Top Insights | Knowledge Base (Product User Guides)

Top Insights shows the lift, impact, and delivery of all behavioral and contextual attributes in your campaign. Top Insights measures the lift of each attribute against the campaign's baseline, not the feature's baseline, thus allowing you to evaluate the performance of attributes across data providers or feature categories. This report shows each attribute's lift as it delivers each individual day. You can:

Slice the report by each Conversion pixel.
Slice the report by custom date ranges, going back 18 months.
New Incremental metrics that combine lift and delivery. Incremental metrics provide insights into each attribute's impact.
See the relationship between performance, delivery, and cost over time on the Trends report.

Campaign baseline is calculated with the general formula: Campaign baseline can clarify further for each available lift metrics:

Impression Conversion Rate Lift = Total attributed campaign conversions / Total campaign impressions
Alien Conversion Rate Lift = Total observed campaign conversions / Total bid opportunities
Click-Through Rate Lift = Total campaign clicks / Total campaign impressions
CPA Lift = Total spend / Total attributed conversions

1. Click on the action menu beside the DSP logo in the upper left corner. Within the menu that appears for Advertisers and Admin, select the Account that contains your advertiser, and then select your Advertiser.

2. As the Advertiser’s campaigns are displayed, select the campaign you would like to view from the list.

3. With the campaign open, click on the breadcrumb menu atop the page and select Manage > Campaign Analytics > Top Insights.

Adjust Top Insights

There are 5 ways to adjust your view of data reflected on the Top Insights page:

Adjust the Parameters.

Adjust the Lift Range.

Adjust the Data Visualization Options.

Adjust the Displayed Attributes.

Adjust the number of Rows Per Page.

Parameters

Expand the Parameters pane to set each field as described below. The report will update with fresh data shortly after you make your selections.

Parameters Metrics Table
Analyze	Select Converters or Clicks. This decision affects whether the report shows insights against converters or clickers.
Who Fired	Select All or individual Conversion Pixels in your campaign. This decision affects which pixels are considered in the report.
From	Select All Sources, Zeta Impressions or Zeta Spend. The data in the Top Insights report is derived from either from Zeta campaigns or All Sources. These data sources are: All Sources: Generate insights against bid requests seen by the campaign. You cannot analyze Clickers using data All Sources. Features like ad recency and campaign frequency are not available if you select All Sources. These features require campaign delivered impressions for evaluation. Zeta Impressions: Generate insights against impressions delivered by Zeta campaigns. Zeta Spend: This option is available when analyzing converters only if your campaign is using dCPM on all line items. Select Zeta Spend to view CPA lift, instead of conversion rate lift. This can help you identify which attributes are most cost-efficient. The lift is calculated as the ratio between the calculated CPA of an attribute and the baseline CPA.
For	Select the date range from which data in the report is derived. Custom Date Ranges can be set on a week-by-week basis.
Against	Select the entire Campaign or specific Line-Items within the campaign. This decision allows you to choose whether to view data on specific lines in the campaign.

Points to remember:

If a campaign is ingesting just Conversions from an External Report, then "From: All Sources" should be selected when pulling data against Converters. "From: DSP Impressions" can be used in this scenario when pulling data against Clickers
Vice versa, if a campaign is ingesting just Clicks from an External Report, then "From: All Sources" should be selected when pulling data against Clickers. "From: DSP Impressions" can be used in this scenario when pulling data against Converters
If a campaign is ingesting both Conversions and Clicks from an External Report, then "From: All Sources" should be selected in all cases when pulling a Top Insights report

Lift Range

Expand the Lift Range pane and input the minimum and maximum displayed values. Any attribute that falls outside the specified range will be hidden.

Use the Exclude Specified Lift Range toggle to either include or exclude the min and max range specified.

Data Visualization

Expand the Data Visualization pane. The secondary metrics provide additional context to the chart by showing incremental and percentage values for each attribute and data source. Select the metrics displayed in the two right-most columns of the report.

When using Zeta Impressions data, the following options are available as secondary metrics:

Incremental Conversions (or Clicks)	This combines lift with delivery to illustrate the amount of additional converters or clickers that can be reached, assuming a fixed rate of response and impression delivery.
% Impressions	The percentage of impressions served by this campaign to users with the attribute.
% Conversions (or clicks)	The percentage of conversions completed by users with this attribute.

When using data from All Sources, the following options are available as secondary metrics:

Incremental Alien Conversions	When the attribute is from a third-party, this combines lift with delivery to illustrate the amount of additional converters or clickers that can be reached by delivering to this attribute, assuming a fixed rate of response and impression delivery.
% of Alien Views (bid views)	The percentage of bids made by this campaign in which the user had the attribute.
% of Alien Conversions	The percentage of conversions completed by users with this third-party attribute.
% of Spend	The percentage of campaign dollars spent on bids with this attribute.

Displayed Attributes

Top Insights can display data for a large number of different attributes categorized into Features. Filter these attributes by Feature using the following process:

1. Click on the All Features dropdown at the upper-left corner to select a specific Feature of attributes to display. Select All Features to show all attributes in all Features.

2. Once you make a selection, the page will automatically update to show only attributes in the selected Feature.

When choosing a specific feature, the following attributes are available:

Category: Context	Is this a Model Attribute?
Above the Fold	No.	True if an Ad is visible on the initial screen, but false if the ability to view the Ad depends on visitor activity such as scrolling a window.
Ad Exchange	No.	The ad exchange that served the ad.
Ad Size	No.	The Ad size, such as 160, 300 or 728 pixels.
Content Category	Yes.	The lifestyle category related to the page.
Language	No.	Lift by predicted language of the Ad visitor.
Site	Yes.	Site that published the Ad.
Netspeed	No.	Lift by method of user's Internet connection.
User Agent Words	Yes.	Words parsed out of user agent from a bid opportunity that relate to device, browser, or operating system.
Category: When
Day of Week	Yes.	The day of the week the ad was served.
Time of Day	Yes.	The time of day the ad was served.
Category: Geography
Country	Yes.	Lift by content category of the page where Ad was served, as reported by the Ad exchange.
State	No.	The U.S. state the user was in.
DMA	Yes.	The designated market area of the user.
Geo Categories	No.	Zeta tracks the historical locations of bid requests for each user and ties them to nearby place categories, e.g. Sporting Goods shops, Electronics Retailers, Shopping Malls, etc.
Geo Places	No.	Zeta tracks the historical locations of bid requests for each user and ties them to nearby place categories, e.g. AT&T, Starbucks Coffee, H&R Block, etc.
Category: Media Activities
Action Recency	Yes.	How much does a recent site visit influence campaign performance? This report captures the effectiveness and predictiveness of targeting visitors shortly after a site action or visit. Specifically, Zeta measures the time between completing an action and clicking or converting bia a subsequent impression from this campaign, and the lift created by each level of recency. Time periods tracked: Less than 1 day 3-7 days 1-2 weeks 2-4 weeks More than 4 weeks Never completed a site action
Ad Recency	Yes.	The time since we showed a user the prior Ad for this same campaign.
Campaign Frequency	Yes.	What was the most effective number of Ad impressions to serve an individual to drive a click or conversion? This report displays the previous number of campaign impressions a user had seen they were served the Ad being analyzed.
Click	Yes.	How much lift have we seen based on users' past click behavior? Zeta tracks whether individual users clicked on your campaign in the past month. For those who did not, Zeta checks whether they have clicked on any campaign in the Zeta network. Otherwise they are not known to have clicked on Ads in the past month.
Click Recency	Yes.	How predictive is the recency of a prior click on your campaign? Users have either never clicked on your campaign or have clicked at some point in the last 28 or more days. Zeta tracks how effective it is to target users by how recently they clicked on your campaign, from 0-8 hours ago, to more than 28 days ago.
Cookie Age	Yes.	How predictive is the age of Zeta's cookie for this campaign? Zeta tracks the length of time since Zeta first saw the user in our network and placed our cookie. Presumably, the longer Zeta has viewed a user, the more information has been collected on their interests and behavior.
Media Condition	Yes.	Media Condition segments.
Pixel	Yes.	Segments based on the campaign's Pixels.
Category: Third-Party Data
Acxiom - Adults	No.	Number of adults in the house as collected by Zeta partner Acxiom.
Acxiom - Age	No.	Age of the user as collected by Zeta partner Acxiom.
Acxiom - Children Ages	No.	Age of the children in the house as collected by Zeta partner Acxiom.
Acxiom - Children Number	No.	Number of children in the house as collected by Zeta partner Acxiom.
Acxiom - Gender	No.	Gender of the user as collected by Zeta partner Acxiom.
Acxiom - Income	No.	Income of the user as collected by Zeta partner Acxiom.
Acxiom - Marital Status	No.	Marital Status of the user as collected by Zeta partner Acxiom.
Acxiom - Net Worth	No.	Net Worth of the user as collected by Zeta partner Acxiom.
Acxiom - Personicx	No.	A third party data tool that is part of Acxiom.
BlueKai	No.	A third-party data source.
Datalogix - Age	No.	The age of the user, as collected by Zeta partner Datalogix.
DLX - Lifestyle	No.	The lifestyle of the user, as collected by DLX.
Epsilon - Buyer	No.	The buying habits of the user. When they buy, how often they buy, how much they spend or what they’re in the market to purchase; as collected by Zeta partner Epsilon.
Epsilon - Ethnic Group	No.	The ethnic group of the user, as collected by Zeta partner Epsilon.
Epsilon - Gender	No.	The gender of the user, as collected by Zeta partner Epsilon.
Epsilon - Income	No.	The income of the user, as collected by Zeta partner Epsilon.
Epsilon - Interest	No.	An interest of the user, as collected by Zeta partner Epsilon.
Epsilon - Language Assimilation	No.	The level of language assimilation of the user, as collected by Zeta partner Epsilon.
Epsilon - Life Stage	No.	The life stage of the user, as collected by Zeta partner Epsilon.
Epsilon - Mailorder Purchase	No.	Whether the user has made mail order purchases, as collected by Zeta partner Epsilon.
Epsilon - Occupation	No.	The occupation of the user, as collected by Zeta partner Epsilon.
Epsilon - Political Party	No.	The political party of the user, as collected by Zeta partner Epsilon.
Epsilon - Purchase Transaction Channel	No.	The purchase transaction channel or institution(s) that facilitate the transaction of the user, as collected by Zeta partner Epsilon.
eXelate	No.	A third-party data source.
eXelate - Age	No.	Age-based on data collected by Zeta partner eXelate.
eXelate - Age EU	No.	The age of the user (in the EU), as collected by Zeta partner eXelate.
eXelate - Career	No.	The career of the user, as collected by Zeta partner eXelate.
eXelate - Children	No.	Whether the user has children, as collected by Zeta partner eXelate.
eXelate - Children Presence	No.	The number of children in the household, as collected by Zeta partner eXelate.
eXelate - Gender	No.	The gender of the user, as collected by Zeta partner eXelate.
eXelate - Gender EU	No.	The gender of the user (in the EU), as collected by Zeta partner eXelate.
eXelate - Home Ownership	No.	Whether the user is a homeowner, as collected by Zeta partner eXelate.
eXelate - Household	No.	The household income of the user, as collected by Zeta partner eXelate.
eXelate - Income	No.	The income of the user, as collected by Zeta partner eXelate.
eXelate - Intent	No.	The intent of the user, as collected by Zeta partner eXelate.
eXelate - Interest	No.	An interest of the user, as collected by Zeta partner eXelate.
eXelate - Shopping	No.	Ther user's shopping patterns, as collected by Zeta partner eXelate.
eXelate - Urbanicity	No.	The user's location on an urban/rural scale, as collected by Zeta partner eXelate.
Eyeota	No.	A third-party data provider.
Personicx - Digital	No.	The user’s digital activity, as collected by Zeta partner Personicx.
Personicx - Digital Group	No.	Grouping users based on their digital activity, as collected by Zeta partner Personicx.
Personicx - Financial	No.	The financial and investment behaviors of the user, as collected by Zeta partner Personicx.
Personicx - Life Stage	No.	The life stage of the user, as collected by Zeta partner Personicx.
Targus	No.	A third-party data provider.
Targus - Age	No.	Age-based on data collected by Zeta partner Targus.
Targus - Children	No.	Number of children in the household based on data collected by Zeta partner Targus.
Targus - Gender	No.	Gender-based on data collected by Zeta partner Targus.
Targus - HHI	No.	The household income, as collected by Zeta partner Targus.
Targus - Home Ownership	No.	Homeownership status, as collected by Zeta partner Targus.
Targus - Household	No.	The household size, as collected by Zeta partner Targus.
Targus - Income	No.	The user's income, as collected by Zeta partner Targus.
Targus - Net Worth	No.	The user's net worth, as collected by Zeta partner Targus.
Targus - Profile	No.	The user's profile, as collected by Zeta partner Targus.
Targus - Urbanicity	No.	The user's location, on an urban/rural scale. As collected by Zeta partner Targus.

