Sigma-Thon 1.0

2701 Registered Allowed team size: 1 - 4
2701 Registered Allowed team size: 1 - 4

Winners are announced.

hackathon
Online
starts on:
Jun 12, 2020, 02:30 PM ()
ends on:
Jul 12, 2020, 06:25 PM ()

Winners

Overview

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Then you're in the right place: HackerEarth presents the first edition of Sigma-Thon 1.0. Join the hackathon and be a part of the data enthusiasts community.

Data Hackathons are an ultimate battleground for aspiring data scientists. Organizations are on a constant lookout for discovering meaningful patterns and insights, to deliver the right products at the right time. Retail is one such industry that is pivoting towards experience-led consumption of goods and services with shoppers and associates taking centerstage.

We are interested in hearing about your next disruptive idea that not only focuses on next-gen experiences but also brings together an ecosystem of enablers to make it a reality.

Put your skills to the test on a new and exciting project. Build a data-driven solution for retailers to innovate their retail channels with data models, recommendation engines, and much more. Grow your appetite for data-based solutions exponentially!

Who can participate in this hackathon?

NOT just coders! Anyone, who is passionate about Data can be part of it! Whether you are a beginner, an expert, or a student, you are welcome to join the Data enthusiast community of innovators and create a solution using YOUR skills!

How can you participate in this hackathon?

  • Register and form a team
  • Attend the webinar about Data Science, ML, and AI
  • Projects are submitted to the hackathon platform
  • Win exciting prizes

Themes

AI has transformed the retail industry by enabling commerce to be not only intelligent but by being behaviorally dynamic and adaptive to each user. Creating an exciting customer experience is only possible with adequate insights driven from customer behavioral data. Higher the granularity of data, better is the visibility into a user’s behavior and better insights can be drawn to educate retailers on leading factors for a heavily personalized customer experience. In turn, the scale of data collected, however, is huge.

Build a data-driven solution for the retailers to innovate their retail channels aiding them with supply chain, pricing & promotion management and planning.

Personalized Experience
Sub-Themes
Fashion
Telecom
FMCG
Delivery

Consumer behavior and preference monitored through repeated interactions in a marketplace can be analyzed to develop a detailed shopper profile, utilize this information to deliver proactive and personalized outbound marketing — tailored recommendations, rewards, or content.

  • You need to submit a solution based on user behavior analysis associated with a personalized recommendation logic
  • Good-to-have: Propose data modeling solutions for the corresponding industry to handle user behavioral data at large scale
  • Demand Forecasting
    Sub-Themes
    Fashion
    Telecom
    FMCG
    Delivery

    Create better demand forecasting by mining insights from the marketplace, consumer, and competitor data. You need to forecast shifts in industries and make proactive changes to a company’s marketing, merchandising, and business strategies under a given domain. Share analysis results showcasing the impact on supply chain planning, pricing and/or promotional planning.

  • You need to build an analytical solution and include a presentation containing your analysis and insights.
  • Good-to-have: Propose strategic solutions based on your analysis
  • Operational Optimization
    Sub-Themes
    Fashion
    Telecom
    FMCG
    Delivery

    AI-supported logistics management systems can adjust a retailer’s inventory, staffing, distribution, and delivery schemes in real-time to create the most efficient supply and fulfillment chains while meeting customers’ expectations for high-quality, immediate access and support.

  • Develop a data-driven solution that empowers retailers to revamp their traditional supply chain in favor of adaptive and flexible ecosystems that are highly responsive to shifts in customer behavior.
  • Good-to-have: Propose data architecture for corresponding industry.
  • Prizes USD 325 in prizes

    Main Prizes
    1st Prize Winner
    USD 150
    2nd Prize Winner
    USD 100
    3rd Prize Winner
    USD 75

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