SEA OIC

#Travel
#PredictiveAnalytics

How might we predict the most popular travel and hospitality products amongst affluent Vietnamese travellers in a more timely, effective and efficient manner?

Background/Context

Since its beginnings as a boutique adventure tour operator in 1994, Thiên Minh Group (TMG) has become a leader in hospitality, aviation and holiday experience, and now owns a collection of brands in these areas.

As a leading provider of end-to-end travel and hospitality services, TMG managers constantly make decisions on what to prioritise in their marketing efforts amongst over 100 products (hotel or resort rooms, airline seats, tours, or a combination).

At present, this decision-making is based on sales history and the managers’ experience in interpreting the data. TMG wants to gain more insights -- drawing from the latest socio-economic conditions and aided by automated analyses of sales data-- and have the capability to forecast or gauge market demand.

Objective

How might we predict the most popular travel and hospitality products amongst affluent Vietnamese travellers in a more timely, effective and efficient manner?

The focus here are “mass affluent” (defined as XXX) and “emerging affluent” (defined as XXX).

Solution

TMG is looking for a business intelligence tool that can:

Produce actionable insights on a fortnightly or monthly basis
Monitor real-time demand and traction for travel products
Integrated with SQL server and have .NET framework compatibility

The pilot should demonstrate real-time results that the full solution would. Ultimately, the solution will enable dynamic pricing, prioritisation in marketing activities and budget allocation, and the creation of promotional packages with suppliers (hotels, resorts and/or airlines).

View Other Participating Demand Drivers Challenge Statements

#Travel#Chatbot

How might we improve the chatbot to better interact with and understand the customer, and offer a better experience?

Background/Context

Thiên Minh Group (TMG) endeavours to ensure every step of their guests’ journey is simple and convenient, starting with their information-gathering and booking stages.

The present chatbot solution (“Olivia” on ivivu.com) can collect the information from the potential customer, offer relevant products, take the order and payment. It is challenging to maintain and add new features. The current lack of Natural Language Processing means TMG is not learning to understand the customer deeply and to respond appropriately.

Objective

How might we improve the chatbot to better interact with and understand the customer, and offer a better experience?

Solution

TMG is looking for a full-integrated chatbot solution that:

Fulfills all data gathering requirements: age, location, experience, web activity, product rating, product specification, etc.
Has good NLP capabilities specific to Vietnamese and English languages
Can understand Vietnamese context well

With a better chatbot that gives customers a better experience, TMG has a more friendly and effective 24/7 sales channel for their products.

View Other Participating Demand Drivers Challenge Statements

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