The biggest limitation in the e-commerce industry today is the burden placed on the consumer to choose and then fine- tune a keyword that accurately identifies or describes the product they want. Even though a great deal of work went into trying to add intelligence to keyword search box, it is still not up to the task. If the keyword is chosen right, the respective search engine’s algorithm will fish out relevant results. If not, consumers will have to iterate with the keyword trial and error until they find what they are looking for. More often than not, keyword search does not go as planned and requires tremendous time commitment.

amazon typical search irrelevant results

Typing “woman shoes red summer” show irrelevant results for the consumer looking for a pair of red shoes for woman for the summer.

Beyond Keyword search

The average keyword search engine algorithms of today lack the ability to understand a given search query with the nuances of language, as a human would. They lack the contextual knowledge, the practical intelligence, and the ability to understand natural language expressions. The power of artificial intelligence combined with natural language processing capabilities (NLP), would put the human element back into a digital experience. Natural language processing seeks to understand text as humans understand text by applying contextual understanding. Shoppers will be able to express their desire, needs, and associated requirements in greater depth.


Towards a Virtual Private assistant

We are shifting from being passive information retrievers to active players. Let’s introduce the Virtual Private Assistant (VPA).
A VPA is incorporating features of proactive personal assistance predicting behaviors, preferences and future purchases. It will also require using your accumulated input data coupled with knowledge that has been amassed and amalgamated from many sources.
It should seamlessly handle a number of complex requests, not just in terms of comprehension but by performing a multitude of services. VPA should be omnipresent in order to understand the preferences and history as the consumers engage with it throughout the day. Providing consumers with improved understanding and a more human touch.

Using metadata, semantic analysis, collaborative filtering and predictive recommendations, the VPA continuously refines, organizes and delivers experiences tailored to a user’s specific needs.
It detects the user’s immediate intent, increase exposure to information, quality product and interesting deals.
Hence, the ability to foster long term customer relationships and boost loyalty.