Analyze this data and summarize key insights.
Use the sample dataset from our Shopify store (last 30 days).
Provide structured summary of key insights, including what stands out across channels and products, identification of underperforming areas (e.g., low-converting channels), and notable patterns. Includes 4–6 prioritized observations and 5 specific follow-up analyses or questions to investigate next.
Review and analyze our sales funnel data.
Use the data from [Campaign name] from [connected analytics app].
Produce set of clearly separated sections: (1) key observed patterns in the funnel, (2) hypotheses explaining those patterns (e.g., onboarding as primary driver), and (3) recommended experiments or tests. Insights are ranked by business impact, with emphasis on conversion bottlenecks and leverage points.
Identify issues or inefficiencies in a process using data
Review the attached current process document, as well as the support team ticket data CSV.
Output a prioritized list of operational issues and bottlenecks (e.g., escalation delays, repeat ticket drivers), each supported by data signals. Includes clear reasoning for why each issue matters, plus recommended areas for immediate improvement or investigation, grouped into quick wins vs deeper fixes.