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Released September 2010

Targeting Local Markets: An IAB Interactive Advertising Guide

1Target ing Local Markets : An IAB InTerAcTIve AdverTIsIng guIde

“Targeting Local Markets” has been developed by the IAB Local Committee.

About the IAB’s Local Committee:

The mission of the IAB Local Committee is to communicate the value of online local interactive advertising to national and local marketers and to provide tools for publishers to effectively monetize their local ad inventory. A full list of Committee member companies can be found at:

http://www.iab.net/local_committee

This document can be found on the IAB website at: www.iab.net/targeting_local

IAB Contact Information:Gina KimDirector of Industry Initiatives, [email protected]


Table of Contents

Introduction .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

IP-based geo-targeting .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Search Targeting .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Explicit Profile Data Targeting .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Behavioral Targeting (Implicit Profile Data Targeting) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Mobile/Location-based Targeting .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Contextual Targeting .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Example A: National Advertiser .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Example B: Local Advertiser .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Summary .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17


Introduction

Local online advertising is still a very small piece of the overall market and few tools exist to provide local advertisers the ability to effectively purchase local impressions. Companies are increasingly focused on the local online market. Many experts agree that local online advertising is poised for impressive growth in the next few years as local businesses get access to better technology. Borrell Associates forecasts the local online advertising to grow nearly 18% in 2011, from $13.7 billion to $16.1 billion.

OnLIne Ad SpendIng FOrCAST

$ in

bill

ions

National$31.8

2010

Local$13.7

National$35.7

Local $16.1

2011

$60

$50

$40

$30

$20

$10

$0

Source: Borrell Associates

“Targeting Local Markets” is an overall look at some techniques used by the online publishing ecosystem to help drive local online advertising. Some of the techniques provide better accuracy than others. Search is often used in local because of the intended action and ease in buying. Localized content has also become increasingly more popular as local blogs and newspapers report on community and neighborhood activities.

IP-based geo-targeting is commonly used for local advertisers to reach their audience; however, with only 25-50 miles of accuracy it is really only effective for regional advertisers to reach users at a DMA level. Similarly, Behavioral Targeting is frequently used to estimate a user’s location, but inferred location is still far from accurate for most local advertisers.

While techniques continue to evolve one thing is certain: a huge opportunity exists for local advertising online. With a large percentage of consumer spend happening within a few miles of the home, there is incredible incentive for the online ecosystem to continue to search for better tools to drive local advertising.

“Targeting Local Markets” provides example campaigns for 2 types of advertisers (one national and one local) that utilize various techniques to reach local audiences. These examples are illustrations of targeting technologies that marketers and advertisers can use today in their own advertising campaigns and should not be taken as an endorsement of any one technique.

The IAB Local Committee will continue to watch the marketplace and the evolution and development of new technology and techniques to reach local users online.


Ip-based geo-targeting

definitionIP-based geo-targeted advertising is delivered to a user’s geographic location as determined by his or her Internet Protocol (IP) address.

ScaleEvery computer connected to the internet is assigned an IP address by its ISP, so the pool of IP targeted impressions is large. However, unlike ZIP codes or area codes, the numbering system of an IP address has no correlation with geography. Therefore a computer’s location cannot be determined by IP address alone.

IP intelligence firms such as Digital Element and Quova supply technology that matches IP addresses to a physical location, providing coverage of virtually the entire internet universe with geographic data.

However, while IP-based geo-targeting is accurate in indentifying the geography of the IP address, there are limitations to the quality of data relative to advertiser intent.

pricing IP-based geo targeting is widely available with many competitive pricing options.

Accuracy vs. precisionGiven that an advertiser’s intention is to reach people, not their IP addresses, the discrepancy between the location of an IP address and a user’s true location diminishes the precision of IP-based geo-targeting.

Several underlying factors can contribute to inconsistency:

• Outdated information – a small percent of IP addresses worldwide change location each month. As IP addresses are dynamically assigned (unlike telephone numbers that are geographically associated) reissued IP addresses can be located anywhere.

