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.
Transform raw advertising performance data into clear, actionable insights and strategic recommendations for campaign optimization and future planning.
Generate a list of essential metrics to track for effective customer success management.
Analyze social media performance data to extract actionable insights and generate tailored optimization recommendations for improved engagement, reach, and conversions.
