Develop and implement roadmap for data mining and quantitative methods to advance customer segmentation, persona development, customer retention marketing strategies, Marketing Mix Modeling, audience optimization efforts and other key business applications.

More Uses of the Marketing Mix Modeling Toolkit:

  • Provide recommendations for cloud analytics technology and be part of the team implementing.
  • Oversee and conduct descriptive analyses to identify, analyze and interpret trends or anomalies in data.
  • Perform quality checks on attribution/Marketing Mix Modeling output to ensure validity and business sense.
  • Translate data into clear, compelling, and actionable insights by leveraging advanced analytics tactics conducted by central resources.
  • Govern: work cross functionally with data, marketing, product, and engineering to identify opportunities toward business objectives.
  • Identify potential data sources and key data points to be captured, outlining and thinking about potential future uses.
  • Be certain that your organization performs analyses of structured and unstructured data to solve multiple and complex business problems.
  • Evaluate effects on marketing optimizations across different and disparate marketing channels.
  • Provide on going analytical leadership in regards to media/Marketing Mix Modeling, attribution, and media optimization for clients.
  • Recruit, train, inspire, mentor, manage and develop the Data Science team.
  • Lead pre sales/sales activities to address critical client concerns regarding marketing effectiveness, marketing mix analysis, pricing strategy.
  • Supervise: partner with marketing to design and measure marketing experiments, scale and optimize acquisition channels, and understand your customer personas to increase engagement.
  • Audit: partner and collaborate with other departments to develop consistent and standardized views of marketing performance and reporting.
  • Steer: team collaboration is key in understanding the mechanics and dynamics of an enterprise scale client engagement.
  • Be accountable for utilizing advanced statistical techniques and mathematical analyses and specialized expertise in multi channel marketing strategies.
  • Direct: descriptive statistics, hypothesis testing, econometric modeling, and regression analysis.
  • Consult on data strategy for your organization, in collaboration with data strategy lead.
  • Anticipate client needs and proactively developing recommendations and solutions.
  • Manage: interface with clients and internal team members to account for complex analytic concepts in an easy to understand way.
  • Ensure you build and mentor a team of marketing data scientists with your technical capabilities.
  • Generate and communicate clear, compelling data analysis with actionable insights; construct insightful narratives through sophisticated analytic techniques.
  • Secure that your organization applies analytical rigor and statistical methods to analyze large amounts of data, using advanced statistical techniques.
  • Ensure you build Marketing Mix Modeling, diminishing returns analysis and campaign test design to assess and inform client return on media investment.
  • Formulate: work to enhance your organizations overall business intelligence offering and analytics strategy.
  • Manage and coordinate with other departments to ensure that disruptions to client reporting is minimized.


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