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Targeted advertising is a form of advertising , including online advertising , that is directed towards an audience with certain traits, based on the product or person the advertiser is promoting. Targeted advertising is concentrated in certain traits and consumers who are likely to have a strong preference.
These individuals will receive messages instead of those who have no interest and whose preferences do not match a particular product’s attributes.
This eliminates waste. Traditional forms of advertising, including billboards , newspapers, magazines, and radio channels, are progressively becoming replaced by online advertisements. In the next generation’s advertising, the importance of targeted advertisements will radically increase, as it spreads across numerous ICT channels cohesively. Through the emergence of new online channels, the usefulness of targeted advertising is increasing because companies aim to minimize wasted advertising by means of information technology.
Web services are continually generating new business ventures and revenue opportunities for internet corporations. Companies have rapidly developed technological capabilities that allow them to gather information about web users.
Most of today’s websites are using these targeting technologies to track users’ internet behavior and there is much debate over the privacy issues present. Search engine marketing uses search engines to reach target audiences. For example, Google ‘s Remarketing Campaigns are a type of targeted marketing where advertisers use the IP addresses of computers that have visited their websites to remarket their ad specifically to users who have previously been on their website whilst they browse websites that are a part of the Google display network , or when searching for keywords related to a product or service on the Google search engine.
Google Ads includes different platforms. The Search Network displays the ads on ‘ Google Search , other Google sites such as Maps and Shopping, and hundreds of non-Google search partner websites that show ads matched to search results’. For example, the search network can benefit a company with the goal of reaching consumers actively searching for a particular product or service. Other ways advertising campaigns are able to target the user is to use browser history and search history.
For example, if the user types promotional pens into a search engine such as Google, ads for promotional pens will appear at the top of the page above the organic listings.
These ads will be geo-targeted to the area of the user’s IP address, showing the product or service in the local area or surrounding regions. The higher ad position is often rewarded to the ad having a higher quality score. When ranked based on these criteria, it will affect the advertiser by improving ad auction eligibility, the actual cost per click CPC , ad position, and ad position bid estimates; to summarise, the better the quality score, the better ad position, and lower costs.
Google uses its display network to track what users are looking at and to gather information about them. When a user goes to a website that uses the Google display network, it will send a cookie to Google, showing information on the user, what he or she searched, where they are from, found by the IP address, and then builds a profile around them, allowing Google to easily target ads to the user more specifically.
For example, if a user went onto promotional companies’ websites often, that sell promotional pens, Google will gather data from the user such as age, gender, location, and other demographic information as well as information on the websites visited, the user will then be put into a category of promotional products, allowing Google to easily display ads on websites the user visits relating to promotional products.
Social media targeting is a form of targeted advertising, that uses general targeting attributes such as geotargeting , behavioral targeting, socio-psychographic targeting, and gathers the information that consumers have provided on each social media platform. According to the media users’ view history, customers who are interested in the criteria will be automatically targeted by the advertisements of certain products or service.
Social media also creates profiles of the consumer and only needs to look at one place, the user’s profile, to find all interests and ‘likes’. Facebook lets advertisers target using broad characteristics like gender, age, and location. Furthermore, they allow more narrow targeting based on demographics, behavior, and interests see a comprehensive list of Facebook’s different types of targeting options . Advertisements can be targeted to specific consumers watching digital cable  or over-the-top video.
Political campaigns may also match against public records such as party affiliation and which elections and party primaries the view has voted in. Since the early s, advertising has been pervasive online and more recently in the mobile setting. Targeted advertising based on mobile devices allows more information about the consumer to be transmitted, not just their interests, but their information about their location and time. This is when advertisers put ads in a specific place, based on the relative content present.
This targeting method can be used across different mediums, for example in an article online, purchasing homes would have an advert associated with this context, like an insurance ad. This is usually achieved through an ad matching system that analyses the contents on a page or finds keywords and presents a relevant advert, sometimes through pop-ups.
This can result in placing contradictory adverts, which are not appropriate to the content. Technical targeting is associated with the user’s own software or hardware status. The advertisement is altered depending on the user’s available network bandwidth, for example, if a user is on their mobile phone that has limited connection, the ad delivery system will display a version of the ad that is smaller for a faster data transfer rate. Addressable advertising systems serve ads directly based on demographic, psychographic, or behavioral attributes associated with the consumer s exposed to the ad.