• Centrally located networks – many organizations with locations in multiple cities have their computer networks mapped to a centrally located IP address. This explains why, for example, someone working in the Los Angeles office of an Ohio based company may see advertising targeted to Cleveland.

• Proxy Servers – some ISPs use a single, or a small number of servers for all users thereby having all their users assigned to few IP addresses. In an oft-cited example, several years ago most AOL users appeared to come from Reston, Virginia regardless of where they lived.

• The more granular the targeted geography, the less precise IP-based geo targeting becomes. When evaluating IP-based geo-targeting, advertisers should consider their campaign’s geographic objectives and requirements, and tolerance for inexactness.

• Generally speaking, IP geo-targeting to the state or DMA level will be more effective that targeting a specific neighborhood. For example, a retailer with multiple locations in the New York City market may regard IP geo-targeting more favorably than one with a single store serving the SoHo area.


Search Targeting

definitionLocal search targeting helps advertisers target users when they look for places, businesses, housing, entertainment, etc. in specific geographies using a search engine (such as Google or Bing). This allows advertisers to present highly relevant localized offers and advertisements to users.

This is an effective form of advertising because the user may enter his or her location in the search query. For example, if a user is searching for “San Francisco condos” an advertiser may purchase those words or phrase and an ad for “restaurants in San Francisco,” may appear on the search results page. The user is likely to take interest in this targeted type of ad over a generalized advertisement.

This is different from IP-based targeting because where the user is querying from and what the user is querying for can be very different. For example, a user might be in New York City but looking for a sunny vacation in Miami. An advertiser in this case could place localized listings for hotels in Miami instead of less relevant hotels in New York if IP-based targeting were used.

ScaleSites with local, searchable content can usually provide a highly targeted audience of users that are performing local searches. The number of page views and users is typically on par with IP-based targeting.

pricingBecause of the explicit statement of interest by the user, local search advertising typically performs well and has high value. At the same time, the inventory is more finely sliced and limited. Usually, this type of targeting commands a premium.

Accuracy vs. precision This type of targeting is very accurate because the user is explicitly stating his or her interests when entering a search query.


explicit profile data Targeting

definitionExplicit data is “registration quality data” collected either online or offline. For online registration data, the user has certain attributes in his or her registration profile at a particular site or service, and that data is associated with the user’s Web cookie or some sort of audience database when the user next logs in. Offline registration data includes the sorts of data held in the massive offline direct response industry databases built up over the last several decades. These are then matched to a user online when that user logs in somewhere that is a partner of the data company. The site at which the user logs in, usually an online mail or similar site, sends the name/email combination to the data company, which then makes the match and sends back data. Ethical data providers do not put personally-identifiable data into the cookie or audience database, but rather anonymize the data (e.g., “male” rather than a name or address).

The data collected is not about where the user has visited, but what they have said about themselves. Much of this data is demographic or purchase history data.

Not all “intent” data is explicit. When data collected is based on visitation to certain types of sites, that is implicit data, even if the site is a detailed listing site. An example of implicit intent data is when a user has visited a car listing on an auto site. An example of explicit intent data is when a user in his or her registration preferences states an expectation to buy a car in the next 90 days.

Explicit data can either be first party (garnered by the site/service in which it is used) or third party (garnered from an external source).

ScaleScale is the primary concern with explicit data. Of all the targeting types, explicit data have the smallest pools. While it allows the conclusion “this person definitively is in this category”, there are 2 prerequisites: the user has provided data in the past (online or offline) and the data has been matched with an online user. Therefore, the pool will never be as large as the actual population. For example, even if the number of males in this country is over 100 million, the number of explicit online data males, across all data providers combined, is likely only 60-70% of that total. Any one data provider has only a fraction of that.

pricingIn general, first party data commands a far more variable premium than third party data. First party data is often more trustworthy, as there are often far fewer steps between the data-collecting party and the ad impression. Additionally, first party data, since by its nature is being used in ads sold by the data collecting party, does not incur additional cost in the process of serving the ad. It is, instead, a differentiator for the media outlet selling the ad. Third party data is usually available in much larger quantities, and yet there is often a fee of anywhere between $0.50 to $2.00 or more paid to the data provider by the ad seller – thus increasing the cost of goods sold (COGS) on the ad, and therefore increasing the price.


