Targeted Segment Analytics report

Note

This service is currently available to a limited set of clients and Microsoft employees only.

The Targeted Segment Analytics report is an admin-only report designed to give you insight into how your segment targeting is affecting the performance of your in-flight campaigns. Use cases for this report include:

• Understanding which targeted segments (both behavioral and contextual) are driving impressions, clicks and conversions within a running campaign.
• Indexing the performance of targeted segments during the campaign to identify which segments are over or underperforming.
• Understanding whether segments purchased from third parties are producing the desired performance.

Note

This feature is intended to address campaign level performance; it does not include information such as a segment's aggregate performance at the advertiser, insertion order, or line item levels.

Time frame

This report's data is retained for 14 days, and is available in one day intervals. All dates and times are given in UTC.

The time_intervals field in the request can be set to last_14_days.

Dimensions

Column	Type	Description
month	time	The month during which the impression took place. Filter: Yes
day	date	The day on which the impression took place. Filter: Yes
member_id	int	The member ID of the buyer. Filter: Yes
campaign_id	int	The campaign ID of the campaign that purchased the impression. Filter: Yes
campaign_name	string	The name of the campaign that purchased the impression. Filter: Yes
campaign	string	The concatenated name and ID of the campaign that purchased the impression, e.g., "Amazing Campaign (31)" Filter: Yes
campaign_code	string	The (optional) custom code associated with the campaign that purchased the impression. Filter: Yes
segment_id	int	The segment ID of the user segment present for this impression. Filter: Yes
segment_name	string	The name of the user segment present for this impression. Filter: Yes
segment	string	The concatenated name and ID of the user segment present for this impression, e.g., "Valuable Segment (314)" Filter: Yes
segment_code	string	The (optional) custom code associated with the user segment present for this impression. Filter: Yes

Metrics

Note

The definition of each metric listed below should read: "that took place during the selected Time Frame".

Column	Type	Formula	Description
imps	int	imps	The number of impressions that occurred.
clicks	int	clicks	The number of clicks that took place.
total_convs	int	post_view_convs + post_click_convs	The total number of conversions.
convs_rate	double	total_convs / imps	The ratio of conversions to impressions that occurred.
ctr	double	imps / clicks	The click-through-rate.
total_revenue	money	post_view_revenue + post_click_revenue	The total revenue booked through direct advertisers (at the line item level).
post_view_convs	int	post_view_convs	The number of post-view conversions.
post_view_revenue	money	post_view_revenue	The amount of revenue generated by post-view conversions through direct advertisers (at the line item level).
post_click_convs	int	post_click_convs	The number of post-click conversions that occurred.
post_click_revenue	money	post_click_revenue	The amount of revenue generated by post-click conversions through direct advertisers (at the line item level).
post_view_convs_rate	double	post_view_convs / imps	The rate of post-view conversions to impressions.
post_click_convs_rate	double	post_click_convs / imps	The rate of post-click conversions to impressions.
spend	money	spend	The total marketer spend across both direct and real time media buys for this segment.
media_cost	money	media_cost	The total cost of the inventory purchased.
revenue_ecpm	money	total_revenue / clicks	The total revenue per 1000 impressions.
revenue_ecpc	money	total_revenue / click	The revenue per click.
revenue_ecpa	money	total_revenue / total_convs	The total revenue per conversion.

Example

Request the report

$ cat the_request.json
 
{
    "report": {
        "report_type": "targeted_segment_analytics",
        "format": "csv",
        "report_interval": "last_14_days",
        "columns": [
            "day",
            "member_id",
            "campaign",
            "segment",
            "segment_code",
            "media_cost",
            "imps",
            "clicks",
            "revenue_ecpm",
            "ctr",
            "convs_rate"
        ],
        "filters": [
            {
                "campaign_id": "827286"
            }
        ]
    }
}
 
$ curl -bc -cc -X POST -d @the_request.json 'https://api.appnexus.com/report'
 
// Note that the response contains some internal-only debugging info if you request it as an admin user.
 
{
    "response": {
        "status": "OK",
        "report": {
            "name": "",
            "created_on": "2013-11-20 19:29:34",
            "cache_hit": false,
            "fact_cache_hit": false,
            "fact_cache_error": "did not find any cache table for 1,2,30,31,32,34,36,66,6",
            "json_request": "{"report":{"filters":[{"campaign_id":"827286"},{"member_id":"541"},{"campaign_id":"827286"}],"columns":["day","member_id","campaign","segment","segment_code","media_cost","imps","clicks","revenue_ecpm","ctr","convs_rate"],"report_interval":"last_14_days","format":"csv","report_type":"targeted_segment_analytics"}}",
            "header_info": "",
            "row_count": "",
            "report_size": "",
            "internal_info": "{\"report_id\":\"823418c8d5548559948617332a1b5a23\",\"cache_miss\":1,\"cache_host\":\"vertica\",\"query\":\" SELECT to_char(ymd, 'YYYY-MM-DD') AS alias_1,buyer_member_id AS alias_2,CAMPAIGN_ID AS alias_3,segment_id AS alias_4,segment_id AS alias_5,SUM(MEDIA_COST_DOLLARS) AS alias_6,SUM(IMPS) AS alias_7,SUM(CLICKS) AS alias_8,SUM(booked_revenue_dollars) \/ (CASE WHEN SUM(imps) > 0 THEN  SUM(imps) ELSE 1 END) * 1000 AS alias_9,SUM(clicks)::numeric\/(CASE WHEN SUM(imps) > 0 THEN  SUM(imps)::numeric ELSE 1 END) AS alias_10,SUM(post_click_convs + post_view_convs)::numeric\/(CASE WHEN SUM(imps) > 0 THEN SUM(imps) ELSE 1 END) AS alias_11  FROM view_agg_dw_targeted_segments fact  WHERE 1=1  AND ymd >= '2013-11-06 00:00:00' AND ymd  < '2013-11-20 00:00:00' AND CAMPAIGN_ID IN ('827286') AND buyer_member_id IN ('541')  GROUP BY to_char(ymd, 'YYYY-MM-DD'), alias_2, alias_3, alias_4, alias_5 LIMIT 1000000001\n-- [member_id] 0\n-- [report_id] 823418c8d5548559948617332a1b5a23\"}",
            "user_id": "14311",
            "entity_id": "0",
            "started_on": "2013-11-20 19:29:34",
            "finished_on": "1970-01-01 00:00:01",
            "query_time": ""
        },
        "execution_status": "pending",
        "dbg_info": {
            "instance": "29.bm-hbapi.prod.nym1",m
            "s1ave_hit": false,
            "db": "master",
            "awesomesauce_cache_used": false,
            "count_cache_used": false,
            "warnings": [],
            "time": 128.81517410278,
            "start_microtime": 1384975794.8973,
            "version": "1.14.46"
        }
    }
}