We are living in a digital era where Customer is the king. Many businesses have capitulated to this new realm and have started interacting with customers dynamically. Today the customers are free to navigate a merchant (eCommerce) website any way they fancy. Also the merchant can display content and place offers dynamically based on how a given customer interacts with his website. To add to the complexity purchase decisions are not necessarily made on the first visit itself. Internet savvy customers now have all the information at their fingertips to land themselves the best deal.
When contemplating a purchase Customers go through something which marketers call the AIDA journey:-
- A: Attention/Awareness – attract the attention of the customer
- I: Interest of the customer
- D: Desire – convince customers that they want and desire the product or service and that it will satisfy their needs
- A: Action – lead customers towards purchase
In most scenario customer’s site navigation on the day of the purchase is mere execution of a decision that has been made even before the customer lands on the site – the customer has been on the site before; the customer is aware of what is on offer; the customer knows exactly how to get to the page on the site where they can choose the product they desire. In fact, the pages visited on the day of the purchase are often not causal to the purchase, just simply correlated.[quote]Dealing with a customer through digital media, the focus of predictive analytics has shifted from prediction to classification[/quote]
In the digital world the focus is dramatically shifting from prediction to classification. The selling and buying is now all happening in a real-time environment where the two players are interacting with each other, and repeatedly. The merchant has the leverage to influence the customer’s behavior through customized offers based on behavioral segmentation and contextual targeting. All the merchant wants to understand is ‘who the customer’ is and that will determine what offer to place. Since the customers are now visiting the merchant’s site several times the independence of each visit/record ceases to exist – a mortal blow to the much beloved logistic regression?
In comes Machine Learning – an elixir for new world technology.
The world of analytics is now talking about Support Vector Machine (SVM), Naïve bayes, expectation maximization using naïve bayes, random forest, bagged regressions et al. – everything is about classification; everything is about adaptively learning and self-evolving algorithms that augment the understanding of the customer with every successive digital footprint.
This paradigm shift has drastically changed the ‘skills’ requirement in job descriptions as well: when screening candidates, employers are now specifically looking for ‘Python, R and machine learning’, as against ‘SAS, regression, optimization.’.
Another advocacy for Machine Learning is in the investment made and innovative projects assumed at top tech companies of the world. Starting from IBM’s big bet on Watson to Microsoft’s increased focus on Cortana and recent product launches and acquisitions from Amazon to Apple; all suggest machine learning’s rising importance. Self-driving cars are the next frontier as applications move beyond the technology industry.
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A customer experience evangelist, I help companies identify and make the best use of their key performance indicators and generate insights to improve their customer experience. I have two years of analytics consulting experience with Fortune 500 global firms across industries to monetize value from Analytics by analyzing information, deriving actionable insights and delivering sustained impact through operationalization of Analytics.