Recommendation systems

Marketing Recommender Systems: A New Approach in Digital Economy

Marketing information systems are those systems which make the gathering, processing, selection, storage, transmission and display of coordinated and continuous internal and external information. Includes systematic and formal methods used for managing all of an organisation's information market. Recommendation systems are those systems that are widely used in online systems to suggest items that users might find interesting.

Recommender systems are able to predict users’ preferences and items of interest, by analysing historical data on their behaviour and actions. Different techniques exist and are applicable in different scenarios. This thesis explores how to combine Content-Based and Collaborative-Filtering techniques in a hybrid system and how personalised recommendations and one-to-one marketing techniques can lead to an improvement in user engagement. Specifically, it is analysed the case of online platforms where there is no rating system in place. Results are empirically tested and evaluated with training/testing approach and recommendations seem to be quite accurate. However, further online evaluation is needed to measure any actual increase in user engagement.

How are Recommender Systems Changing the Consumer Marketing World?

Posted on September 20, 2018

Recommender systems are one of the latest additions to the long list of marketing ploys made available by technology. These are basically algorithms which provide the consumer recommendations for products that are similar to their choices. Recommendation systems are widely used by websites such as Netflix or Amazon, and they have a huge impact on the consumer sales. Here are some of the ways that recommender systems are changing the various trends in consumer marketing:

Discovery

The first step towards a consumer buying a certain product is the consumer finding out about it. In case of online products, this happens via search and if the description of the product contains the keywords of the search, it will appear in the results and will be placed in the list as per its popularity. However, with the introduction of recommender systems, it is seen that this model of placing keywords within the description has turned redundant and most people are going from one product to another through the process of recommendation tabs within the website.

Product Bundles

The goal is no longer to guess what a consumer wants to buy, but rather what could they want to buy next. If someone has just bought a pair of shoes, a recommender system will not only show them other shoes, but also a pair of socks and shoe polish. So, through the use of recommender systems the chances of selling products that are supplementary to the initial product are made possible, and thus the marketing ploy turns to place products as bundles, all linked with one another.

A Much Bigger Choice

Before the introduction of recommender systems across various websites, consumers had to search for each product separately and go through the list to find what they needed. If a customer searched for shoes they would be shown a list of shoes from where they would pick one. But with recommender systems in place, they can select a shoe and they would automatically be shown another list of shoes which are similar in branding or style to this shoe. This second list would in all probability be absolutely different from the first list presented to the customer and thus the number of choices presented to the consumer is increased manifold.