Native advertising

Native advertising is a web advertising method in which the advertiser attempts to gain attention by providing valuable content in the context of the user’s experience; it is similar in concept to an advertorial, which is a paid placement attempting to look like an article. A native ad tends to be more obviously an ad than most advertorials while still providing interesting or useful information. The advertiser’s intent is to make the paid advertising feel less intrusive and thus increase the likelihood users will click on it.

Among the formats for native advertising are promoted videos, images, articles, music and other media. Examples of the technique include Search engine marketing (ads appearing alongside search results are native to the search experience) and Twitter with promoted Tweets, trends and people. Other examples include Facebook’s promoted stories or Tumblr’s promoted posts. Content marketing is another form of native advertising, placing sponsor-funded content alongside editorial content or showing “other content you might be interested in” which is sponsored by a marketer alongside editorial recommendations.

The types of platforms and websites that participate in native advertising can be split up into two categories, “open” and “closed” platforms. “Closed” platforms are brands creating profiles and/or content within a platform, then promoting that content within the confines of that same closed platform. Examples include Promoted Tweets on Twitter, Sponsored Stories on Facebook and TrueView Video Ads on YouTube. “Open” platforms are defined by the promoting the same piece of branded content across multiple platforms within native ad formats. Unlike closed platforms, the branded content asset lives outside the platform. For example, Adyoulike, AdsNative, Sharethrough and Nativo are open native advertising platforms, which allow brands to include the same content in native ad placements on multiple publishers. Large publishers, such as Washington Post, have recently started introducing their own native advertising formats.

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Behavioral targeting

Behavioral Targeting refers to a range of technologies and techniques used by online website publishers and advertisers which allows them to increase the effectiveness of their campaigns by capturing data generated by website and landing page visitors. When it is done without the knowledge of users, it may be considered a breach of browser security and illegal by many countries’ privacy, data protection and consumer protection laws.

When a consumer visits a web site, the pages they visit, the amount of time they view each page, the links they click on, the searches they make and the things that they interact with, allow sites to collect that data, and other factors, create a ‘profile’ that links to that visitor’s web browser. As a result, site publishers can use this data to create defined audience segments based upon visitors that have similar profiles. When visitors return to a specific site or a network of sites using the same web browser, those profiles can be used to allow advertisers to position their online ads in front of those visitors who exhibit a greater level of interest and intent for the products and services being offered. On the theory that properly targeted ads will fetch more consumer interest, the publisher (or seller) can charge a premium for these ads over random advertising or ads based on the context of a site.

Behavioral marketing can be used on its own or in conjunction with other forms of targeting based on factors like geography, demographics or contextual web page content. It’s worth noting that many practitioners also refer to this process as “Audience Targeting”.

Behavioral targeting techniques may also be applied to any online property on the premise that it either improves the visitor experience or it benefits the online property, typically through increased conversion rates or increased spending levels. The early adopters of this technology/philosophy were editorial sites such as HotWired, online advertising with leading online ad servers, retail or other e-commerce website as a technique for increasing the relevance of product offers and promotions on a visitor by visitor basis. More recently, companies outside this traditional e-commerce marketplace have started to experiment with these emerging technologies.

The typical approach to this starts by using web analytics to break-down the range of all visitors into a number of discrete channels. Each channel is then analyzed and a virtual profile is created to deal with each channel. These profiles can be based around Personas that gives the website operators a starting point in terms of deciding what content, navigation and layout to show to each of the different personas. When it comes to the practical problem of successfully delivering the profiles correctly this is usually achieved by either using a specialist content behavioral platform or by bespoke software development. Most platforms identify visitors by assigning a unique id cookie to each and every visitor to the site thereby allowing them to be tracked throughout their web journey, the platform then makes a rules-based decision about what content to serve.

Again, this behavioral data can be combined with known demographic data and a visitor’s past purchase history in order to produce a greater degree of data points that can be used for targeting.

Self-learning onsite behavioral targeting systems will monitor visitor response to site content and learn what is most likely to generate a desired conversion event. Some good content for each behavioral trait or pattern is often established using numerous simultaneous multivariate tests. Onsite behavioral targeting requires relatively high level of traffic before statistical confidence levels can be reached regarding the probability of a particular offer generating a conversion from a user with a set behavioral profile. Some providers have been able to do so by leveraging its large user base, such as Yahoo!. Some providers use a rules based approach, allowing administrators to set the content and offers shown to those with particular traits.

