In (Ansari et al., 2000). This technique

In the first stage of the decision making process known as the problem recognition, the customer sees a gap between what he/she has and what he/she wants. Companies can sense this moment from a variety of sources such as social media, search queries, addressable advertising (Blattberg and Deighton, 1991) and direct marketing response. Qualitative research methods such as interviews and focus groups can be used to recognise problems and improved by Big Data.
Information search throws off digital data at every turn. Retailers can record all search activities on its website and shopping app such as logs recording all activities on the site, including which items have been searched, clicked on, added to a shopping cart or wish list, abandoned, purchased, etc. It also knows which search terms attracted prospective customers from search engines, and whether it was a paid search term or an organic one.
E-tailers will have data on alternative evaluations including consideration and inferred choices. Big Data can be utilised as input, including the choices of other shoppers (Ansari et al., 2000). This technique is collaborative filtering. Shopping cart abandonment (Kukar-Kinney and Close, 2010) can signal that customers are comparing prices on other sites. Search behaviour in general can provide additional hints on the way the consumer is planning to evaluate the alternatives.
Purchase behavior
We now have detailed digital records of what happens in many different types of purchase environments. Data sources include cameras in stores, mobile purchase activities on branded apps, scanners at checkout, direct marketing purchase responses online, online browsing and shopping carts, loyalty programs,and digital TV, among others.
Post-purchase evaluation
Consumers evaluate the gap between their expectations and their consumption experience during and after consumption. This step known as post purchase behaviour by itself does not create Big Data but positive or negative gaps may be described online in reviews, tweets, shared photos, etc. We also wonder whether traditional post-purchase evaluation measures of satisfaction, commitment and attitudinal loyalty will be as relevant or necessary when the firm can monitor every interaction.


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