These systems are always digital and must be addressable in that the endpoint which serves the ad set-top box , website, or digital sign must be capable of rendering an ad independently of any other endpoints based on consumer attributes specific to that endpoint at the time the ad is served. Addressable advertising systems, therefore, must use consumer traits associated with the endpoints as the basis for selecting and serving ads.
According to the Journal of Marketing , more than 1. With this astounding buyer trend, it is important for advertisers to choose the right time to schedule content, in order to maximize advertising efficiency.
To determine what time of day is most effective for scheduling content, it is essential to know when the brain is most effective at retaining memory. Research in chronopsychology has credited that time-of-day impacts diurnal variety in a person’s working memory accessibility and has discovered the enactment of inhibitory procedures to build working memory effectiveness during times of low working memory accessibility. Working memory is known to be vital for language perception , learning , and reasoning   providing us with the capacities of putting away, recovering, and preparing quick data.
For many people, working memory accessibility is good when they get up toward the beginning of the day, most reduced in mid-evening, and moderate at night. Sociodemographic targeting focuses on the characteristics of consumers. This includes their age, generation, gender, salary, and nationality.
Facebook and other social media platforms uses this form of targeting by showing advertisements relevant to the user’s individual demographic on their account, this can show up in forms of banner ads, mobile ads, or commercial videos. This type of advertising involves targeting different users based on their geographic location. IP addresses can signal the location of a user and can usually transfer the location through ZIP codes. A location-based service LBS is a mobile information service that allows spatial and temporal data transmission and can be used to an advertiser’s advantage.
Although producing advertising off consumer’s location-based services can improve the effectiveness of delivering ads, it can raise issues with the user’s privacy. Advertisers using this method believe it produces ads that will be more relevant to users, thus leading consumers to be more likely influenced by them. Its advantage is that it can target individual’s interests, rather than target groups of people whose interests may vary. 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, to 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 marketers and advertisers to position their online ads and messaging in front of those visitors who exhibit a greater level of interest and intent for the products and services being offered.
Behavioral targeting has emerged as one of the main technologies used to increase the efficiency and profits of digital marketing and advertisements, as media providers are able to provide individual users with highly relevant advertisements. On the theory that properly targeted ads and messaging will fetch more consumer interest, publishers can charge a premium for behaviorally targeted ads and marketers can achieve.
Behavioral marketing can be used on its own or in conjunction with other forms of targeting. Major advantages of Behavioral marketing are that it will help in reaching surfers with affinity, reach surfers that were not exposed to a media campaign, contact surfers close to conversion and in reconnecting with prospects or customers.
Behavioral targeting may also be applied to any online property on the premise that it either improves the visitor experience or benefits the online property, typically through increased conversion rates or increased spending levels. 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 or behavioral 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 give 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.
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 a 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 their 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. Some servers even record the page that referred you to them, websites you visit after them, which ads you see and which ads you click on.
This data is collected without attaching the people’s names, address, email address or telephone number, but it may include device identifying information such as the IP address, MAC address , cookie or other device-specific unique alphanumerical ID of your computer, but some stores may create guest IDs to go along with the data. Cookies are used to control displayed ads and to track browsing activity and usage patterns on sites.
This data is used by companies to infer people’s age, gender, and possible purchase interests so that they could make customized ads that you would be more likely to click on. 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. Behavioral targeting allows them to be slightly more specific about this. In the work titled An Economic Analysis of Online Advertising Using Behavioral Targeting,  Chen and Stallaert study the economic implications when an online publisher engages in behavioral targeting.
They consider that the publisher auctions off an advertising slot and are paid on a cost-per-click basis. Chen and Stallaert identify the factors that affect the publisher’s revenue , the advertisers’ payoffs, and social welfare. They show that revenue for the online publisher in some circumstances can double when behavioral targeting is used. Increased revenue for the publisher is not guaranteed: in some cases, the prices of advertising and hence the publisher’s revenue can be lower, depending on the degree of competition and the advertisers’ valuations.
They identify two effects associated with behavioral targeting: a competitive effect and a propensity effect. The relative strength of the two effects determines whether the publisher’s revenue is positively or negatively affected.
Chen and Stallaert also demonstrate that, although social welfare is increased and small advertisers are better off under behavioral targeting, the dominant advertiser might be worse off and reluctant to switch from traditional advertising. In , BlueLithium now Yahoo!
Advertising in a large online study, examined the effects of behavior targeted advertisements based on contextual content. The study used million “impressions”, or advertisements conveyed across behavioral and contextual borders. Specifically, nine behavioral categories such as “shoppers” or “travelers”  with over 10 million “impressions” were observed for patterns across the content.