Correlation between data quality and success in e-commerce
In addition to product quality, optimized logistics, and the rest of the e-commerce toolbox, it’s often the product data that significantly impacts return rates, margins, and the customer experience. A good reason to take a closer look!
€73 billion in online sales in Germany: the pressure is on
The year 2020 was special in many ways. And among many other developments, one thing accelerated significantly: the shift of purchasing processes to the web. This shift affects online shop revenues, return rates—and increases the pressure on all processes related to online shops, marketplaces, and product data.
Want some figures?
- According to a Bevh survey, more than one in eight euros of household spending on goods was spent in e-commerce—around €73 billion in 2020.
- Of that, a good €25 billion came from Amazon alone.
- Across all product categories, the return rate exceeds 6%—with Germany leading Europe with an estimated 315 million returned parcels in 2020.
(Sources: absatzwirtschaft.de; collect.ai; businessinsider.de)
Key questions in this context
- How can the USP of my products be presented creatively and convincingly—especially when they are easily comparable with competitor products?
- The return rate is a margin killer—what can my product data do, what can’t it do, and what should I watch out for?
- How can our data be structured and prepared to meet third-party system standards so that our product placements are optimal?
Significance from a Data Perspective and a Manufacturer’s Perspective
There’s a lot that could be said about various aspects of this development. For example, that the 65+ age group is the fastest-growing segment among e-commerce users, growing by around 160%. Or that Amazon, for instance, still appears to destroy returned items. But let’s stay focused on our main topics...
From a data perspective, the increasing dominance of marketplaces mainly means that product data is increasingly processed by third-party systems and must comply with external standards.
From a manufacturer’s perspective, the decision to “do e-commerce in-house” is heavily influenced by the opportunities and constraints of marketplaces, often supplemented by large retail partners. This frequently brings with it enforced transparency and comparability with competitor products, making the creative presentation of USPs increasingly difficult.
Large platforms scale well—also in negative ways: poorly maintained or communicated content can, with fast-moving products and high sales volumes, quickly lead to high return rates that destroy margins—especially when operating with an aggressive pricing strategy.
What Needs to Be Done?
So, what actions should be taken if we consider current market conditions as an opportunity for e-commerce?
1. Understand product data maintenance and modeling as directly revenue-relevant—and keep challenging and optimizing them regularly.
2. Implement a data model that is flexible in its output: Ideally, it should be possible to map additional classification standards alongside your internal structure.
- Products need to be described differently depending on context—without requiring unnecessary duplicate maintenance.
- Images and media in general must be exportable flexibly, in terms of format, naming conventions, etc.
3. Stay alert: Errors in data maintenance happen. It becomes critical when they go unnoticed throughout the entire supply chain. In such cases, it’s important to have already built a publication process that allows for shortcuts when necessary.
If you have questions on this topic, we're happy to offer our support.