We understand customer behavior and stop delusional; thus, we prioritize our team members to close the deal before considering alternative channels.
Table of Content
About the Business
Business details : Ozone by Bankhaokho is a tourist resort business in Khao Kho District, Phetchabun Province, Thailand.
Objective : To find out which types of customers are most likely to cancel their accommodations and recommend other popular trends from customers insights.
Executive Summary
Lead time is essential for canceling customers, and direct sales generate more profit than other channels. Thus, we prioritize our team members’ closing the deal before considering alternative channels.
Result of 3 business pillars
Profitability increase by 25% | Customer satisfaction increased by 19% | Business Growth by 3% |
Getting Start
Note : This Impact Study is Dithanon's data - The same owner with Power Ladder - So this can reveal some detail for examples.
First, We've considered that this business doesn't need to use Big Data. Only data from Channel Manager is sufficient for analytics.
The Important thing is The way to solve business by using the appropriated resource.
Our team has collected accommodation booking data, which provided in Google Sheet format as raw material for Data Science. Once the data has been analyzed, There are two interesting points in this matter.
1. Understand customer behavior through data, and as a business owner, Just play along with the game, without trying to influence or pressure the customers to act in a certain way.
From the picture, you can see that the more Lead Time(Number of days between the date of booking and the arrival date), the more time the customer has to book. The higher the chance of requesting a cancellation, the better. How does this help me make business decisions?
Based on the provided information, I am now better prepared to manage customer service and develop effective marketing strategies. When understanding customer behavior, customers often book and then actually stay within a short period of time. That means that if I want customers to come and reserve accommodation between April 13 and 15, which is the Songkran long holiday or Thai New Year. That means The marketing team should advertise nine days in advance (from the median value, which is a solid line running through the middle, not the 21 days in the dotted line) so that customers decide to book and not cancel their reservations before then.
2. Stop delusional. You may be easily deceived if you don't have Predictive Business.
This is the proportion of channels for booking resort accommodation with us. From the picture, you can see that Agoda is the channel with the highest proportion of bookings (37.7%). If I look at the data here, I will probably decide to focus on booking accommodations through Agoda. Is that true? But if compared with the other side of the data, does that show how much a customer paid at one time?
From the graph, it can be seen that Wee(one of reservation staffs) has the ability to generate the most profitable bookings for our resorts.
How does this help me make business decisions
I prioritize our team members to close the deal before considering alternative channels. Before using other channels as alternatives.
Note: Booking accommodation through Agoda or other Online Travel Agencies (OTAs) is not inherently negative. This is simply one aspect of information within my own resort. Our resort generates revenue not only through accommodation fees but also through additional sales such as food and catering services. Each company has a unique business model, leading to differences in Predictive Business outcomes.
Another example of data visualization is the transformation into predictive business through the utilization of AI in the machine learning process, typically represented in the form of a decision tree.
For every Predictive Business project leveraging Data Science by the Power Ladder team, we not only provide Data Visualization but also guidance from a Business Analytics Consultant throughout the four-month duration of the project to help you analyze and explain technical data science terms to ensure understanding during the analysis process.
And these are Data Scientists, who will take care of this project for you.
We would like to know more about your business.
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