Accuracy vs. precisionExplicit data is both highly accurate, as the data has been freely given by the user about them, and can be highly precise. The precision is based on the level of the questions asked by the data provider. Some data, especially offline, is very precise. For example, there are data providers that know what car is in an individual’s driveway, household income, past purchase history, and similar information based on surveys.

Several underlying factors can contribute to inconsistency:

• Outdated information due to clearing of cookies

• Veracity of user registration data


Behavioral Targeting (Implicit profile data Targeting)

definitionBehavioral Targeting is the ability to serve online advertising based on profiles that are inferred from an individual user’s technical footprint and viewing behavior. As opposed to Explicit Profile Data Targeting, Behavioral Targeting uses implicit data collected on a user’s Web browsing actions, usually through the use of “cookies.”

The implicit data collected is with reference to where the user has been online and what activities he or she has completed – such as specific pages visited, searches made, or clickthroughs to specific content or ads.

Online publishers and advertisers use this information on its own or often in conjunction with explicit profile data and/or contextual data to display more relevant advertising specific to the interests of the user.

ScaleData can be collected on many levels. Originally implicit data was gathered from surveys, opt-in forms and public records. However, now data is also gathered from the digital footprint left by the individual user through raw data feeds. This digital footprint has become ubiquitous, not only through more sophisticated targeting, but also through the increasingly intimate use of the Internet as a vehicle for information searches, information gathering and transactions. As the medium has grown from a “browsing” experience to interactional so have the levels of information gathered. Newer forms of information include the data collected about influences, social preferences through social networks and an individual user’s content created online.

The data is often gathered in real-time and can be used for real-time decision-making so that relevant advertising can be delivered dynamically to an individual user during their online session.

Individuals do have some control over the amount of information they share and the more technically proficient can limit certain information gathered by disabling various file, cookies and history settings, thus reducing the scope of the individual’s data footprint. Individuals may also elect not to register at a Web site that offers such an option.

pricingPricing for behaviorally targeted advertising commands higher ad rates than less targeted advertising that lacks profile information about the individual user. Behaviorally targeted advertising commands a higher price because of targeted placement versus general run-of-site (ROS) advertising.

By virtue of the targeted nature the digital footprint provides, an advertiser can request that their advertising be placed in the appropriate places where it will be seen by the users that meet their customer profile.

Cost Per Action (CPA), or Pay Per Click (PPC), pricing methods are often the basis for the ad serving structure because of the ability to deliver higher results based on the higher probability of a user’s interest.

Accuracy vs. precisionBehavioral Targeting can be highly accurate when the user is leaving a digital footprint of their activities as they move through the Web. Problems can arise if the computer is in public use, shared by other people (libraries, households with shared computers, etc.), or if the amount of data collection settings has been reduced by the user (clearing cookies).


Mobile/Location-based Targeting

definitionMobile/location-based targeting refers to a way to target advertisements on mobile devices such as smartphones or feature phones, GPS receivers, tablets (such as iPads) and soon on many mobile laptops. On phones and tablets, such advertisements can appear in a mobile Web browser or within an app. Geographic targeting information can come in the form of either a confirmed location or a derived location.

