Which Customers are leaving the company and what causes them to go? How much does the company need to invest to prevent customers to quit? Is it worth to invest money in retaining customers?
Customer Engagement Management is in the end all about maintaining profitable as a company and preventing customer churn. In order to prevent customers of leaving the company it is vital to analyze the customer- company relationship. Here, retention analysis becomes substantial for every type of company whether it is product or service driven. It helps the company to become aware “of those customers who demonstrate an increased likelihood of ending the relationship, then it can take action to prevent this” (Peelen & Beltman, 2013).
In general the first step towards a successful retention analysis is to have qualitative, historical data of customer transactions and patterns. Therefore every interaction with the customer should be noted in detail to be able to recognize when a customer is likely to churn the company. In service based businesses like a Destination Management Organization (DMO) it is not easy to find out when a customer has quit the relationship with the company. (Lehman, 2015) The interactions, like purchasing a holiday package are not done every month but rather every 6 to 12 months. Therefore it is hard to identify if a customer really left the company or is just attrite and didn’t book for a long time due to other circumstances. To be able to analyze the client behavior it is essential to keep track “of every email, tweet, link, click, and phone call made to that client.” (Lehman, 2015).
To undertake the retention analysis to its fullest, the obtained historical data needs to be put in a successful model. Therefore the data needs to be divided into 50% of former customers and 50% of current customers to have a predictable sample. Then the 50:50 data should again be divided in half in order that one set will be the training set and the other half will be the validation set. The assumptions which are made with the training set can be compared to the validation set to actually see which customers are likely to withdraw from the company. In order to do so, interest variables need to be checked as well. Interest variables for a DMO could be: purchase (time, frequency, monetary), email contact, log-in on website, open website or social media and direct contact via phone. (Peelen & Beltman, 2013)
When it is clear which customers have quit or are about to quit the company could react to those clients. The company could send personalized messages or call the customer based on their behavioral history with the company. The DMO could send a person who usually travels to London every Christmas a booking reminder in autumn. The client usually books every year in summer so autumn would be a good time for a reminder. To be more convincing this message should include the general dates which have usually been booked by the customers. As an advantage the company could then use the hotel preference to introduce the customer to a new, maybe even more luxurious hotel than the one which has been booked every year. Reviews or discounts of partners could be included to underline the importance of the customer to the company.
“Many business owners know their acquisition rate, because getting new customers is fun. Relatively few know their attrition rate; losing customers is no fun.” – Jeff Haden (Beard, 2013)
Why is customer retention so important you might ask. One of the most important reasons is effort and money. It would cost the DMO a lot more money to acquire a new customer than to stick to a loyal customer. (Beard, 2013) (Peelen & Beltman, 2013) Therefore it is very important to undertake a successful Retention analysis to convince customers to stick with your company.
Beard, R. (2013, October). Customer Retention Rate Explained for Dummies. (C. Heartbeat, Editor) Retrieved 2015, from http://blog.clientheartbeat.com/customer-retention-rate/
Lehman, T. (2015). How to define retention rate for customer retention. (N. North, Editor) Retrieved October 2015, from http://www.newnorth.com/how-to-calculate-metrics-for-customer-retention/
Peelen, E., & Beltman, R. (2013). Customer Relationship Management. Pearson.