When choosing the "All Sources" feature, the following attributes are available:

Category: Context	Is this a Model Attribute?
Ad Exchange	Yes.	The ad exchange that served the ad.
Ad Size	No.	The Ad size, such as 160x600 , 300x250 or 728x90 pixels.
Content Category	Yes.	The lifestyle category related to the page.
Language	No.	Lift by predicted language of the Ad visitor.
User Agent Words	Yes.	Words parsed out of user agent from a bid opportunity that relate to device, browser, or operating system.
Net Speed	No.	The lift generated by the user's internet speed.
Category: When
Day of Week	Yes.	The day of the week the ad was served.
Time of Day	Yes.	The time of day the ad was served.
Category: Geography
DMA	Yes.	The designated market area of the user.
Country	Yes.	The country of the user.
Category: Media Activities
Cookie Age	Yes.	How predictive is the age of Zeta's cookie for this campaign? Zeta tracks the length of time since Zeta first saw the user in our network and placed our cookie. Presumably, the longer Zeta has viewed a user, the more information has been collected on their interests and behavior.
Media Condition	Yes.	Media Condition segments.
Pixel	Yes.	Segments based on the campaign's Pixels.

Rows Per Page

You can adjust the number of rows shown on a single page.

Located at the bottom-right of the page, the options include viewing 25 per page, 50 per page, 100 per page, or All.

Screen Shot 2020-01-06 at 3.26.05 PM.png

Data Bar

Each row in Top Insights represents one attribute.

Top Insights is evaluating each attribute's performance against the campaign's objective. To do this, each attribute is assigned a Lift. Each row displays the Lift with a Data Bar, centered around a Dot and a Lift Percentage.

The Data Bar shows the potential range in the lift of a given attribute. Features of the Data Bar include:

The minimum and maximum values are derived by evaluating the lift values that fall within one standard deviation of the calculated (Dot) value.
The size of the Data Bar corresponds to the confidence we have in the prediction of the lift value. A small Data Bar indicates a narrow range and a high level of confidence in our prediction of the lift value.
If there is no Data Bar, it is because the lift range is smaller than the width of the Dot.

Lift Percentage

The Lift Percentage shows how that attribute is providing lift compared to the campaign baseline. The lift Percentage is represented by a dot in the center of the Data Bar and corresponds to the lift percentage highlighted next to the Data Bar.

Confidence is Key!

Each lift percentage is shown at an 85% confidence level.

Color

The color of the Data Bar, Dot, and Lift Percentage can be shown in red, green, or all green.

Red means the attribute provides less lift than the campaign baseline.
Green means it provides more lift.
All/Both indicate our confidence spread spans over the positive and negative threshold.

Screen Shot 2020-01-06 at 4.26.28 PM.png

Stop Scrolling!

Click on Lift atop the chart to sort the chart by positive or negative lift.

Hover over any attribute's data bar to see a Tooltip for the attribute. The Tooltip shows the Feature and Attribute Name; along with the average lift, and lift range provided by the attribute.

Screen Shot 2020-01-06 at 4.22.40 PM.png Screen Shot 2020-01-06 at 4.24.07 PM.png

Decoding Attribute Names

Attributes are named with the following convention [Feature Name | Attribute] (e.g. "Ad Recency | 2-4 Weeks", "Age | 18-25", or "Gender | Male").

Key

This is a lot to remember, but don't worry, there is a Key on the page to remind users how to interpret the Data Bar.

To open the key, click Screen Shot 2020-01-06 at 3.25.19 PM.png located in the bottom-right corner of the page. To close the key, click

Available Views

There are two views on the Top Insights page: Visualization and Data. By default, Top Insights displays the Visualization View.

Visualization View

The Visualization View is centered around visualizing each attribute's lift relative to every other attribute.

Screen Shot 2020-01-06 at 2.50.45 PM.png

Data View

The Data View shows the raw numbers associated with insights on an attribute.

In Data View users can:

Adjust all column widths.
Not remove the first 6 columns (Date Range, Campaign, Line Item, Conversion Pixel, Feature, attribute).
When analyzing Clickers, the Conversion Pixel column shows a cumulative count for each row.

Screen Shot 2020-01-06 at 2.50.30 PM.png

Date Range	The time frame against which data is being evaluated and insights are being generated. Custom date ranges can be set. The custom dates used in this field are weekly. These weeks begin on Monday and end on Sunday. The report displays up to 18 months worth of data.
Attribute	The name of the attribute, as passed from a third-party vendor or internally Zeta classified.
Campaign	The name of the campaign against which insights are being generated.
Line Item	The name of the line item against which insights are being generated. Line items live within campaigns.
Conversion Pixel	The conversion pixel(s) against which insights are being generated.
Spend	Actual U.S. dollars spent on the given attribute during the given time period. For example, say the campaign spent $100 and you spent $10 on "Men's Sites," $10 is shown. This number is within 5% of the actual value. For example, if you spent $100 espn.com, the Top Insights report may show that number as anywhere between $95 - $105.
% of Spend	Percentage of campaign (or line item) total U.S. dollars spent on the given attribute during the given time period. For example, say the campaign spent $100 and you spent $10 on "Men's Sites," % of spend would surface as 10%. This number is within 5% of the actual Total Spend value. For example, if you spent $10 espn.com in a $100 total spend, Top Insights may show this number as anywhere between 9.5% and 10.5%.
Impressions	The raw number of impressions served to users with a given attribute during the specified time period.
% of Impressions	The percentage of the campaign and/or line item's impressions were served to users with a given attribute during the specified time period.
Avg CPM	The average CPM paid to deliver impressions against users with a given attribute during the specified time period.
Conversions	The raw number of conversions completed by users with a given attribute during the specified time period.
% of Conversions	The percentage of the campaign/line item''s conversions that were completed by users with a given attribute during the specified time period.
Imp Conversion Rate	The rate at which users with a given attribute subsequently carried out a conversion action relative to the impressions delivered to them. Calculate by dividing Conversions by Impressions.
Imp CVR Lift	The ratio between the calculated response rate of an attribute and the baseline response rate. See Lift for details.
Incremental Conversions	Number of conversions that can be generated by targeting the given attribute over an average replacement attribute, or the delivery potential behind each attribute. Calculated as (Imp CVR - Baseline CVR)*(Impressions).
Alien Views	The raw number of bid opportunities associated with a given attribute that are leveraged for generating insights.
% of Alien Views	The percentage of all bid opportunities associated with a given attribute relative to the campaign total.
Alien Conversions	The raw number of conversions that were observed against the conversion pixel(s) assigned to the campaign. These include converters not reached by Zeta impressions.
% of Alien Conversions	The percentage of non-campaign-attributable conversions that were completed by users with a given attribute.
Alien Conversion Rate	The rate at which users with a given attribute fired a conversion action relative to the number of bid views they were seen in. Calculated by dividing Alien Conversions by Alien Views.
Alien CVR Lift	The ratio between the calculated response rate of an attribute and the baseline response rate. Alien CVR Lift is based on bid views and all converting users as opposed to impressions and attributed conversions. See Lift for details.
Incremental Alien Conversions	Number of all alien conversions that can be generated by targeting the given attribute over an average replacement attribute, or the delivery potential behind each attribute.
Clicks	Raw number of clicks completed by users with a given attribute.
% of Clicks	The percentage of the campaign and/or line item's clicks that were completed by users with a given attribute during the specified time period.
Click-thru Rate	Number of clicks on ads divided by the number of Impressions delivered. Calculated as (Clicks/Impressions)*100.
CTR Lift	The ratio between the calculated click-through rate of an attribute and the baseline click-through rate. See Lift for details.
Incremental Clicks	Number of clicks that can be generated by targeting the given attribute over an average replacement attribute.

