Research & Data Strategy
Choosing the best methodology for analyzing data and drawing conclusions requires expertise in understanding how the data is organized, the business goals and research outcomes. Daly Analytics offers a range of specialized solutions to optimize your organization's research and data strategy.
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Our solution for statistical methodology research and implementation goes beyond basic statistical tests by intimately understanding your unique data structure and desired analysis outcomes, ensuring tailored and robust statistical solutions for your specific needs.
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Explainable statistical modeling ensures that your models are interpretable, providing clear insights and actionable results to support your decision-making process.
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Causal impact analysis is a statistical method used to assess the effect of an intervention or treatment on an outcome variable over time. By comparing observed data to a counterfactual scenario (what would have happened without the intervention), it helps identify and quantify the causal impact of the intervention, allowing for more informed decision-making based on the results.
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Hypothesis testing is crucial for establishing the rigor of scientific experiments and assigning substantive significance to outcomes; let us help enrich your research publication with expert guidance and robust analysis.
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Key Performance Indicators (KPIs) are measurable values that demonstrate how effectively an organization is achieving its key business objectives. Daly Analytics can work alongside your key stakeholders to define & distill those measurable values within dashboards and financial reporting.
Expertise Highlight
Led demand analysis and forecasting for a global cloud and security company using custom Prophet models, improving capital expenditure planning for data centers worldwide.
Implemented unconstrained loss modeling using XGBOOST - improving accuracy of loss predictions for an auto insurance company.
Developed a new process using R and LOESS modeling to identify at-risk and high usage growth customers to provide the customer success team with outreach lists on a monthly basis to proactively reduce churn and improve support communications at a WebRTC startup.
Developed an early detection machine learning model to monitor spikes in ACH returns leading to data-informed decisions for mitigating fraud loss for an online bank.
