The Corvus | August 2018
history of everything you ’ ve bought from their store ( online and offline ). In some cases , they can acquire more data about you from other sources to get a better idea of your persona , interests , wants and needs . Then the retailer proceeds to use the aggregated data / information about you to predict your likely shopping needs and their prediction are mostly correct .
Let ’ s take Amazon for instance . Amazon is an e-commerce giant that sells everything . Every time you go on the site it feels like a visit to your neighborhood petty trader who knows your name and your frequent purchases . However , in the case of Amazon , they use the data of your recent purchases and searches to recommend related products and discount deals as well as additional items for your purchase consideration right there on your homepage .
With Cognitive commerce , retailers gather data on each customer to understand them within the context of a particular situation , analyze the data and applies machine learning to make recommendations for future purchases based on the customer ’ s historic activities on their platform .
This capability is available now and has shown great results in real-world testing thus , it is not entirely futuristic . In 2012 , Target - the second largest discount retail store in the United States - decoded a teenage girl was pregnant before her father did . The store had come up with a formula about the clues to a shopper ’ s impending bundle of joy with the aid of cognitive solutions . Chief Statistician of Target , Andrew Pole and his associates were able to identify 25 products that , when analyzed together , allowed them to assign a “ pregnancy prediction ” score to each shopper . These products didn ’ t involve the usual tell-tale baby items like car seats and breast pumps but seemingly harmless products including unscented lotions , hand sanitizers and multivitamins .
The objective of cognitive systems as a whole is to help people make better
decisions . And this is why it is gaining more traction and popularity in the marketplace as it accurately gets up close and personal with customers . For retailers and companies who use cognitive commerce , prices optimize themselves , products sell through at higher speed with lower stock out and customer service is revolutionized into becoming more proactive than reactive .
With Cognitive Commerce , the landing page of each customer ’ s favourite e-commerce site contain the brands they use frequently first , as well as options of other brands that might also be of interest to them . Each customer receives information of products , discounts and offers that they are actually interested in as they are tailored just for them .
Cognitive Commerce is like a fast sports car that can hit 100km / h in 2secs , sleek as a fox but without fuel that beast can ’ t move an inch . The fuel that feeds cognitive commerce is data , without analyzed data there would be no cognitive commerce .
Data has been called the world ’ s most valuable resource overtaking oil and gold , but many companies are yet to fully utilize the data they ’ re sitting on . Digital-savvy customers , have certain expectations from companies . For one , customers don ’ t expect to start the same conversation over and over again with their favourite retailer , once they start a conversation from a physical outlet , they expect that when they go online , the retailer recognizes that it is the same person that initiated the correspondence offline and continue from where the correspondence stopped . Putting data to proper use helps to connect with customers in a variety of ways , across multiple devices and channels which will in turn build relationships that go beyond sales with customers thus , delivering a complete end-to-end experience . Brands that fail to keep up with customer expectations and provide these experiences might find themselves struggling for market share and relevance .
The trick here as stated by Steve Gatto of Perficient Digital is to “ think of all the data you need – stored data , online data , CRM data , etc . All of this data sits in other repositories , and it ’ s awfully difficult to bring it together , analyze and use the insights to deliver relevancy in the moment ,” he said . “ But if you have cognitive solutions to take in and analyze this data , from an omni-channel perspective , you can understand how customers are engaging with all of your touch points , and maybe even predict some of the things that they need
How Cognitive Makes Everyone ' s Life Easier 30