Advertising Networks use behavioral targeting in a different way than individual sites. Since they serve many advertisements across many different sites, they are able to build up a picture of the likely demographic makeup of internet users. An example would be a user seen on football sites, business sites and male fashion sites. A reasonable guess would be to assume the user is male. Demographic analyses of individual sites provided either internally (user surveys) or externally (Comscore \ netratings) allow the networks to sell audiences rather than sites. Although advertising networks used to sell this product, this was based on picking the sites where the audiences were. Behavioral targeting allows them to be slightly more specific about this.

Many online users and advocacy groups are concerned about privacy issues around doing this type of targeting. This is a controversy that the behavioral targeting industry is trying to contain through education, advocacy and product constraints to keep all information non-personally identifiable or to obtain permission from end-users. AOL created animated cartoons in 2008 to explain to its users that their past actions may determine the content of ads they see in the future. Canadian academics at the University of Ottawa Canadian Internet Policy and Public Interest Clinic have recently demanded the federal privacy commissioner to investigate online profiling of Internet users for targeted advertising.
The European Commission (via commissioner Meglena Kuneva) has also raised a number of concerns related to online data collection (of personal data), profiling and behavioral targeting, and is looking for “enforcing existing regulation”.

In October 2009 it was reported that a recent survey carried out by University of Pennsylvania and the Berkeley Center for Law and Technology found that a large majority of US internet users rejected the use of behavioral advertising. Several research efforts by academicians and others have demonstrated that data that supposedly anonymized can be used to identify real individuals.

In March 2011, it was reported that the online ad industry would begin working with the Council of Better Business Bureaus to start policing itself as part of its program to monitor and regulate how marketers track consumers online, also known as behavioral advertising.

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Opt-in email advertising

Opt-in email advertising, or permission marketing, is a method of advertising via email whereby the recipient of the advertisement has consented to receive it. This method is one of several developed by marketers to eliminate the disadvantages of email marketing.

Opt-in email marketing may evolve into a technology that uses a handshake protocol between the sender and receiver. This system is intended to eventually result in a high degree of satisfaction between consumers and marketers. If opt-in email advertising is used, the material that is emailed to consumers will be “anticipated”. It is assumed that the consumer wants to receive it, which makes it unlike unsolicited advertisements sent to the consumer. Ideally, opt-in email advertisements will be more personal and relevant to the consumer than untargeted advertisements.

A common example of permission marketing is a newsletter sent to an advertising firm’s customers. Such newsletters inform customers of upcoming events or promotions, or new products. In this type of advertising, a company that wants to send a newsletter to their customers may ask them at the point of purchase if they would like to receive the newsletter.

With a foundation of opted-in contact information stored in their database, marketers can send out promotional materials automatically—known as Drip Marketing. They can also segment their promotions to specific market segments.

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Banner blindness

Banner blindness is a phenomenon in web usability where visitors to a website consciously or subconsciously ignore banner-like information, which can also be called ad blindness.

The term “banner blindness” was coined by Benway and Lane as a result of website usability tests where a majority of the test subjects either consciously or unconsciously ignored information that was presented in banners. Subjects were given tasks to search information on a website. The information that was overlooked included both external advertisement banners and internal navigational banners, e.g. quick links. The placement of the banners on a web page had little effect on whether or not the subjects noticed them. The result of the study contradicted the popular web design guideline that larger, colourful and animated elements on a website are more likely to be seen by users.

However, in an experiment by Bayles the results showed that users generally noticed web banners. This was proven by eye-tracking tests and other means. The experiment concentrated on how users perceived a single web page and what they could recognise and recall of it afterwards. It has been argued that experiments like this without real-world tasks have poor methodology, and produce poor results.

Pagendarm and Schaumburg argued that a possible explanation for the banner blindness phenomenon lay in the way users interacted with websites. Users tend to either search for specific information or aimlessly browse from one page to the next. Users have constructed web related cognitive schemata for different tasks on the web. This hypothesis was also suggested by Norman. When searching for specific information on a website, users focus only on the parts of the page where they assume the relevant information will be, small text and hyperlinks. Large colourful or animated banners and other graphics are in this case ignored. Usability tests that compared the perception of banners between groups of subjects searching for specific information and subjects aimlessly browsing seem to support this theory.

