DATA ANALYTICS

BUSINESS CHALLENGE

Dear students,

In light of COVID-19, PSA unboXed Data Analytics Business Challenge will be tentatively changed to an online platform.

It will now be comprised of virtual mentorship instead. Note that the prize presentation would still be physical, as arranged by PSA.

Do stay safe in light of the virus and good luck for the challenge!

Win up to 6k worth of cash prizes !!!

Analyse a set of data 
Discover insights to redefine customers' digital experience on PORTNET®

Analytics Scope

PORTNET® is the first nation-wide business-to-business (B2B) port community solution that empowers the shipping community to easily manage the complexity of cargo operations and the entire shipping process.

It seamlessly handles all electronic vessel and container data passing through PSA Singapore Terminals, the world's largest transhipment hub. Beyond that, its automated system intelligently consolidates and synchronises the transactions and information from every player in the logistics process for an efficient and reliable supply chain.

There are more than 10,000 users, covering various sub-communities. The Haulage Community uses Portnet to achieve the following benefits:

  •  Automates the Haulage Workflow from job orders to job fulfilment and tracking of incentive payments to drivers

  •  Improves efficiency for port documentation submissions and job deployment to drivers

  •  Holistic view of all trucking activities scheduled for each truck

  •  Instantaneous and round-the-clock access for haulage operations anywhere

  •  Enhanced business visibility with timely operational reports

We are seeking insights from customer journey analytics to better profile our users through the understanding of their transactional patterns and preferences. This in turn enables us to anticipate their evolving needs and identify areas of improvement for the haulage community to make an informed decision – to deliver more value-add services, improve our business or enhance customer experiences with the haulage community.

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Teams will be furnished with various datasets containing various types of transactions, and will require mining of the following information: ​

 

(1) Rank the frequency of the transaction sequences* (user-path)

-Outcome: to improve understanding of our user needs.

(2)  Using timestamp data, rank the most common consecutive transactions where the time gap between the first click of each transaction is within 10 mins.

-Outcome: to identify which transactions can be completed in one setting and reduce users’ turnaround time spent on the portal

(3) Identify and rank the transactions that are aborted with user having to repeat the transaction again

-Outcome: to understand if the user interface of the particular transaction system needs to be improved

(4) Based on no. of transactions, rank the hourly timings where the portal is most utilised. For each hourly timing, rank the frequency of the transactions that are submitted.

- Outcome: To understand the peak hours of the portal as well as the needs of the user during their peak hours

 

(5) Based on Company ID, identify and rank the most common transactions

-Outcome: to find cross-selling and up-selling opportunities

(6) Based on geographical location (using IP) of the User, identify their preference to mobile and web portal.

-Outcome: To understand which communication channel is more effective to different users and different regions to ensure better outreach

(7) Effects of COVID'19 on Usage Patterns

-Outcome: To understand if there are any changes in user behavior patterns with the recent outbreak

*Transaction Sequence are defined as a series of transactions made by One Single User within A DAY.

 

Expected deliverables from the teams:

  • Insights on customer journeys and usage behaviour on the platform based on patterns of transaction sequences and the user profile

  • Actionable insights on improving customer experience by identifying bottlenecks and recommend areas of improvement

 

Evaluation Criteria

  • Quantity and Quality of insights

  • Use of data tools for visualization and other analytics aspects like modeling

  • Ideas/Proposals for enhancing user experiences

  • Overall Presentation of Reporting (Clarity, Effectiveness of communications, visualizations)

Sample Data

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