Lift

The Top Insights Visualization View was designed to display Lift data. The selections within the parameters pane determine the type of lift displayed.

Lift Type	Description	How to Enable	Calculations
Impression CVR Lift	The ratio between the calculated response rate of an attribute and the baseline response rate.	Select the following Parameters: Analyze: Converters Data Source: Zeta Impressions	Positive lift = (attribute response rate / baseline response rate - 1). Negative lift = (1 - baseline response rate/attribute response rate).
Alien CVR Lift	The ratio between the calculated response rate of an attribute and the baseline response rate. Alien CVR Lift is based on bid views and all converting users as opposed to impressions and attributed conversions.	Select the following Parameters: Analyze: Converters Data Source: All Sources	Positive lift = (attribute response rate / baseline response rate - 1). Negative lift = (1 - baseline response rate/attribute response rate).
CTR Lift	The ratio between the calculated click-through rate of an attribute and the baseline click-through rate.	Select the following Parameters: Analyze: Clickers Data Source: Zeta Impressions	Positive lift = (attribute click through rate / baseline click through rate - 1). Negative lift = (1 - baseline click-through rate/attribute click-through rate)
CPA Lift	The ratio between the calculated CPA of an attribute and the baseline CPA. This lift type is only available for campaigns that are being run entirely on dCPM.	Select the following Parameters: Analyze: Converters Data Source: Zeta Spend	Positive lift = (attribute cpa / baseline cpa - 1) Negative lift = (1 - baseline cpa / attribute cpa)

Geographic Attributes

Top Insights contains geographic data for 249 Countries and 353 DMAs from France, the United States, and Great Britain. These locations will appear in the Attribute column via their unique identifier.

Two known exceptions are:

If the campaign currency is AUD (Australian Dollars):
- WA = Western Australia
- NS = New South Wales
If the campaign currency is ZAR (South African Rand), only South Africa (SA) will populate.

Click here to view the list of countries and DMAs.

