In B2B ecommerce, catalog search could be considered a primary tool for customer interaction — and buyers expect high-level relevance, suggestions, multiple languages, faceting, and near-instantaneous responses.
Unlike B2C, in B2B ecommerce, users often look for items containing unstructured information. These can be manuals, drawings, assembly diagrams, photos, original and non-original (similar) spare parts. Since the average cheque in B2B is significantly higher than in the consumer market, vendors must do everything possible to provide the best user experience in catalog search.
There are two essential factors in B2B commerce when we talk about product catalog search challenges. The first refers to the fact that corporate buyers (aka users) visit the vendor ecommerce website solely for the purpose of purchasing, and not for a pleasant time like in B2C. Their task is to buy the necessary goods or services for the company and do this as quickly as possible.
Therefore, the vendor must value the time of the buyers, who are also paid by their employer. In other words, searching through the product catalog should work as quickly and as accurately as possible. But these two functions, accuracy and search speed, do not go well together in terms of the design and operation of IT systems.
The second factor is that in most cases, the buyer must be authorized to access the catalog. That is, the seller knows the user's personal data and the company for which the user is buying. Accordingly, the purchase history of this user and of the entire company is known. Such information helps both the personalization of offers and the relevance of search results.
Historically, “searching” a directory meant retrieving data from a structured data repository. With the advancement of search technology, today's sellers have at their disposal both open source Elasticsearch and cloud AI-powered cognitive search technologies.
Virto Commerce catalog search module supports Elasticsearch/Elastic Cloud and Azure Search engines. Document-based full-text search and text analysis for products and categories are available for users. The search logic is extendable and customizable with third party modules.
In this first article, we discuss why Elasticsearch is used for one of the most complex problems in ecommerce, namely search. The second article is dedicated to Azure Search service as the best on the market example of AI-powered cognitive search for B2B ecommerce portals.