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Ad serving

Ad serving describes the technology and service that places advertisements on web sites. Ad serving technology companies provide software to web sites and advertisers to serve ads, count them, choose the ads that will make the website or advertiser most money, and monitor progress of different advertising campaigns.

An ad server is a computer server, specifically a web server, that stores advertisements used in online marketing and delivers them to website visitors.

The content of the webserver is constantly updated so that the website or webpage on which the ads are displayed contains new advertisements—e.g., banners (static images/animations) or text—when the site or page is visited or refreshed by a user.

In addition, the ad server also performs various other tasks like counting the number of impressions/clicks for an ad campaign and report generation, which helps in determining the ROI for an advertiser on a particular website.

Ad servers come in two flavors: local ad servers and third-party or remote ad servers. Local ad servers are typically run by a single publisher and serve ads to that publisher’s domains, allowing fine-grained creative, formatting, and content control by that publisher. Remote ad servers can serve ads across domains owned by multiple publishers. They deliver the ads from one central source so that advertisers and publishers can track the distribution of their online advertisements, and have one location for controlling the rotation and distribution of their advertisements across the web.

The first central ad server was released by FocaLink Media Services and introduced on July 17, 1995, for controlling the delivery of online advertising or banner ads. Although most contemporary accounts are no longer available online, the Weizmann Institute of Science published an academic research paper documenting the launch of the first ad server. The original motherboard for the first ad server, assembled in June 1995, is also preserved. Focalink relaunched the ad server under the name SmartBanner in February 1996. The company was founded by Dave Zinman and Jason Strober, and based in Palo Alto, California. In 1998, the company changed its name to AdKnowledge, and was purchased by CMGI in 1999. The AdKnowledge name was subsequently purchased by a company in Kansas City in 2004, which now operates under the brand name AdKnowledge.

The first local ad server was released by NetGravity in January 1996 for delivering online advertising at major publishing sites such as Yahoo and Pathfinder. The company was founded by Tom Shields and John Danner, and based in San Mateo, California. In 1998, the company went public on NASDAQ (NETG), and was purchased by DoubleClick in 1999. NetGravity AdServer was then renamed to DART Enterprise. In March 2008 Google acquired DoubleClick. Google has continued to improve and invest in DART Enterprise. The latest version of the product was renamed and shipped as DoubleClick Enterprise 8.0 on September 28, 2011.

Another central or remote ad server was introduced by David Stein at Burst! Media in January 1996 for controlling online advertising or banner ads. The company was founded by Jarvis Coffin, David Stein and Bob Hanna, and based in Katonah, New York. In 2006, the company went public on the London Stock Exchange’s Alternative Investment Market (BRST).

Ad server functionality

The typical common functionality of ad servers includes:

Uploading advertisements and rich media.
Trafficking ads according to differing business rules.
Targeting ads to different users, or content.
Tuning and optimization based on results.
Reporting impressions, clicks, post-click & post-impression activities, and interaction metrics.

Advanced functionality may include:

Frequency capping so users only see messages a limited amount of time. (Advertisers can also limit ads by setting a frequency cap on money-spending)
Sequencing ads so users see messages in a specific order (sometimes known as surround sessions).
Excluding competition so users do not see competitors’ ads directly next to one another. (Usually done by bidding on keywords)
Displaying ads so an advertiser can own 100% of the inventory on a page (sometimes known as Roadblocks).
Targeting ads to users based on their previous behavior (behavioral marketing or behavioral targeting).
Targeting specific IP-addresses i.e. targeting specific individuals or companies

Ad targeting and optimization

One aspect of ad serving technology is automated and semi-automated means of optimizing bid prices, placement, targeting, or other characteristics. Significant methods include:

Behavioral Targeting – Using a profile of prior behavior on the part of the viewer to determine which ad to show during a given visit. For example, targeting car ads on a portal to a viewer that was known to have visited the automotive section of a general media site.
Contextual Targeting – (also known as Semantic targeting) Inferring the optimum ad placement from information contained on the page where the ad is being served. For example, placing Mountain Bike ads automatically on a page with a mountain biking article.
Creative Optimization – Using experimental or predictive methods to explore the optimum creative for a given ad placement and exploiting that determination in further impressions.

