Hey there! I’ve dealt with this exact need before—frustrating that the official docs don’t call out a direct breakdown for day-of-week, but there’s a straightforward workaround. Here’s how to pull off grouped metrics by Sunday/Monday/etc.:

Option 1: Fetch Daily Data & Map to Day of Week (Most Reliable) #

The Facebook Marketing API doesn’t have a built-in day_of_week breakdown, but you can request daily-level data and then post-process it to group by the day name.

Step 1: Request Insights with Daily Time Increment #

When making your API call, set time_increment=1 to get data for each individual day. Include all the metrics you need (like impressions, clicks, etc.) along with standard parameters like level or filtering.

Step 2: Convert Dates to Day of Week #

Once you have the daily response, use your programming language’s date utilities to map each date_start (or date_end) value to the corresponding day of the week.

Here’s a quick Python example to illustrate:

import datetime
from collections import defaultdict

# Sample API response snippet (replace with your actual fetched data)
api_response = [
    {"date_start": "2024-05-26", "impressions": "1200", "clicks": "45"},
    {"date_start": "2024-05-27", "impressions": "1500", "clicks": "60"},
    # ... more daily entries
]

# Initialize a dict to aggregate metrics by day of week
weekly_metrics = defaultdict(lambda: {"impressions": 0, "clicks": 0})

for entry in api_response:
    # Parse the date string (match the format returned by the API)
    date_obj = datetime.datetime.strptime(entry["date_start"], "%Y-%m-%d")
    # Get the full day name (e.g., "Sunday", "Monday")
    day_name = date_obj.strftime("%A")
    
    # Aggregate the metrics
    weekly_metrics[day_name]["impressions"] += int(entry["impressions"])
    weekly_metrics[day_name]["clicks"] += int(entry["clicks"])

# Print the grouped results
for day, metrics in weekly_metrics.items():
    print(f"{day}: Impressions = {metrics['impressions']}, Clicks = {metrics['clicks']}")

Critical Note: Timezone Alignment #

Make sure your API request specifies a timezone parameter (e.g., timezone=Europe/London) that matches the timezone you use for converting dates. This prevents off-by-one errors where a date in UTC might fall on a different day in your local timezone.

Option 2: Spreadsheet Workaround (For Quick One-Off Analysis) #

If you don’t need to automate this via API, export the daily report from Ads Manager, then use spreadsheet tools (like Google Sheets or Excel) to add a formula like =TEXT(date_cell, "dddd") to generate the day name. You can then pivot the data to group metrics by this day-of-week column.

内容的提问来源于stack exchange，提问作者Renjith K