Most e-commerce websites have their sales inventory items as a large collection of private data. This data is private to the business and is centric to the operations of the business. The private business data can be either in structured format as entries in a SQL database or in an unstructured format as documents in a no-SQL data store. In either case, for an user to effectively search and locate an inventory item, it is imperative that search functionality be feature rich and robust. Users want to type less on the search bar but expect good quality results from the website.
Cognitive search is a technology by which a user of a website is able to search the business inventory just like how Google or Bing is able to search for webpages on the internet. This technology is akin to the concept of a private search engine that indexes the private business data and delivers accurate search results based on user input. This technology can be thought of as a search engine as a service for private business data. For example a user on an apparel store can type “spring collection orange shirts” and the e-commerce website will list the items that match his query.
The success of a retail business is defined by its ability to sell the items in its inventory. When the retail business is being served by an e-commerce website, much of the ability to sell inventory items is governed by the intuitive organisation of the inventory items. When the number of items in its inventory becomes large, the effectiveness of hierarchical grouping of items tends to become ineffective.
Now imagine that instead of having a group wise ordering or a hierarchical ordering, the user is presented with a simple search bar. In the early days of internet search, Google came up with the idea of a simple search bar that can produce a good quality search result for what the user is searching. Customer friendly information retrieval is the key to unlock the selling potential of a retail business. Most search functionality in current e-commerce websites are implemented as an elaborate form based user input. This is a rigid and ineffective means of information retrieval. Retail businesses can benefit hugely by providing a flexible searching and querying functionality to bring out the inventory accurately. If the user is able to search his item of interest quickly, it reduces the friction in the buying journey. Studies have shown that when the search is quick and effective, the customer retentivity of the e-commerce website is enhanced.
Most large e-commerce websites make use of this functionality. Thanks to the democratization of artificial intelligence, now any retail business can make use of the cognitive search capabilities.
The cognitive services feature is provided by Microsoft Azure and it exposes the search functionality as a service. This allows any professional developer to access the search engine capabilities and apply it on his / her own private data. To add cognitive search features for an e-commerce website, local data inventory corresponding to the items in sale have to be aggregated as indexable elements. This can either be as JSON documents or as keys on a SQL database. After setting up the source of indexable elements, the rules of association for the indexable elements have to be set up. The search target functionality can be one of the following - scoring, faceting, suggestions and synonyms. This completes the data setup for the retail business. Now the search functionality can be implemented on the e-commerce website front end to deliver natural search experience.
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