Recommendations in
e-Commerce
By Bhoomika Narwani, FE IT
“We are leaving the age of information and entering the age of recommendation”
- Chris Anderson
Looking at the present scenario the above quote by Mr. Anderson is an apt description
of it. In this busy world of ours e-Commerce as emerged as a boon, just a click away and your
desired commodity will be there at your doorstep. With such a sudden boost, consumers are
provided with enormous number of options to choose from which leads us to think about the
importance of recommendations. Recommendations help consumers to buy the required
commodity according to his requirements and also in some cases saves the buyer from being
cheated. Looking on the other side it seems pretty clear that companies can increase their
consumer base with the help of these recommendations. Recommendations can act as value
added advertisement for the company in the following manner:
1. “Conversion”: Turning Browsers into Buyers is what the seller desires. Recommendations
incline you towards the product and the consumer ends up buying it even if it wasn’t planned.
2. By increasing Cross-sell Recommender systems improve cross selling by suggesting
additional products or services to customers. If the recommendations are good, the average
order size increases. For instance, a site might recommend additional products in the checkout
process, based on those products already in the shopping cart.
3. By building loyalty: Building customer-loyalty becomes an essential aspect of business
strategy. Recommender systems can improve loyalty by creating a value-added relationship
between the site and the customer. If the product is satisfactory it will catch the eyes of the
customer and when he looks for something else next time he will end up buying it from the very
same seller.
Advancing on this line of thought Recommendation System is further classified in two categories
1.
Content-based recommendations: These are basic recommendations based on the
description of an item. In such kind of system there are three crucial aspects of it ‘the matcher’,
‘the item description’ and ‘the user profile’. It is important for the seller to ensure that the buyer
receives proper advice to fulfil his requirement.
2.
Collaborative filtering systems: Collaborative Filtering systems make recommendations
exclusively based on knowledge of users’ relationships to items. These techniques require no
knowledge of the properties of the item themselves. This type of system extensively focusses