Customer Personalization is the art to perfect as far as the modern day retailers are concerned. The advent of deep learning algorithms from the tech giants has ensured that big data is being used more than ever before to power customer insight into retail. But predictive analytics has been in use since decades. It's the phenomenon known as 'Artificial Intelligence' that has enhanced the speed, scale and effectivity in the way predictive analytics is being used to attain top notch personalization among customers. After all it's not just about enhancing the customer shopping experience. It's about doing it with a great degree of differentiation and effectiveness.
Innovation through AI is what is helping retailers advance their business. There is more than one way in which AI is being put to use today.
One of the more convenient form of use of AI is via automation. Product recommendations can be taken care of by computers and machines without the need of human intervention. This can be enabled due to machine learning. The automated systems can self sufficiently recommend products by correctly interpreting digital user reviews and past purchase history.
With the minimum of effort, retailers can experience a rise in customer engagement and drive sales due to the implementation of algorithms like collaborative filtering. This point is validated by Paul Marques, CTO at Feedzal, who has witnessed the firsthand impact of AI on the retail clients as his company registers over $2 billion in transactions per day with the use of machine learning.
Super-Personalization due to Segmentation
Retailers today look to go the extra mile. It's one thing attending to a cluster of customers. It's completely something else when you attend to each one in the cluster. The standard search and filtering tools commonly deployed by retailers can sometimes prove to be ineffective and unpenetrative. The segmented approach allows retailers to target and cater to the needs of each customer exclusively with the help of micro-segments. This helps in converting visitors into high value and long term customers.
The North Face is one brand who was an early acknowledger of this fact and has resorted to this method. They demonstrated its use by working with a tool called the Fluid Expert Personal Shopper (XPS) which is powered by IBM's Watson cognitive computing technology. The XPS Solution makes use of the natural language capability and asks the customer a series of intelligent questions. The answers become a part of the data to be analysed which helps determine the ideal product to be recommended to the customer based on his specific purpose.
Real Time Personalization
Back in the days, data analysis was very much a part of retail. But product offerings and recommendations were made after days, sometimes weeks later. Today, machine learning systems have become advanced and stream live data and as a result help in curating products in real time. The adherence to mobile geo-location technology is allowing retailers to track the customers live when they are in-store or around. As a result, offers, promotions and discount codes can be sent to their mobiles in real time during their presence in the form of notifications.
There exist a lot of choices for retailers in the way they would want to make use of Artificial Intelligence. With consumers continuously seeking a rich retail experience, the sooner retailers come to terms with AI and its' fundamentals, the quicker they will be able to reap profits.