Fri, 06 November, 2020
A first wave of B2B marketplaces oriented to manufacturing, such as eBay Business, Alibaba, Global Sources or ThomasNet; started around year 2000. This marketplaces mainly integrated in its core of the platform a consumers oriented e-commerce user experience approach.
WeldGalaxy, as a knowledge based driven marketplace, addresses a specific (niche) vertical market; focused on arc welding. The project supports a data driven models to improve the supply chain and extends a servitization driven interaction between buyers and offerors. In WeldGalaxy both buyers and offerors also can collaborate, share trusted technical/product knowledge and provide knowledge based services or experimentation.
Further than its core functionality and envisioned business, the WeldGalaxy platform`s user experience (UX) and usability, is also knowledge driven. The marketplace platform uses analytics to collectively gather the feedback, behaviour information and knowledge from all the users; while the digital users use or acquire/provide the products or services in the marketplace ecosystem. This data and information is gathered as adaptive knowledge (descriptive, predictive and synthetic), by using analytic tools. In WeldGalaxy data analytics is used over adaptive knowledge so new optimized user interactions and experiences can be developed for the marketplace; the interaction between the analytical and UX tools, is linked and exploited to enable performance, easy engagement with targeted audiences and good usability.
The overall goal of the analytics in the WeldGalaxy approach is to provide simple configuration requirements and have a highly customisable marketplace platform experience for both, suppliers and offerors. Under a digital based data-analytics approach, WeldGalaxy brings the equivalent to the voice of the customer (for buyers and offerors) to the B2B platform environment. By coupling this approach with the data and knowledge driven services strategy of the platform, WeldGalaxy empowers both type of users/customers by supporting them to make decisions on information and value.
Courtsey: LifeSTech Team from Universidad Politécnica de Madrid