The Fifth Elephant round the year submissions for 2019
Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering
Sanjoy Bose
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
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