Description	Feature	Identifier	Name
Country	Geography	AD	Andorra
Country	Geography	AE	United Arab Emirates
Country	Geography	AF	Afghanistan
Country	Geography	AG	Antigua And Barbuda
Country	Geography	AI	Anguilla
Country	Geography	AL	Albania
Country	Geography	AM	Armenia
Country	Geography	AO	Angola
Country	Geography	AQ	Antarctica
Country	Geography	AR	Argentina
Country	Geography	AS	American Samoa
Country	Geography	AT	Austria
Country	Geography	AU	Australia
Country	Geography	AW	Aruba
Country	Geography	AX	Aland Islands
Country	Geography	AZ	Azerbaijan
Country	Geography	BA	Bosnia And Herzegovina
Country	Geography	BB	Barbados
Country	Geography	BD	Bangladesh
Country	Geography	BE	Belgium
Country	Geography	BF	Burkina Faso
Country	Geography	BG	Bulgaria
Country	Geography	BH	Bahrain
Country	Geography	BI	Burundi
Country	Geography	BJ	Benin
Country	Geography	BL	Saint Barthelemy
Country	Geography	BM	Bermuda
Country	Geography	BN	Brunei Darussalam
Country	Geography	BO	Bolivia, Plurinational State Of
Country	Geography	BQ	Bonaire, Saint Eustatius And Saba
Country	Geography	BR	Brazil
Country	Geography	BS	Bahamas
Country	Geography	BT	Bhutan
Country	Geography	BV	Bouvet Island
Country	Geography	BW	Botswana
Country	Geography	BY	Belarus
Country	Geography	BZ	Belize
Country	Geography	CA	Canada
Country	Geography	CC	Cocos Islands
Country	Geography	CD	Congo, The Democratic Republic Of The
Country	Geography	CF	Central African Republic
Country	Geography	CG	Congo
Country	Geography	CH	Switzerland
Country	Geography	CI	Cote D'ivoire
Country	Geography	CK	Cook Islands
Country	Geography	CL	Chile
Country	Geography	CM	Cameroon
Country	Geography	CN	China
Country	Geography	CO	Colombia
Country	Geography	CR	Costa Rica
Country	Geography	CU	Cuba
Country	Geography	CV	Cape Verde
Country	Geography	CW	Curacao
Country	Geography	CX	Christmas Island
Country	Geography	CY	Cyprus
Country	Geography	CZ	Czech Republic
Country	Geography	DE	Germany
Country	Geography	DJ	Djibouti
Country	Geography	DK	Denmark
Country	Geography	DM	Dominica
Country	Geography	DO	Dominican Republic
Country	Geography	DZ	Algeria
Country	Geography	EC	Ecuador
Country	Geography	EE	Estonia
Country	Geography	EG	Egypt
Country	Geography	EH	Western Sahara
Country	Geography	ER	Eritrea
Country	Geography	ES	Spain
Country	Geography	ET	Ethiopia
Country	Geography	FI	Finland
Country	Geography	FJ	Fiji
Country	Geography	FK	Falkland Islands
Country	Geography	FM	Micronesia, Federated States Of
Country	Geography	FO	Faroe Islands
Country	Geography	FR	France
Country	Geography	GA	Gabon
Country	Geography	GB	United Kingdom
Country	Geography	GD	Grenada
Country	Geography	GE	Georgia
Country	Geography	GF	French Guiana
Country	Geography	GG	Guernsey
Country	Geography	GH	Ghana
Country	Geography	GI	Gibraltar
Country	Geography	GL	Greenland
Country	Geography	GM	Gambia
Country	Geography	GN	Guinea
Country	Geography	GP	Guadeloupe
Country	Geography	GQ	Equatorial Guinea
Country	Geography	GR	Greece
Country	Geography	GS	South Georgia And The South Sandwich Islands
Country	Geography	GT	Guatemala
Country	Geography	GU	Guam
Country	Geography	GW	Guinea-bissau
Country	Geography	GY	Guyana
Country	Geography	HK	Hong Kong
Country	Geography	HM	Heard Island And Mcdonald Islands
Country	Geography	HN	Honduras
Country	Geography	HR	Croatia
Country	Geography	HT	Haiti
Country	Geography	HU	Hungary
Country	Geography	ID	Indonesia
Country	Geography	IE	Ireland
Country	Geography	IL	Israel
Country	Geography	IM	Isle Of Man
Country	Geography	IN	India
Country	Geography	IO	British Indian Ocean Territory
Country	Geography	IQ	Iraq
Country	Geography	IR	Iran, Islamic Republic Of
Country	Geography	IS	Iceland
Country	Geography	IT	Italy
Country	Geography	JE	Jersey
Country	Geography	JM	Jamaica
Country	Geography	JO	Jordan
Country	Geography	JP	Japan
Country	Geography	KE	Kenya
Country	Geography	KG	Kyrgyzstan
Country	Geography	KH	Cambodia
Country	Geography	KI	Kiribati
Country	Geography	KM	Comoros
Country	Geography	KN	Saint Kitts And Nevis
Country	Geography	KP	Korea, Democratic People's Republic Of
Country	Geography	KR	Korea, Republic Of
Country	Geography	KW	Kuwait
Country	Geography	KY	Cayman Islands
Country	Geography	KZ	Kazakhstan
Country	Geography	LA	Lao People's Democratic Republic
Country	Geography	LB	Lebanon
Country	Geography	LC	Saint Lucia
Country	Geography	LI	Liechtenstein
Country	Geography	LK	Sri Lanka
Country	Geography	LR	Liberia
Country	Geography	LS	Lesotho
Country	Geography	LT	Lithuania
Country	Geography	LU	Luxembourg
Country	Geography	LV	Latvia
Country	Geography	LY	Libyan Arab Jamahiriya
Country	Geography	MA	Morocco
Country	Geography	MC	Monaco
Country	Geography	MD	Moldova, Republic Of
Country	Geography	ME	Montenegro
Country	Geography	MF	Saint Martin
Country	Geography	MG	Madagascar
Country	Geography	MH	Marshall Islands
Country	Geography	MK	Macedonia, The Former Yugoslav Republic Of
Country	Geography	ML	Mali
Country	Geography	MM	Myanmar
Country	Geography	MN	Mongolia
Country	Geography	MO	Macao
Country	Geography	MP	Northern Mariana Islands
Country	Geography	MQ	Martinique
Country	Geography	MR	Mauritania
Country	Geography	MS	Montserrat
Country	Geography	MT	Malta
Country	Geography	MU	Mauritius
Country	Geography	MV	Maldives
Country	Geography	MW	Malawi
Country	Geography	MX	Mexico
Country	Geography	MY	Malaysia
Country	Geography	MZ	Mozambique
Country	Geography	NA	Namibia
Country	Geography	NC	New Caledonia
Country	Geography	NE	Niger
Country	Geography	NF	Norfolk Island
Country	Geography	NG	Nigeria
Country	Geography	NI	Nicaragua
Country	Geography	NL	Netherlands
Country	Geography	NO	Norway
Country	Geography	NP	Nepal