Confirmed Location. A phone, mobile operator network, or a user may provide confirmed-location data. One method of confirming a location is by utilizing a phone’s GPS capabilities to produce a set of latitude and longitude (“lat/long”) coordinates. GPS-based data may be provided by the phone directly in some cases, or may be aggregated and brokered to third parties by the mobile operator. User-provided confirmed-location data provide not only a specific location but also intent. For example, users may type in a city or ZIP code into a publisher website or application, indicating either where they are now, or where they are going in the future. In another instance, users may “check in” at a location they specify. Ads can then be tailored to where the user has interest.

derived Location. A mobile web or app publisher can provide derived-location data. For instance, a publisher may derive what the likely location of the user is by the nature of its content or audience demographics. In another instance, mobile network operators may derive a DMA location of the user by matching the cell tower being used to the tower’s known geographic location. Some network operators offer this derived-location data to mobile web or app publishers. This derived location will typically be more precise in urban areas, where cell towers cover smaller areas, and less precise in rural areas. As a third example, for devices that connect via wi-fi, a number of vendors map the locations of hotspots and use that data to derive the approximate location of users connecting via that technology.

ScaleThe total mobile inventory in existence remains a fraction of what’s available on the Web. This inventory is by far mostly mobile Web (~70%) rather than application inventory (~30%). In other words, most ads are shown in a phone’s Web browser rather than within an app running on the phone.

Consequently, most available mobile ad inventory has only DMA-level targeting because mobile Web publishers generally have access to only derived-location data. Large scale campaigns consequently cannot be fulfilled when only targeted on neighborhood levels or sometimes even city levels. A minority of mobile ad inventory can be layered with lat/long coordinates but not enough to fulfill large scale campaigns trying to only reach a very specific part of a DMA and not the rest.

pricingMobile-targeting pricing varies depending on the granularity of the target info -- the more finely sliced, the more expensive the inventory. Mobile in general tends to be a more intimate experience because there are fewer ads on screen at any given time and ads can sometimes be delivered while a user is physically near a location to take action there. Consequently, mobile inventory may carry a premium over its Web counterpart for a location-focused advertiser.


Accuracy vs. precision Confirmed-location targeting is extremely accurate. Such targeting will rarely deliver an ad for the wrong location.

However, the vast majority of mobile inventory lacks that granularity. DMA-level targeting from derived-location data remains the most prevalent and easily implemented mobile targeting. Campaigns purchased to reach a sub-section of a DMA can certainly expect high precision for the DMA but will expend money to reach areas and audiences not of interest.

Mobile targeting based on location data derived by broad demographics of a publisher’s audience or the publisher’s content is prone to the same inaccuracies as traditional media. This targeting relies on generalized demographic information about the target audience, but some users may fall outside the normal. In the best cases, the publisher itself is location-specific and would have wastage comparable to a city-magazine when considering how many users would read the publication but not fit the target geographic market.


Contextual Targeting

definitionContextual targeting serves advertising messages based on content being viewed on an individual Web page. In contrast to audience targeting, contextual targeting leverages information inferred about the user mindset at the time an ad is being viewed. There is a visible trend towards hyper-local targeting (ZIP code, neighborhood, etc.), which, most often leverages local content that is highly relevant to the user. Contextual targeting does not only apply to geo-targeting, but also is available for personal interests (travel, golf, medical condition, etc.) This form of geo-targeting can be used to reach users at various ZIP codes, cities, DMAs, states, regions or countries. Examples of contextual local content can include:

• Events

• Local news

• School information

• Weather: ZIP code, city, state, country

ScaleBased on the geography and the target, Contextual targeting can range from niche to mass. Typically, content sites in the news and information category specialize in contextual geo-targeted inventory. Naturally, portals and ad networks can also target contextually.

pricingContextual targeting is one of the more accurate forms of geo-targeting and therefore typically commands higher prices than other forms of geo-targeting. Pricing for contextual geo-targeting varies based upon the degree of local targeting (i.e. zip code will be more expensive than state).

