Customer Relationship Management Through Loyalty

Posted in Marketing & Strategy Articles, Total Reads: 1030 , Published on 15 November 2016
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Do you like to visit our restaurant every day? Voila! Enjoy a free overnight stay at our luxurious hotel! Or do you order a pizza every month? Get a 20% off on your next pizza (offer valid only for three weeks). Customer relationship is not just about treating the customer nicely but retaining the customer over lifetime and holding his loyalty. This is gained by providing him with incentives to continue being a customer. But how do we decide what incentive to give?


Harrah’s casino chain is one of the largest in the world and witnesses great influx of customers. But even they were faced with a time when the customer inflow reduced and it led to drastic decrease in revenue. There rose an urgent need to rectify this and increase revenue, mostly by retaining customers. Were the customers not feeling the same adrenaline rush like before? The major problem was that after continuously losing, customers moved on to the next casinos to try their luck.


Image: pixabay


This situation was saved by Gary Loveman, a Harvard professor, who took the position of Chief operating officer of Harrah’s in 1998. They had around 20 million customers to take care of. He ensured that every customer held an encoded card which had to be inserted in the slot before they played their luck. Players collected points and rewards for gambling, and Harrah’s collected information about gamers’ preferences. This frequent gambler program was called Total Rewards. It took all the information from what, how and when. It recorded how frequent the customer was, how much money he used in playing, how many times he won or lost, on what days did he visit and so on. All this data was send to a common network that gave analyzed results which led to coming up with innovative marketing strategies. Diverse tactics were applied on different type of customers then, for example out of all the beats one person visited on, it was guaranteed that he won at least once, so that the motivation to play continued. As a consequence of using these systems the profitability of Harrah’s increased by 20%.


The magic behind all these kind of analysis are Recommender systems. These are the tools that can not only make life easy but also provide solutions. They can bring out the meaning from large unstructured data and give useful suggestions without getting us involved in plethora of information. The most important thing is that they are and can be used in almost every arena from where one can get any kind of data; from ants to oceans. The recommender systems thus tell us to use resources effectively and put energy in the right direction. They help in providing better customer service through customization and targeting customers with suitable campaigns hence increasing profitability. They communicate to a company what to do for which type of customer. They are already being used in a number of companies especially all e-commerce websites, to keep a track of customer habits. And these recommender systems are getting more cutting-edge each day with the advent of technology. In general, there are three primary categories of recommender systems, namely, collaborative filtering, content-based filtering and hybrid recommender systems. Collaborative filtering methods are based on predicting what users will like depending on their similarity to other users and the ratings provider by those users. Content-based filtering methods are based on description of the item and a profile of the user’s preference. In other words, this method recommends items based on the items that the user has liked in the past. A hybrid recommender system on the other hand, combines both the above mentioned approaches in order to reduce their disadvantages and exploit their benefits.


A person who regularly visits Amazon and buys around eight to ten books every month is given a normal Margin retail price or less discount as compared to a person who rarely does the same. All this “what is to be shown” is automatically generated and recommender systems are making it vigorous. A person who orders a pizza every month can be given a coupon valid for three weeks only; it will motivate him to buy one more pizza that month. These kind of strategies help companies built customer frequency. There can be numerous examples from the current world, say in suggesting friends, marriage partners, a hotel to stay in, places to visit, airlines, books, furniture, clothing and what not.


This proves the importance of recommender systems for businesses. Companies have to cope up with technology to beat the competition. As long as companies emphasis on their business strategies by using their people, right customer relationship methods and most of all the veracious technology it will definitely give the businesses great profitability.

 

This article is authored by Akanksha Rajput from IIM Raipur


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