Country	Geography	NR	Nauru
Country	Geography	NU	Niue
Country	Geography	NZ	New Zealand
Country	Geography	OM	Oman
Country	Geography	PA	Panama
Country	Geography	PE	Peru
Country	Geography	PF	French Polynesia
Country	Geography	PG	Papua New Guinea
Country	Geography	PH	Philippines
Country	Geography	PK	Pakistan
Country	Geography	PL	Poland
Country	Geography	PM	Saint Pierre And Miquelon
Country	Geography	PN	Pitcairn
Country	Geography	PR	Puerto Rico
Country	Geography	PS	Palestinian Territory, Occupied
Country	Geography	PT	Portugal
Country	Geography	PW	Palau
Country	Geography	PY	Paraguay
Country	Geography	QA	Qatar
Country	Geography	RE	Reunion
Country	Geography	RO	Romania
Country	Geography	RS	Serbia
Country	Geography	RU	Russian Federation
Country	Geography	RW	Rwanda
Country	Geography	SA	Saudi Arabia
Country	Geography	SB	Solomon Islands
Country	Geography	SC	Seychelles
Country	Geography	SD	Sudan
Country	Geography	SE	Sweden
Country	Geography	SG	Singapore
Country	Geography	SH	Saint Helena, Ascension And Tristan Da Cunha
Country	Geography	SI	Slovenia
Country	Geography	SJ	Svalbard And Jan Mayen
Country	Geography	SK	Slovakia
Country	Geography	SL	Sierra Leone
Country	Geography	SM	San Marino
Country	Geography	SN	Senegal
Country	Geography	SO	Somalia
Country	Geography	SR	Suriname
Country	Geography	ST	Sao Tome And Principe
Country	Geography	SV	El Salvador
Country	Geography	SX	Sint Maarten
Country	Geography	SY	Syrian Arab Republic
Country	Geography	SZ	Swaziland
Country	Geography	TC	Turks And Caicos Islands
Country	Geography	TD	Chad
Country	Geography	TF	French Southern Territories
Country	Geography	TG	Togo
Country	Geography	TH	Thailand
Country	Geography	TJ	Tajikistan
Country	Geography	TK	Tokelau
Country	Geography	TL	Timor-leste
Country	Geography	TM	Turkmenistan
Country	Geography	TN	Tunisia
Country	Geography	TO	Tonga
Country	Geography	TR	Turkey
Country	Geography	TT	Trinidad And Tobago
Country	Geography	TV	Tuvalu
Country	Geography	TW	Taiwan
Country	Geography	TZ	Tanzania, United Republic Of
Country	Geography	UA	Ukraine
Country	Geography	UG	Uganda
Country	Geography	UK	United Kingdom
Country	Geography	UM	United States Minor Outlying Islands
Country	Geography	US	United States
Country	Geography	UY	Uruguay
Country	Geography	UZ	Uzbekistan
Country	Geography	VA	Vatican City State
Country	Geography	VC	Saint Vincent And The Grenadines
Country	Geography	VE	Venezuela, Bolivarian Republic Of
Country	Geography	VG	Virgin Islands, British
Country	Geography	VI	Virgin Islands, U.S.
Country	Geography	VN	Vietnam
Country	Geography	VU	Vanuatu
Country	Geography	WF	Wallis And Futuna
Country	Geography	WS	Samoa
Country	Geography	YE	Yemen
Country	Geography	YT	Mayotte
Country	Geography	ZA	South Africa
Country	Geography	ZM	Zambia
Country	Geography	ZW	Zimbabwe
DMA	Geography	0	Unknown
DMA	Geography	250001	Ain, FRA
DMA	Geography	250002	Aisne, FRA
DMA	Geography	250003	Allier, FRA
DMA	Geography	250004	Alpes-De-Haute-Provence, FRA
DMA	Geography	250005	Hautes-Alpes, FRA
DMA	Geography	250006	Alpes-Maritimes, FRA
DMA	Geography	250007	Ardeche, FRA
DMA	Geography	250008	Ardennes, FRA
DMA	Geography	250009	Ariege, FRA
DMA	Geography	250010	Aube, FRA
DMA	Geography	250011	Aude, FRA
DMA	Geography	250012	Aveyron, FRA
DMA	Geography	250013	Bouches-Du-Rhone, FRA
DMA	Geography	250014	Calvados, FRA
DMA	Geography	250015	Cantal, FRA
DMA	Geography	250016	Charente, FRA
DMA	Geography	250017	Charente-Maritime, FRA
DMA	Geography	250018	Cher, FRA
DMA	Geography	250019	Correze, FRA
DMA	Geography	250020	Corse-Du-Sud, FRA
DMA	Geography	250021	Cote-D'or, FRA
DMA	Geography	250022	Cotes-D'armor, FRA
DMA	Geography	250023	Creuse, FRA
DMA	Geography	250024	Dordogne, FRA
DMA	Geography	250025	Doubs, FRA
DMA	Geography	250026	Drome, FRA
DMA	Geography	250027	Eure, FRA
DMA	Geography	250028	Eure-Et-Loir, FRA
DMA	Geography	250029	Finistere, FRA
DMA	Geography	250030	Gard, FRA
DMA	Geography	250031	Haute-Garonne, FRA
DMA	Geography	250032	Gers, FRA
DMA	Geography	250033	Gironde, FRA
DMA	Geography	250034	Herault, FRA
DMA	Geography	250035	Ille-Et-Vilaine, FRA
DMA	Geography	250036	Indre, FRA
DMA	Geography	250037	Indre-Et-Loire, FRA
DMA	Geography	250038	Isere, FRA
DMA	Geography	250039	Jura, FRA
DMA	Geography	250040	Landes, FRA
DMA	Geography	250041	Loir-Et-Cher, FRA
DMA	Geography	250042	Loire, FRA
DMA	Geography	250043	Haute-Loire, FRA
DMA	Geography	250044	Loire-Atlantique, FRA
DMA	Geography	250045	Loiret, FRA
DMA	Geography	250046	Lot, FRA
DMA	Geography	250047	Lot-Et-Garonne, FRA
DMA	Geography	250048	Lozere, FRA
DMA	Geography	250049	Maine-Et-Loire, FRA
DMA	Geography	250050	Manche, FRA
DMA	Geography	250051	Marne, FRA
DMA	Geography	250052	Haute-Marne, FRA
DMA	Geography	250053	Mayenne, FRA
DMA	Geography	250054	Meurthe-Et-Moselle, FRA
DMA	Geography	250055	Meuse, FRA
DMA	Geography	250056	Morbihan, FRA
DMA	Geography	250057	Moselle, FRA
DMA	Geography	250058	Nievre, FRA
DMA	Geography	250059	Nord, FRA
DMA	Geography	250060	Oise, FRA
DMA	Geography	250061	Orne, FRA
DMA	Geography	250062	Pas-De-Calais, FRA
DMA	Geography	250063	Puy-De-Dome, FRA
DMA	Geography	250064	Pyrenees-Atlantiques, FRA
DMA	Geography	250065	Haute-Pyrenees, FRA
DMA	Geography	250066	Pyrenees-Orientales, FRA
DMA	Geography	250067	Bas-Rhin, FRA
DMA	Geography	250068	Haut-Rhin, FRA
DMA	Geography	250069	Rhone, FRA
DMA	Geography	250070	Haute-Saone, FRA
DMA	Geography	250071	Saone-Et-Loire, FRA
DMA	Geography	250072	Sarthe, FRA
DMA	Geography	250073	Savoie, FRA
DMA	Geography	250074	Haute-Savoie, FRA
DMA	Geography	250075	Paris, FRA
DMA	Geography	250076	Seine-Maritime, FRA
DMA	Geography	250077	Seine-Et-Marne, FRA
