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Data capture & ML consulting services to map out the way to a custom

An American mass media and entertainment conglomerate with a global presence. They have facing challenges around their Analytical reporting using leveraging Artificial Intelligence Capabilities

Processing System

Must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born will give you a complete account of the system pain can procure.

  • Step 01
  • Step 02
  • Step 03
  • Step 04

Step1: Define the problem:

Differentiate fact from opinion.
Specify underlying causes.
Consult each faction involved for information.
State the problem specifically.
Identify what standard or expectation is violated.
Determine in which process the problem lies.
Avoid trying to solve the problem without data.

Step2: Generate solutions:

Postpone evaluating alternatives initially
Include all involved individuals in the generating of alternatives
Specify alternatives consistent with organizational goals
Specify short- and long-term alternatives
Brainstorm on others’ ideas
Seek alternatives that may solve the problem.

Step3: Evaluate:

Evaluate alternative relative to a target standard
Evaluate all alternatives without bias
Evaluate alternatives relative to established goals
Evaluate both proven and possible outcomes
State the selected alternative explicitly.

Step4: Implement:

Plan and implement a pilot test of the chosen alternative
Gather feedback from all affected parties
Seek acceptance or consensus by all those affected
Establish ongoing measures and monitoring
Evaluate long-term results based on a final solution.

Our Approach

DataGridz engaged, assisted by developing Looker Machine Learning reports leveraging Data Models for building marketing intelligence.
The outcome helped them improve their market insights and were better informed to take business decisions.
->Identify channel which yields more sales uplift
->Real time recommendations to users what is buzzing socially
->Real time multichannel personalized recommendations
->Recommendations for Active/Inactive users
->Recommendations for similar or upcoming shows
->Segmentation of people based on the profile score & cross recommendation to users