The Fifth Elephant round the year submissions for 2019

Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering

Building a Location Intelligence Platform for audience segmentation

Submitted by Sanjoy Bose (@sanjoybsahaj) on Jun 18, 2019

Session type: Short talk of 20 mins Status: Rejected


The ROI of OOH (Out of Home Advertisement) depends on precise and intelligent targeting of advertisements. The media buyers therefore require detailed understanding and visibility of the audiences across various attributes so that they can then plan their OOH media buy to specifically target a selected set of audiences. Location information of the user, device level audience data, enriched with real world locations and moments provide a rich source of information about audience behaviours and interests. This data can be used to generate insights of granular and niche audience segments about visits, interests, journeys etc. Using these information about the audience, the platform helps in taking smart campaign buy decision to have better audience targeting and outcome.


Problem Definition and Context
What is Location Intelligence and Why ?
Identify the data requirements and data provider
Challenges with the quality of data
Designing the audience segments and audience explorer
DataScience models for Inferences
Designing the data pipeline and workflow
Breaking down the pipeline responsibility for parallel development
Making the data available in a data warehouse
Building the analytics pipeline

Speaker bio


  • Abhishek Balaji (@booleanbalaji) a year ago

    Hi Sanjoy,

    Thank you for submitting a proposal. We need to see detailed slides and a preview video to evaluate your proposal. Your slides must cover the following:

    • Problem statement/context, which the audience can relate to and understand. The problem statement has to be a problem (based on this context) that can be generalized for all.
    • What were the tools/frameworks available in the market to solve this problem? How did you evaluate these, and what metrics did you use for the evaluation? Why did you pick the option that you did?
    • Explain how the situation was before the solution you picked/built and how it changed after implementing the solution you picked and built? Show before-after scenario comparisons & metrics.
    • What compromises/trade-offs did you have to make in this process?
    • What is the one takeaway that you want participants to go back with at the end of this talk? What is it that participants should learn/be cautious about when solving similar problems?

    We need your updated slides and preview video by Jun 28, 2019 to evaluate your proposal. If we do not receive an update, we’d be moving your proposal for evaluation under a future event.

    • Sanjoy Bose (@sanjoybsahaj) Proposer a year ago

      Thanks Abhishek. I will get back soon.

      • Abhishek Balaji (@booleanbalaji) a year ago

        Hi Sanjoy, I’m marking this as reject and parking it for a future conference. I’ll move it to evaluation if you can upload the slides and address the questions presented above.

        • Sanjoy Bose (@sanjoybsahaj) Proposer a year ago

          Thanks Abhishesk, unfortunately I have not been able to finish it. Will wait for the next conference schedules. Thanks.

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