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Clickthrough rate

Clickthrough rate (CTR) is a way of measuring the success of an online advertising campaign for a particular website. The clickthrough rate of an advertisement is defined as the number of clicks on an ad divided by the number of times the ad is shown (impressions), expressed as a percentage. For example, if a banner ad is delivered 100 times (100 impressions) and receives one click, then the clickthrough rate for the advertisement would be 1%.

Click-through rates for banner ads have fallen over time. When banner ads first started to appear, it was not uncommon to have rates above five percent. They have fallen since then, currently averaging closer to 0.2 or 0.3 percent. In most cases, a 2% click-through rate would be considered very successful, though the exact number is hotly debated and would vary depending on the situation. The average click-through rate of 3% in the 1990s declined to 0.28% by 2003. Since advertisers typically pay more for a high click-through rate, getting many click-throughs with few purchases is undesirable to advertisers. Similarly, by selecting an appropriate advertising site with high affinity (e.g. a movie magazine for a movie advertisement), the same banner can achieve a substantially higher CTR. Though personalized ads, unusual formats, and more obtrusive ads typically result in higher click-through rates than standard banner ads, overly intrusive ads are often avoided by viewers.

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Cost per action

Cost Per Action or CPA (sometimes known as Pay Per Action or PPA) is an online advertising pricing model, where the advertiser pays for each specified action (a purchase, a form submission, and so on) linked to the advertisement.

Direct response advertisers consider CPA the optimal way to buy online advertising, as an advertiser only pays for the ad when the desired action has occurred. An action can be a product being purchased, a form being filled, etc. The desired action to be performed is determined by the advertiser. Radio and TV stations also sometimes offer unsold inventory on a cost per action basis, but this form of advertising is most often referred to as “per inquiry.”

The CPA can be determined by different factors, depending where the online advertising inventory is being purchased.

CPA is sometimes referred to as “Cost Per Acquisition”, which has to do with the fact that most CPA offers by advertisers are about acquiring something (typically new customers by making sales). Using the term “Cost Per Acquisition” instead of “Cost Per Action” is not incorrect in such cases, as not all “Cost Per Action” offers can be referred to as “Cost Per Acquisition”.

Online and Offline advertising payment model in which fees are charged based solely on the delivery of qualified leads.

In a pay per lead agreement, the advertiser only pays for leads delivered under the terms of the agreement. No payment is made for leads that don’t meet the agreed upon criteria.

Leads may be delivered by phone under the pay per call model. Conversely, leads may be delivered electronically, such as by email, SMS or a ping/post of the data directly to a database. The information delivered may consist of as little as an email address, or it may involve a detailed profile including multiple contact points and the answers to qualification questions.

There are numerous risks associated with any Pay Per Lead campaign, including the potential for fraudulent activity by incentivized marketing partners. Some fraudulent leads are easy to spot. Nonetheless, it is advisable to make a regular audit of the results.

Differences between CPA and CPL advertising

In CPL campaigns, advertisers pay for an interested lead (hence, Cost Per Lead) — i.e. the contact information of a person interested in the advertiser’s product or service. CPL campaigns are suitable for brand marketers and direct response marketers looking to engage consumers at multiple touchpoints — by building a newsletter list, community site, reward program or member acquisition program.

In CPA campaigns, the advertiser typically pays for a completed sale involving a credit card transaction.

There are other important differentiators:

1.CPL campaigns are advertiser-centric. The advertiser remains in control of their brand, selecting trusted and contextually relevant publishers to run their offers. On the other hand, CPA and affiliate marketing campaigns are publisher-centric. Advertisers cede control over where their brand will appear, as publishers browse offers and pick which to run on their websites. Advertisers generally do not know where their offer is running.
2.CPL campaigns are usually high volume and light-weight. In CPL campaigns, consumers submit only basic contact information. The transaction can be as simple as an email address. On the other hand, CPA campaigns are usually low volume and complex. Typically, consumer has to submit credit card and other detailed information.

Effective cost per action

A related term, eCPA or Effective Cost Per Action, is used to measure the effectiveness of advertising inventory purchased (by the advertiser) via a CPC, CPI, or CPM basis.

In other words, the eCPA tells the advertiser what they would have paid if they had purchased the advertising inventory on a Cost Per Action basis (instead of a Cost Per Click, Cost Per Impression, or Cost Per Mille/Thousand basis).