Accuracy vs. precisionThere is a direct correlation between accuracy of geo-targeting and price. While contextual targeting is among the most accurate, it has exceptions. On some sites, non-local users might be viewing travel content. For example, frequent leisure travel cities like Las Vegas and Orlando may have a higher concentration of travelers vs. locals. It is important to check with the site on its method to deal with these exceptions. Oftentimes, that may mean the addition of an IP layer on top of the contextual geo-targeting.


example A: national Advertiser

Advertiser: National Hardware Retailer (DIY Hardware)

Objective: Online promotion to increase sales and collect explicit profile data

DIY Hardware is seeking to increase the sale of Acme power tools using a promotion aimed at DIY’s (do-it-yourselfers). The promotion is for the prize of a “Wreck” room makeover based on users voting for the worst-looking recreation or family room based on user-photo submissions. Acme is sponsoring the promotion along with regional sponsorship by local market furniture stores (handled by DIY Hardware). Information gathered at contest registration will include e-mail, age, gender, # of years in current home, # of people in household, income, and address.

IP-based Geo-Targeting

IP targeting will be done to ensure coverage of outlying markets such as suburban and rural areas.

Search Targeting

Search targeting will be used to capture users that may be interested in purchasing power tools. Key words such as “powertools” “electric/battery drill” and other power tool descriptions will be used. In addition, words related to the contest such as “rec room” “remodeling” and “wreck room” will be used.

Explicit Profile Data Targeting

DIY Hardware has an e-mail list of customers containing their past purchase and demographic information. This information is deemed good because it is supplied by the consumers themselves. The list has been actively maintained and is considered fresh. Special e-mails will be sent to customers who are homeowners and who have indicated they have lived in their house for more than five years. Further sorting will be done to target households that include children and young teens. The mailing will be divided by gender and have different subject lines and content for females and for males.

Behavioral Targeting (Implicit Profile Date Targeting)

DIY Hardware will use behavioral targeting, which collects information on a user’s Web browsing actions, usually through the use of “cookies,” to track all their advertising and visitors to the power tools section of their Web site. Information gathered on the user’s footprint will be used to refine the targeting of display ads and to better place new advertising online.

Location Based Mobile Targeting

DIY Hardware employs location based targeting to reach consumers via their mobile decides. Utilizing a phone’s GPS capabilities, DIY Hardware will send messages inviting mobile users to vote in-store at a kiosk for the ugliest rec room or to upload their own pictures that they can take from their cellphone. Registration can be done on a mobile browser through a special mobile site.


DIY Hardware will place a series of online display ads for the contest on specific home decorating and interior design DIY Web sites such as Better Homes and Gardens (BHG.com) and diynetwork.com. These ads will be placed in the areas associated with home improvement and decorating of family rooms and recreation rooms.


Objective: Circulars

DIY Hardware is challenged by rising newsprint costs and a large shift of media time away from newspapers to Internet. How will they evolve their circular budget to meet this challenge?


IP target users by their Designated Market Area (DMA), to synchronize digital creative with the weekly newspaper insert, local broadcast schedule, and in-store circular to ensure that the user receives a sales message appropriate to their local area stores. In addition to ensuring that the national media appears localized, IP targeting can be used when DIY wants to complement their national media with additional media weight in certain co-op markets.

Search Targeting

Search targeting allows DIY Hardware to align their own store product needs with the needs of their consumers. For example, DIY can purchase search terms like “Chicago Gardening”, “Richmond Paint Store” or “San Jose Plumbing” to support product sales that exist across their desired geographies. Doing this allows them be relevant at very opportune times.


DIY Hardware will use its segmented email list to target appropriate prospects in targeted markets informing them to get the new circular online. The segment of homeowners that are least likely readers of newspapers will be targeted first (ages 27-40). Users can also register to receive a weekly preview copy by email.

Behavioral Targeting (Implicit Profile Date Targeting)

DIY Hardware is able to tap into consumer behaviors on their site and around the Web to accurately target their circular products. For starters, DIY monitors the behavior of consumers who receive their in-store weekly email to learn which products are of interest. If a consumer clicks on a product from the email circular, DIY Hardware takes note of that and later targets them throughout the Web via what is referred to as retargeting. Here, as consumers view media on thousands of Web sites, a behavioral network shows them an ad banner for the exact product viewed on DIY’s Web site.