DMA	Geography	250078	Yvelines, FRA
DMA	Geography	250079	Deux-Sevres, FRA
DMA	Geography	250080	Somme, FRA
DMA	Geography	250081	Tarn, FRA
DMA	Geography	250082	Tarn-Et-Garonne, FRA
DMA	Geography	250083	Var, FRA
DMA	Geography	250084	Vaucluse, FRA
DMA	Geography	250085	Vendee, FRA
DMA	Geography	250086	Vienne, FRA
DMA	Geography	250087	Haute-Vienne, FRA
DMA	Geography	250088	Vosges, FRA
DMA	Geography	250089	Yonne, FRA
DMA	Geography	250090	Territoire De Belfort, FRA
DMA	Geography	250091	Essonne, FRA
DMA	Geography	250092	Hauts-De-Seine, FRA
DMA	Geography	250093	Seine-Saint-Denis, FRA
DMA	Geography	250094	Val-De-Marne, FRA
DMA	Geography	250095	Val-D'oise, FRA
DMA	Geography	250096	Haute-Corse, FRA
DMA	Geography	500	Portland-Auburn, ME
DMA	Geography	501	New York, NY
DMA	Geography	502	Binghamton, NY
DMA	Geography	503	Macon, GA
DMA	Geography	504	Philadelphia, PA
DMA	Geography	505	Detroit, MI
DMA	Geography	506	Boston, MA
DMA	Geography	507	Savannah, GA
DMA	Geography	508	Pittsburgh, PA
DMA	Geography	509	Ft Wayne, IN
DMA	Geography	510	Cleveland, OH
DMA	Geography	511	Washington, DC
DMA	Geography	512	Baltimore, MD
DMA	Geography	513	Flint, MI
DMA	Geography	514	Buffalo, NY
DMA	Geography	515	Cincinnati, OH
DMA	Geography	516	Erie, PA
DMA	Geography	517	Charlotte, NC
DMA	Geography	518	Greensboro, NC
DMA	Geography	519	Charleston, SC
DMA	Geography	520	Augusta, GA
DMA	Geography	521	Providence, RI
DMA	Geography	522	Columbus, GA
DMA	Geography	523	Burlington, VT
DMA	Geography	524	Atlanta, GA
DMA	Geography	525	Albany, GA
DMA	Geography	526	Utica-Rome, NY
DMA	Geography	527	Indianapolis, IN
DMA	Geography	528	Miami, FL
DMA	Geography	529	Louisville, KY
DMA	Geography	530	Tallahassee, FL
DMA	Geography	531	Tri-Cities, TN
DMA	Geography	532	Albany-Schenectady-Troy, NY
DMA	Geography	533	Hartford, CT
DMA	Geography	534	Orlando, FL
DMA	Geography	535	Columbus, OH
DMA	Geography	536	Youngstown-Warren, OH
DMA	Geography	537	Bangor, ME
DMA	Geography	538	Rochester, NY
DMA	Geography	539	Tampa, FL
DMA	Geography	540	Traverse City-Cadillac, MI
DMA	Geography	541	Lexington, KY
DMA	Geography	542	Dayton, OH
DMA	Geography	543	Springfield-Holyoke, MA
DMA	Geography	544	Norfolk-Portsmouth, VA
DMA	Geography	545	Greenville-New Bern-Washington, NC
DMA	Geography	546	Columbia, SC
DMA	Geography	547	Toledo, OH
DMA	Geography	548	West Palm Beach, FL
DMA	Geography	549	Watertown, NY
DMA	Geography	550	Wilmington, NC
DMA	Geography	551	Lansing, MI
DMA	Geography	552	Presque Isle, ME
DMA	Geography	553	Marquette, MI
DMA	Geography	554	Wheeling, WV
DMA	Geography	555	Syracuse, NY
DMA	Geography	556	Richmond-Petersburg, VA
DMA	Geography	557	Knoxville, TN
DMA	Geography	558	Lima, OH
DMA	Geography	559	Bluefield-Beckley-Oak Hill, WV
DMA	Geography	560	Raleigh-Durham, NC
DMA	Geography	561	Jacksonville, FL
DMA	Geography	563	Grand Rapids, MI
DMA	Geography	564	Charleston-Huntington, WV
DMA	Geography	565	Elmira, NY
DMA	Geography	566	Harrisburg-Lancaster-Lebanon-York, PA
DMA	Geography	567	Greenville-Spartenburg, SC
DMA	Geography	569	Harrisonburg, VA
DMA	Geography	570	Florence-Myrtle Beach, SC
DMA	Geography	571	Ft Myers, FL
DMA	Geography	573	Roanoke-Lynchburg, VA
DMA	Geography	574	Johnstown-Altoona, PA
DMA	Geography	575	Chattanooga, TN
DMA	Geography	576	Salisbury, MD
DMA	Geography	577	Wilkes Barre-Scranton, PA
DMA	Geography	581	Terre Haute, IN
DMA	Geography	582	Lafayette, IN
DMA	Geography	583	Alpena, MI
DMA	Geography	584	Charlottesville, VA
DMA	Geography	588	South Bend, IN
DMA	Geography	592	Gainesville, FL
DMA	Geography	596	Zanesville, OH
DMA	Geography	597	Parkersburg, WV
DMA	Geography	598	Clarksburg-Weston, WV
DMA	Geography	600	Corpus Christi, TX
DMA	Geography	602	Chicago, IL
DMA	Geography	603	Joplin-Pittsburg, MO
DMA	Geography	604	Columbia-Jefferson City, MO
DMA	Geography	605	Topeka, KS
DMA	Geography	606	Dothan, AL
DMA	Geography	609	St Louis, MO
DMA	Geography	610	Rockford, IL
DMA	Geography	611	Rochester-Mason City-Austin, MN
DMA	Geography	612	Shreveport, LA
DMA	Geography	613	Minneapolis-St Paul, MN
DMA	Geography	616	Kansas City, MO
DMA	Geography	617	Milwaukee, WI
DMA	Geography	618	Houston, TX
DMA	Geography	619	Springfield, MO
DMA	Geography	620	Tuscaloosa, AL
DMA	Geography	622	New Orleans, LA
DMA	Geography	623	Dallas-Fort Worth, TX
DMA	Geography	624	Sioux City, IA
DMA	Geography	625	Waco-Temple-Bryan, TX
DMA	Geography	626	Victoria, TX
DMA	Geography	627	Wichita Falls, TX
DMA	Geography	628	Monroe, LA
DMA	Geography	630	Birmingham, AL
DMA	Geography	631	Ottumwa-Kirksville, IA
DMA	Geography	632	Paducah, KY
DMA	Geography	633	Odessa-Midland, TX
DMA	Geography	634	Amarillo, TX
DMA	Geography	635	Austin, TX
DMA	Geography	636	Harlingen, TX
DMA	Geography	637	Cedar Rapids-Waterloo, IA
DMA	Geography	638	St Joseph, MO
DMA	Geography	639	Jackson, TN
DMA	Geography	640	Memphis, TN
DMA	Geography	641	San Antonio, TX
DMA	Geography	642	Lafayette, LA
DMA	Geography	643	Lake Charles, LA
DMA	Geography	644	Alexandria, LA
DMA	Geography	646	Anniston, AL
DMA	Geography	647	Greenwood-Greenville, MS
DMA	Geography	648	Champaign-Springfield-Decatur, IL
DMA	Geography	649	Evansville, IN
DMA	Geography	650	Oklahoma City, OK
DMA	Geography	651	Lubbock, TX
DMA	Geography	652	Omaha, NE
DMA	Geography	656	Panama City, FL
DMA	Geography	657	Sherman, TX
DMA	Geography	658	Green Bay-Appleton, WI
DMA	Geography	659	Nashville, TN
DMA	Geography	661	San Angelo, TX
DMA	Geography	662	Abilene-Sweetwater, TX
DMA	Geography	669	Madison, WI
DMA	Geography	670	Ft Smith-Fay-Springfield, AR
DMA	Geography	671	Tulsa, OK
DMA	Geography	673	Columbus-Tupelo-West Point, MS
DMA	Geography	675	Peoria-Bloomington, IL
DMA	Geography	676	Duluth, MN
