Forecasting customer knowledge Management ckm leveraging big data Techniques in global retail industries

Abstract

Customarily, people make their choices in favor of buying any product, primarily newlinebased on (1) the knowledge they have acquired about the product and the surrounding newlineservices, (2) comparisons they have drawn (mostly in mind) about other products newlinecomprising of similar attributes or offerings and (3) a fitment they have imagined, the newlineproduct can offer specific to their requirements. Question is, can businesses manage that newlinevery knowledge customers acquire in their favor, for their product including the newlinesurrounding services that entails the product? Of course, management of customers newlineknowledge (CKM) alone will not cut it, unless the promise about the product or service newlinethat was infused in the knowledge the customer accessed, is anything but real! newlineIn broader sense what we research as CKM in this thesis is the overarching newlineconcept of customer experience (CX) in classical marketing studies. In which, CX has newlineemerged as a significant differentiator for businesses in the realm of customer newlineacquisition, retention, and delightful advocacy. Buoyed by recent advancements in newlinebigdata, smart use of data science has unlocked plethora opportunities for businesses to newlineunderstand and thereby manage customers experience across array of touchpoints they newlineinteract with along the customer journey. CKM is at the intersection of ingenious use of newlineData Science and the diligent acquisition of customers touchpoint data, including newlineinconspicuous yet clever mining of customer feedback. newlineOur review of literatures reveals the significant studies conducted in these two newlineareas i.e., CKM and Bigdata including its supporting tools and techniques, but done newlineindependently and in isolation. Coalescing these two very powerful concepts, casts the newlinefoundation stone to our research for their very obvious complementary nature i.e. Data newlineScience fuels CKM and Data Science is inconsequential without transforming Data into newlineknowledge! newlineTo maintain sanctity to the exploratory nature of our research, we have been newlineunassuming of any opportunity that may exist to address impro