DIY Hardware employs location based targeting to reach consumers via their mobile decides. Utilizing a phone’s GPS capabilities, DIY Hardware sends local ad messages via the mobile Web or apps that encourage a consumer to visit the store near them for one of many circular products on sale. Given the proximity of one’s cell phone to them at all times, this is a quickly growing method to reach affluent people on the go.


DIY Hardware maintains a local presence by advertising on local media Web sites. When DIY’s banners load on these sites, a look-up is done to determine the context of the page. A few highly regarded Web sites and rich media vendors have the capability to then populate the ad banner with product images and prices relevant to the local content being viewed. This allows the advertiser to traffic one piece of creative along with a weekly feed of circular products to populate within the banner.


Objective: Localized Branding

DIY Hardware is looking to continue to evolve a very strong national brand, and to remind customers of all of the ways DIY Hardware can help make their homes better. They want customers to know their local DIY Hardware understands their needs and can deliver on better customer service, in-stock inventory, and a friendly shopping environment.


IP-based geo-targeting can be used to get blanket coverage. For larger DMAs, they can improve on reaching a more specific audience by combining IP-based geo-targeting with another targeting methodology.

Localized Search Targeting

DIY Hardware can tailor advertising messaging to users depending on their local search criteria. For example, DIY Hardware can target ad creative highlighting all the different top Designer Paint Brands that they carry at the local DIY Hardware to users searching for open houses in Beverly Hills, CA. For users searching for open houses in San Francisco, CA, they would tailor the ad messaging to all of the Green and Environmental friendly products they carry at DIY Hardware stores near San Francisco.


DIY Hardware can target users on Facebook based on where they’ve indicated they live. Similar to sending marketing by post mail, DIY Hardware can show users’ ads with local messaging based on where a user lives. This data is typically very accurate and therefore an effective creative that would resonate with the user could be an ad that shows the location of the nearest DIY Hardware with a friendly face.

Behavioral Targeting (Implicit Profile Data Targeting)

Because this is slightly less accurate than Explicit Profile data targeting but has a broader reach, DIY Hardware can create a more generalized message based on where the customer likely lives. For example, DIY Hardware can have ads showing different colored Cape Cod-style homes being painted in the New England area, and similar creative but on Colonial-style homes for users in Georgia.


With the best in-stock inventory, DIY Hardware has the unique ability to promote a DIY inventory tool that could be available for its customers on a mobile device. This could allow the customer to check inventory for what they want to buy on their own mobile phones. Promoting a tool available on mobile devices to check inventory in their local DIY Hardware would leverage technology across all stores and demonstrate to the customer that DIY Hardware understands the needs of customers constantly on the go.


DIY Hardware can tailor messaging based on the local content of the site. In a promotion for DIY Hardware with sports teams, the advertising can be painting a chair purple-and-gold when shown on a page about the Los Angeles Lakers, or painting pinstripes when shown on a page where users are reading about the New York Yankees. This will further show that DIY Hardware can relate to the customer and because of the National footprint, there is a local DIY Hardware that can help the customer paint their chairs the correct color based on their sports team.


example B: Local Advertiser

Advertiser Local Auto Dealership (TLC Cadillac)

Marketing Objectives

• Drive dealership traffic

• Promote sales events

• Increase test drive for new models

Target Audience

TLC Cadillac targets a specific audience segment of car buyers. This audience segment consists of 35+ year olds with household income $80k+ and professional or technical occupations. Ideally, they have expressed interest in purchasing a luxury domestic car. Geographically, TLC Cadillac only wants to reach people in Central and Southern Connecticut which is within one hour travel from its location.

Recommended Media Plan

To reach its target audience, TLC Cadillac will push its message out to target demographic through guaranteed-placements and will pull in buyers who are actively looking for new vehicles through non-guaranteed performance placements. The goals of these media buys are to drive foot traffic to the dealership in general, build awareness of large sales events, and gather customers interested in test driving the newest vehicles.