DMA	Geography	678	Wichita, KS
DMA	Geography	679	Des Moines, IA
DMA	Geography	682	Davenport-Rock Island-Moline, IL
DMA	Geography	686	Mobile, AL
DMA	Geography	687	Minot-Bismarck-Dickinson, ND
DMA	Geography	691	Huntsville, AL
DMA	Geography	692	Beaumont-Port Author, TX
DMA	Geography	693	Little Rock-Pine Bluff, AR
DMA	Geography	698	Montgomery, AL
DMA	Geography	702	La Crosse-Eau Claire, WI
DMA	Geography	705	Wausau-Rhinelander, WI
DMA	Geography	709	Tyler-Longview, TX
DMA	Geography	710	Hattiesburg-Laurel, MS
DMA	Geography	711	Meridian, MS
DMA	Geography	716	Baton Rouge, LA
DMA	Geography	717	Quincy, IL
DMA	Geography	718	Jackson, MS
DMA	Geography	722	Lincoln-Hastings, NE
DMA	Geography	724	Fargo-Valley City, ND
DMA	Geography	725	Sioux Falls, SD
DMA	Geography	734	Jonesboro, AR
DMA	Geography	736	Bowling Green, KY
DMA	Geography	737	Mankato, MN
DMA	Geography	740	North Platte, NE
DMA	Geography	743	Anchorage, AK
DMA	Geography	744	Honolulu, HI
DMA	Geography	745	Fairbanks, AK
DMA	Geography	746	Biloxi-Gulfport, MS
DMA	Geography	747	Juneau, AK
DMA	Geography	749	Laredo, TX
DMA	Geography	751	Denver, CO
DMA	Geography	752	Colorado Springs, CO
DMA	Geography	753	Phoenix, AZ
DMA	Geography	754	Butte-Bozeman, MT
DMA	Geography	755	Great Falls, MT
DMA	Geography	756	Billings, MT
DMA	Geography	757	Boise, ID
DMA	Geography	758	Idaho Falls-Pocatello, ID
DMA	Geography	759	Cheyenne, WY
DMA	Geography	760	Twin Falls, ID
DMA	Geography	762	Missoula, MT
DMA	Geography	764	Rapid City, SD
DMA	Geography	765	El Paso, TX
DMA	Geography	766	Helena, MT
DMA	Geography	767	Casper-Riverton, WY
DMA	Geography	770	Salt Lake City, UT
DMA	Geography	771	Yuma, AZ
DMA	Geography	773	Grand Junction, CO
DMA	Geography	789	Tucson, AZ
DMA	Geography	790	Albuquerque, NM
DMA	Geography	798	Glendive, MT
DMA	Geography	800	Bakersfield, CA
DMA	Geography	801	Eugene, OR
DMA	Geography	802	Eureka, CA
DMA	Geography	803	Los Angeles, CA
DMA	Geography	804	Palm Springs, CA
DMA	Geography	807	San Francisco, CA
DMA	Geography	810	Yakima-Pasco, WA
DMA	Geography	811	Reno, NV
DMA	Geography	813	Medford-Klamath Falls, OR
DMA	Geography	819	Seattle-Tacoma, WA
DMA	Geography	820	Portland, OR
DMA	Geography	821	Bend, OR
DMA	Geography	825	San Diego, CA
DMA	Geography	826001	Anglia, GBR
DMA	Geography	826002	Border, GBR
DMA	Geography	826003	Central, GBR
DMA	Geography	826004	Granada, GBR
DMA	Geography	826005	London, GBR
DMA	Geography	826006	Meridian, GBR
DMA	Geography	826007	Stv North (grampian), GBR
DMA	Geography	826008	Tyne Tees, GBR
DMA	Geography	826009	Utv, GBR
DMA	Geography	826010	Wales And West, GBR
DMA	Geography	826011	Westcountry, GBR
DMA	Geography	826012	Yorkshire, GBR
DMA	Geography	826013	Anglia/Central, GBR
DMA	Geography	826014	Anglia/London, GBR
DMA	Geography	826015	Anglia/Yorkshire, GBR
DMA	Geography	826016	Border/Granada, GBR
DMA	Geography	826017	Stv Central (scottish), GBR
DMA	Geography	826018	Border/Tyne Tees, GBR
DMA	Geography	826021	Central/Granada, GBR
DMA	Geography	826022	Central/London, GBR
DMA	Geography	826023	Central/Wales And West, GBR
DMA	Geography	826024	Central/Yorkshire, GBR
DMA	Geography	826025	Granada/Wales And West, GBR
DMA	Geography	826026	Granada/Yorkshire, GBR
DMA	Geography	826027	London/Meridian, GBR
DMA	Geography	826028	Meridian/Wales And West, GBR
DMA	Geography	826029	Meridian/Westcountry, GBR
DMA	Geography	826030	Tyne Tees/Yorkshire, GBR
DMA	Geography	826031	Wales And West/Westcountry, GBR
DMA	Geography	826032	Stv North/Stv Central, GBR
DMA	Geography	826033	STV North
DMA	Geography	826034	STV North
DMA	Geography	826035	UTV
DMA	Geography	826036	ITV Channel Television
DMA	Geography	826037	ITV Border
DMA	Geography	826038	ITV Tyne Tees
DMA	Geography	826039	ITV Yorkshire
DMA	Geography	826040	ITV Granada
DMA	Geography	826041	ITV Wales
DMA	Geography	826042	ITV Central
DMA	Geography	826043	ITV Anglia
DMA	Geography	826044	ITV London
DMA	Geography	826045	ITV Meridian
DMA	Geography	826046	ITV Westcountry
DMA	Geography	826047	ITV West
DMA	Geography	828	Monterey-Salinas, CA
DMA	Geography	839	Las Vegas, NV
DMA	Geography	855	Santa Barbara, CA
DMA	Geography	862	Sacramento, CA
DMA	Geography	866	Fresno, CA
DMA	Geography	868	Chico-Redding, CA
DMA	Geography	881	Spokane, WA

Settings & Trends

By clicking on any cell (via either view), you can see settings and data trends for every attribute over the last 18 months. u can also compare trends across many metrics including impressions, spend, CVR lift, average CPM, and more.

1. To view Trends, click any cell to open the Settings & Trends pane.

2. Toggle the Trends tab to refine the trend data.

3. Select Metrics to compare in the graph.

4. Select the Time Range.

Sort

Click on the column headers to sort the attributes based on these metrics. This can provide valuable insights, such as:

Sort by an “Incremental” column to see which attribute has the most potential impact on conversion/click volume, as opposed to the largest difference in response rate.
Sort by an “% of Impressions” column metric to see which attributes had the most/least delivery against them while simultaneously looking at additional metrics.
Sort by a “% of Alien Views” column to see which attributes had the most/least potential delivery against them (bid opportunities) while simultaneously looking at additional metrics.

Export

Click on Export to create a CSV file of your report. To see a sample Top Insights export, click Unknown Attachment.

Currently, exporting is only available for Data View. We are working to add a Visualization View export in Q2 2020.

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