon Unmanageable?

Short product lifecycles and evermore fast-moving trends pose a major challenge for the industry – a challenge both manufacturers and retailers must get to grips with. International competitive pressure too is growing, meaning if you want to thrive in today’s industry, you need to scout developments and trends early on, well before the competition. As if this all weren’t enough, customers are becoming more and more demanding. And what do they ask for? Personalization. In products and communications alike.

The customer journey has never been more relevant, offering individualized content at every touchpoint. Applying strategic data management is the only way to achieve this. Whether that’s omnichannel, AI or IoT, it’s always about data. Few industries can rival fashion, sports and luxury goods when it comes to data-driven, disruptive concepts. Want to thrive moving forward? Be a data leader.

Choose Disruption

Meeting the regulatory requirements of the Supply Chain Act is pretty much a case of freestyling it out. Regulation, customer demands, competitive pressure: ultimately, manufacturers and retailers will have to leverage data to organize their value creation processes to make the cut. But that requires the right mindset, the strategic drive to put data at the center and rely on it to make decisions. Data leadership requires disruptive change, especially in this industry.

Three Trends Revolutionizing Your Industry

The Customer-Centric Retail Chain

If you want to address your customers as individuals, you need to know, at any given time, exactly where they are on their customer journey and when, where and how they want to interact with you. If we’re talking omnichannel and direct-to-consumer, you need to collect and analyze data to identify and leverage the right sales options. After all, the 360° customer view is all the buzz for a reason: it’s vital at every single stage of production and retail. And the aim? Higher customer lifetime value and lower customer acquisition costs.

Product and Supply Chain Transparency

Not only is it enshrined in the Supply Chain Act; your customers want it too: clear evidence about processes, sustainability and the composition of goods. Transparency – about the supply chain, supplier and manufacturers – is a must, and strategic data management is the foundation. Plus, it allows companies to accelerate their onboarding for new products and suppliers because all the relevant information is already available when the product is still being created.

Overcoming Silo Infrastructure

Let’s be real, it’s not all that useful to center your data strategy around individual processes and functions or to apply a silo mentality to your infrastructure. Because when the value chain is not fully integrated, redundant data is kept, calling up information takes far too much time and the time-to-market is longer than ever. By contrast, end-to-end data-based companies identify relevant trends, develop successful products and meet new customer needs – quickly, automatically and efficiently.

Customer Voices

“Taking a bird’s eye view enables us to shape the digital future effectively, reduce costs and systematically address the turnover of our digital markets. In this respect, Parsionate has provided valuable momentum to turn our vision into a reality.”
“With its expertise in digitalization, Parsionate is a key partner for us in Engelhorn’s strategic development.”
“Parsionate’s Application Management team takes the weight off our organization. With their pragmatic approach and their close relationship with technology providers, they help solve problems quickly, giving our team the chance to focus on further developing the IT structure.”
“Customer satisfaction is our main focus. Exceeding expectations is what drives us. Applying this technically to specific customer touchpoints is an ongoing task.”

Data Leadership For Experts

Thank You, Managers. From Here On, It Gets Boring…

Or simply more specific (however you like to see it).
The experts among you will probably appreciate that we also provide insight here
that goes well beyond the necessary basic understanding. So, let’s go!

Technology Issues in the Industry

For Experts Only: Technology Issues in the Fashion, Sports and Luxury Goods Industry

Automated Onboarding

Until recently, onboarding new suppliers, or more specifically their data, was a tedious, manual process involving hours of cumbersome manual import and the manual mapping of un- or semi-structured product lists or supplier provisions. These are exactly the kind of onboarding processes where automation promises incredible efficiency gains. In fact, your suppliers can even handle this process themselves, with data provision based on templates and standards set out for specific product groups, for example. Not only does this drastically reduce process costs; it also frees up your employees to devote their time to more valuable tasks – think strengthening supplier relationships or optimizing your product range.

The idea of a golden record also plays a key role in automated onboarding. This means you select the attributes from each data suppliers that have the highest quality. And it goes without saying, the best way to do this is automatically, with the help of trained and optimized machine learning models known as matching algorithms. Data lineage, on the other hand, aims to boost transparency and traceability regarding which suppliers you have received which data from and where it’s used. Another valuable tool is automated supplier scoring, where suppliers who provide better and more comprehensive product data are granted better conditions – and greater visibility in your channels and campaigns.

Creating Content Automatically

Another prime area for automation is your marketing content. The right combination of data and AI is now more than capable of creating convincing content with natural language generation (NLG). This allows you to generate highly targeted texts based on relevant product attributes, with the NLG application helping you personalize your customer approach more efficiently than ever. It’s never been easier or faster to expand into new countries and markets.

That said, if you want automatic content creating tailored to your target group, you can’t do it without a professional data quality and governance organization. As a truly sophisticated automation application, it only works well with complete and consistent data.

Gaining Market Insights

How exactly do your customers behave? And why do they behave the way they do? If you want to tap customer motivation and behavior – including across different customer segments – you need to systematically analyze the data provided by the customer journey at all touchpoints. Now you can do so better than ever with appropriate data analytics to give you fresh insights. There’s a plethora to discover on basket abandonment or on customer behavior signaling which next best action to choose.

Composable Commerce Made Easy

Analysts at Gartner coined the term composable commerce back in 2020. Because online commerce isn’t just growing apace, it’s also unbelievably fast-moving. And in an environment like this, stocking your products in only one online shop or on a single platform can quickly prove fatal. Composable commerce means that a range of online sales channels can be combined with ease, fully in line with needs and trends and with maximum flexibility. The key to making this work is a modern product information management system (PIM system) and a modular data and system architecture based on the headless principle. With this in place, it can take just one click to update product ranges and data across all desired channels. Plus, the approach allows for maximum technical flexibility: if certain system components no longer fit or new market solutions emerge that better address your company requirements, the old components are easy to swap out or replace.

A Sophisticated Multi-Brand Strategy

There is definitely overlap between composable commerce and a multi-brand strategy, as multi-brand strategies are also applied to offer the same products via different channels. The only difference is that it does so based on different market presences, allowing it to speak to your target group in the best possible way. This sort of multi-brand strategy turbocharges the requirements for mapping processes and data structures because the content needs to be contextualized correctly every time. For example, you would stage the same T-shirt differently for brand presence A than for brand presence B, which may well require new, target-group-specific product descriptions, product photos and potentially different models as well.

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