IP-based geo-targeting

This will be utilized to deliver a large quantity of ad impressions to the target audience segment. The best ad creative would be one for promotion of large sales events like a Labor Day Blowout Sale since the added promotional offers would be more likely to induce foot traffic than a general advertisement touting the dealership location. Of the IP-based geo-targeting budget, greater allocation could be made to target the affluent Fairfield County. Specifying ZIP codes of that county like 06830, 06831, 06832, and 06836, which identify Greenwich residents, can further refine the ad delivery to households likely to fit the target audience parameters. Unfortunately, the inaccuracy of IP-based geo-targeting will lead to many wasted impressions which are delivered to misidentified users outside the target zone. However, a good amount will be delivered to users within the target zone. Because of this result, much attention must be given to acquiring impressions at low CPMs to ensure enough impressions are being delivered within the target zone for the budget given.

Explicit Profile Data Targeting and Behavioral Targeting (Implicit Profile Data Targeting)

These ad buys can be utilized to deliver sizeable ad impressions to the target audience segment. Explicit profile targeting would restrict the ad delivery to an ad view who self identified as being a 35-64 year old who earn $80k+, and has a professional or technical occupation. Behavioral targeting would deliver impressions to audience segments identified to be “Auto intenders/In Market: Luxury Class” and “Auto intenders/In Market: Cadillac.” These methods would best achieve the goal of driving general foot traffic since the media spend will be devoted to reaching users who have gone to auto-websites in recent history or self-identified themselves as auto-enthusiasts.



This will deliver both guaranteed placement and non-guaranteed performance placement. To gain signups for future exclusive test drive events for new models, TLC Cadillac can make contextually-targeted ad buys on auto portals to run ad creatives that offer the ability to register to users reading auto-related websites. To reach users already in the market, TLC Cadillac can pay on a performance basis to place its ads on a wide range of content sites to reach that user who is on a site with specific keywords that relate to a stage of decision making.

Search Targeting

Using search targeting can best deliver non-guaranteed performance placement to ensure TLC Cadillac’s message is put in front of a user actively searching for information relating to an auto purchase. Most of the non-guaranteed placement budget should be dedicated to search targeting to ensure sufficient fulfillment in a highly valuable inventory. Search targeting would be best suited to drive interested customer traffic to the dealership.

Mobile Targeting

This will help drive dealership traffic and promote sales events in a similar fashion to IP-based geo-targeting, contextual targeting, and search targeting by simply doing the same thing these methods do for the desktop but for a mobile handset. However, more of the budget should be allocated to achieve the goal of increasing test drives for new models. Mobile targeting can allow TLC Cadillac to reach users who are in short walking or driving distance and offer them the ability to walk-in the store to simply test drive a new model. TLC Cadillac can go step further and offer their already existing free beverages for prospective customers as another way to entice people to stop by the dealership while nearby.


Summary

Methods of Placing Geo-targeted Advertising

Definition Example Usage

IP-basedLocation based on user’s IP address

End-user at home using internet; IP address of local ISP is detected

Broad-targeting of users based on where they are browsing the internet

SearchTarget user searches for local content

End-user searches for homes in a particular neighborhood of interest

Target specific local search terms initiated by users

Explicit Profile

Location is based off user’s registration info

End-user registers with their home address on a social network

Target users based on their registration info

Behavioral (Implicit Profile)

Location is inferred based on a user’s browsing behavior

End-user browses local news and sports content from different websites

Target the user with specific messaging based on their browsing behavior

Mobile/ Location-based

Targeting on mobile handsets based on GPS coordinates

User is browsing the internet from their mobile device

Target users on their mobile device when their approximate location is known

ContextualTargeting to content being viewed on the website

User is browsing local weather

User is browsing local weather

targeting local markets - archive.iab.com · targeting local markets: an iab interactive...

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