Problem Statement: Optimizing Call Scheduling Based on Time-Of-Day and Demographic Insights

In a contact center environment, the success of outbound calls in terms of member reach and assessment rates is crucial for operational efficiency and member satisfaction. However, the optimal timing for these calls in relation to member demographics and other factors is not always clear. This challenge seeks to unravel the intricate patterns of member availability and receptiveness to calls at different times of day and days of the week.

Participants will analyze historical call data with the goal of determining:

·       The most effective time slots for placing calls to members, ranked by hour or half-hour segments.

·       The correlation between hit rates and call times, identifying potential gaps in call scheduling.

·       The impact of dialing at varied times and days on success rates, incorporating open-source data for broader insights.

·       The possibility of presenting this data in an iterative format suitable for decision-making processes.

 

Key Considerations:

 

·       Analysis of reach and successful routing rates by time of day, employing data segmentation tools.

·       Exploration of factors leading to unsuccessful attempts, focusing on timing patterns.

·       Examination of patterns in unsuccessful repeated attempts, supported by qualitative call recording analysis.

 

Data Inputs:

 

·        Member demographic information

·        Insurance coverage types

·        Historical call outcomes (e.g., contact achieved, routed, assessment completed)

·        Timing of calls

 

Get the Data from here: https://drive.google.com/drive/folders/1J53U7HGv--0LOO5q9od8_8sSJlAPkTTz?usp=sharing

 

Participants are encouraged to preprocess the data to remove anomalies and explore the correlation between call attempts and success rates.

Requirements

Desired Outcomes:

·       A predictive model or tool for recommending the best calling times based on member specifics.

·       A strategic framework for scheduling calls to enhance outbound call success rates.

·       An ongoing data analysis methodology for real-time decision-making support within the contact center.

 

Key Calculations for Routine Analysis:

Outcome Definitions:

·        Various outcomes for reached and routed calls, including successful contacts and different reasons for unsuccessful attempts.

Analysis Dimensions:

·       Comparison of reached and routed rates, incorporating demographic and lead-specific filters.

·       Visualization and data extraction options, including success metrics and demographic details, with potential future integration of assessment success rates.

Additional Challenges:

·       Analysis of contact success at specific call attempts, using frequency distribution and other data segmentation tools.

·       Investigation into the timing of unsuccessful initial attempts, offering insights into optimal timing strategies.

Hackathon Sponsors

Prizes

$1,000 in prizes
Cash and Swags
1 winner

The top participants will receive a cash prize and swags of up to 1000 dollars. Swags are from Ground Game Health and Tableau as they are our sponsors.

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

Amogh Bhaskara

Amogh Bhaskara
Software Engineer at Ground Game Health

SUBBARAO P

SUBBARAO P
Senior data architect at Teradyne

Sushil Banubakode

Sushil Banubakode
Vice President at Nobl Q

Sameer Ranjan

Sameer Ranjan
CTO at Catenate

Judging Criteria

  • Judging Criteria
    You will be judged upon both the presentation and the code and insights you have submitted. If you have any doubts in judging criteria, please reach out to any of our team members and we will be happy to assist you.

Questions? Email the hackathon manager

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