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Cost per Thousand Viewable ads (CPMV)

Cost per mille (CPM), also called cost ‰ and cost per thousand (CPT) (in Latin mille means thousand), is a commonly used measurement in advertising. Radio, television, newspaper, magazine, out-of-home advertising, and online advertising can be purchased on the basis of what it costs to show the ad to one thousand viewers. It is used in marketing as a benchmark to calculate the relative cost of an advertising campaign or an ad message in a given medium. Rather than an absolute cost, CPM estimates the cost per 1000 views of the ad. This traditional form of measuring advertising success can also be used in tandem with performance based models such as percentage of sale, or cost per acquisition (CPA).

In online advertising, if a website sells banner ads for a $10 CPM, that means it costs $10 to show the banner on 1000 page views.

Effective cost per mille (eCPM) is used to measure the effectiveness of a publisher’s inventory being sold (by the publisher) via a CPA, CPC, or CPT basis. In other words, the eCPM tells the publisher what they would have received if they sold the advertising inventory on a CPM basis (instead of a CPA, CPC, or CPT basis). This information can be used to compare revenue across channels that may have widely varying traffic – by figuring the earnings per thousand.

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Cost per impression

Cost per impression, often abbreviated to CPI or CPM (Cost per mille) are phrases used in online advertising and marketing related to web traffic. They refer to internet marketing campaigns where advertisers pay for every time that their advert is displayed to a user usually in the form of a banner ad on a website, but can also refer to advertisements in Email advertising.

An impression describes the instance when an advert is downloaded by a user while viewing a web page. A single web page may contain multiple adverts and in such cases a single pageview would result in one impression for each advert displayed to that user. In order to count the impressions served as accurately as possible and prevent fraud, an ad server may exclude certain non-qualifying activities such as page-refreshes or other user actions from counting as impressions. When advertising rates are described as CPM or CPI, this is the amount paid for every thousand qualifying impressions served.

Cost per mille is one of the most common marketing practice used on the internet along with Cost per click (CPC/PPC) and Cost per action (CPA) (including CPL and CPS). CPM advertising is often preferred by publishers because they can be more certain about the revenue they will generate from their website traffic, but CPM can be compared with different marketing strategies by examining their Effective cost per mille (eCPM). eCPM informs the publisher what they would have received if they sold the advertising inventory on a CPM basis by taking into account the Clickthrough rate (CTR) and/or Conversion rate (CVR) of the campaigns.

Cost per mille is the closest online advertising strategy to those offered in the more traditional media such as on television or in print which sell advertising based on estimated viewership or readership, and as such is popular with advertisers as it is simple to measure campaigns and can be compared and contrasted with their advertising in other media.

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An Introduction to “Pay per click”

Pay per click (PPC) (also called Cost per click) is an Internet advertising model used to direct traffic to websites, where advertisers pay the publisher (typically a website owner) when the ad is clicked. With search engines, advertisers typically bid on keyword phrases relevant to their target market. Content sites commonly charge a fixed price per click rather than use a bidding system. PPC “display” advertisements are shown on web sites or search engine results with related content that have agreed to show ads. This approach differs from the “pay per impression” methods used in television and newspaper advertising.

In contrast to the generalized portal, which seeks to drive a high volume of traffic to one site, PPC implements the so-called affiliate model, that provides purchase opportunities wherever people may be surfing. It does this by offering financial incentives (in the form of a percentage of revenue) to affiliated partner sites. The affiliates provide purchase-point click-through to the merchant. It is a pay-for-performance model: If an affiliate does not generate sales, it represents no cost to the merchant. Variations include banner exchange, pay-per-click, and revenue sharing programs.

Websites that utilize PPC ads will display an advertisement when a keyword query matches an advertiser’s keyword list, or when a content site displays relevant content. Such advertisements are called sponsored links or sponsored ads, and appear adjacent to or above organic results on search engine results pages, or anywhere a web developer chooses on a content site.

Among PPC providers, Google AdWords, Yahoo! Search Marketing, and Microsoft adCenter are the three largest network operators, and all three operate under a bid-based model.

The PPC advertising model is open to abuse through click fraud, although Google and others have implemented automated systems to guard against abusive clicks by competitors or corrupt web developers.

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