How Product Data makes the difference in E-Commerce

May 5, 2022

Product Data

What used to be oil is now data. More and better product information provides the basis for commercial success – especially in e-commerce. It’s all about using intelligently prepared data to attract customers to your own website, offer them a unique shopping experience, and ultimately bring them to conversion. Solid, consistent and up-to-date product information is the basis for this.

Product Labeling – What is it?

What is product labeling? It is primarily about assigning structured information to different products. This information can be technically available in different formats.

The basis for accessing the information is always a database.

Content management systems and online store systems access this data and present it in the form of structured data. On the one hand, this facilitates user-friendly presentation in the online store, and on the other hand, it enables search engine-compliant tagging.

Google-compliant tagging is mostly done in microdata format. This gives the crawlers of the search engine clear signals regarding the type of information. Important product data are, for example, brand, size, shape, application area, style, type, color and the like. Outsourcing solutions are suitable for the creation and enrichment of such data sets – for example, with crowdsourcing. Thus, a large number of microjobs are offered, which are to assign certain characteristics to individual products. AI systems, which are particularly powerful, can also be used to supplement this.

What kind of Product Data exists?

Product data comes in numerous forms. The following are just a few examples that illustrate how complex the many pieces of information surrounding a single product can be:

  • Images
  • Titles
  • Brand names
  • Attributes (style, color, shape, cut, etc.)
  • Prices
  • Categorization
  • Descriptions
  • Variants
  • Availability

One thing is clear: A site that provides as much information as possible for each product scores over the competition. Product labeling with meta data is the heart of e-commerce. More and more customers are shopping online – that’s why it’s also important for small and medium-sized companies that were previously only analog to jump on the digital bandwagon so that they don’t miss the boat.

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Product Metadata makes the difference

Product metadata are all the characteristics of a product that are available in structured form. With comprehensive product tagging, online stores achieve many goals that lead to more sales. These include, for example:

  • optimizing the crucial first impression (images, title, description and information),
  • making it easier to search for products in the store by providing a rich information base
  • and the improvement of usability: metadata provides the prerequisite for the website to function in the customer’s sense.

Even a perfect design cannot do without structured product data. The look and feel of an online store is therefore based primarily on reliable data.

Quantity and Quality are important

When it comes to product data, it is often the quantity that makes the difference: If online store A offers more data on the same product than online store B, online store A initially has an advantage. Potential customers prefer sites with more information.

At the same time, however, users also place demands on the quality of the data. Here, negligence on the part of the provider can be costly: Customers lose trust. The three biggest mistakes with product data are

  • Incompleteness (missing information on products),
  • Inconsistency (incorrect, for example, outdated product data),
  • Inaccuracy (data with a low information content).

Only reliable, detailed, and accurate product data ensures simple and efficient management of products and their suitability for display in online stores.

Product Tagging is SEO-relevant

Product tagging is an essential element of search engine optimization in the shopping sector. Most online shoppers start their search on Google – be it via text or images. Carelessness in tagging becomes noticeable: Irrelevant search results cause a negative customer experience and cast a bad light on the provider. Many visitors to a product page are of no use if users click back in disappointment because the result is not relevant. This can happen, for example,

  • if a product is classified in the wrong category,
  • if it contains incorrect information about essential features
  • or the data listed is incomprehensible to the user and thus useless.

Product tagging is therefore relevant to SEO. Therefore, it is important to consistently pay attention to the quality and timeliness of the respective data. Continuous data maintenance ensures more visitors and satisfied customers in the long term.

Demand Forecasts and Inventory Management

Consistent and detailed product data is essential for estimating demand and managing inventory. An universal product code alone is not enough to know at any time what is currently happening behind the scenes and how, for example, customer demand habits are changing.

Missing, incorrect or incomplete data on products leads to wasted resources through the purchase of items that ultimately remain in the warehouse – because they do not meet a corresponding demand. Detailed and up-to-date product data, on the other hand, helps e-commerce companies to develop a successful inventory strategy.

Digital Transformation

Structured data forms the basis for digital transformations in areas that previously functioned in an analog fashion. Competition is getting tougher, customers are demanding more innovations and convenient digital shopping options. A fragile base of unorganized and unstructured data makes this transformation very difficult.

Digital transformation is greatly simplified by structured product data. They remove hurdles to entering online marketing and make it easier to compete in this market.

Automatic Product Tagging with AI

Artificial intelligence imitates human thinking. Cognitive computing (visual AI) goes one step further and deals not only with logical conclusions, but also with the perception and independent recognition of contexts. Visual AI perceives images with human-like accuracy and can, for example, capture and assign various elements in product images.

In doing so, AI often serves as a complement to data created by humans.

  • For example, if a leather jacket has been pre-tagged by a human as a short biker leather jacket, visual AI will take on additions such as “white lined,” “casual style,” or “silver buttons.”
  • In addition, tags based on image data ensure that exactly those products are displayed that are particularly popular with customers. And they do so even if their requests don’t match the wording of an existing record.

The benefits of AI-powered product tagging are clear:

  • It delivers more accurate search results.
  • It requires fewer personnel to do so.
  • Finally, AI improves the efficiency of product tagging.

AI-based product tagging optimizes a vendor’s chances of providing its customers with a consistently positive shopping experience. This also creates synergy effects: Over time, word gets around about which website has comprehensive and reliable information available. Automation leads to more data with better quality.

Conclusion

E-commerce cannot do without reliable product data in structured form. This is because they provide the basis for successful online stores that offer customers a unique shopping experience. Metadata is also relevant for search engines. And finally, this data improves the chance of not falling behind in the digital transformation, but of exploiting all of the market’s potential on the web.

Dieser Artikel wurde am 05.May 2022 von Jan Knupper geschrieben.

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Jan Knupper




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