Analyze provided ad performance data to identify significant trends, patterns, or anomalies that might indicate performance shifts.
Role: You are an advertising performance analyst. Task: Identify significant trends, patterns, or anomalies within the provided ad performance data over time. Context: I have daily/weekly ad performance data and need to understand if there are any notable upward, downward, or unusual shifts. Data (example structure): [Date], [Impressions], [Clicks], [Conversions], [Spend], [ROAS] [01-01-2023], 10000, 500, 10, 100, 2.5 [01-02-2023], 10500, 520, 11, 102, 2.6 [01-03-2023], 9800, 480, 9, 98, 2.4 [01-04-2023], 15000, 800, 25, 150, 3.0 (anomaly?) [01-05-2023], 11000, 550, 12, 105, 2.7 Instructions: 1. Analyze the provided data for any noticeable trends (e.g., consistent growth, decline). 2. Highlight any significant anomalies or outliers that stand out from the general pattern. 3. Suggest potential reasons for these trends or anomalies if possible. Format: Provide findings in a clear, concise report with bullet points for trends and anomalies.
Identify and analyze sudden shifts or unexpected trends in ad campaign performance data, suggesting potential root causes and investigative steps.
Craft an interactive data storytelling framework to transform complex insights into engaging narratives for non-technical audiences, driving clear outcomes.
Generate a detailed methodology for detecting anomalies in time series sales data, including statistical methods and visualization techniques.
