Types of Online Marketing

Types of Online Marketing

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. By tracking and monitoring what websites users visit, internet service providers can directly show ads that are relative to the consumer's preferences. 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

Further information: Search engine marketing

No alt text provided for this image

Search engine marketing uses search engines to reach target audiences. For example, Google's Google Remarketing Campaigns are a type of targeted advertising where websites use the IP addresses of computers that have visited their websites to remarket their ad specifically to the user who has previously been on their website as they use 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. Dynamic remarketing can improve the targeted advertising as the ads are able to include the products or services that the consumers have previously viewed on the advertisers' website within the ads.

Google Adwords have different platforms how the ads appear. 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 AdWords ads matched to search results'. 'The Display Network includes a collection of Google websites (like Google FinanceGmailBlogger, and YouTube), partner sites, and mobile sites and apps that show AdWords ads matched to the content on a given page.' These two kinds of Advertising networks can be beneficial for each specific goal of the company, or type of company. For example, the search network can benefit a company with the goal of reaching consumers 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 typed in promotional pens in a search engine, such as Google; ads for promotional pens will appear at the top of the page above the organic pages, these ads will be targeted to the area of the users IP address, showing the product or service in the local area or surrounding regions, the higher ad position is a benefit of the ad having a higher quality score. The ad quality is affected by the 5 components of the quality score:

  • The ad's expected click-through rate
  • The quality of the landing page
  • The ad/search relevance
  • Geographic performance
  • The targeted devices

When ranked based on these criteria, it will affect the advertiser by improving ad auction eligibility, 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 onto 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. these types of adverts are also called behavioral advertisements as they track the website behavior of the user and displays ads based on previous pages or searched terms. ("Examples Of Targeted Advertising")

No alt text provided for this image

Social media targeting

Further information: Social media marketing

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 stuff will be automatically targeted by the advertisements of certain products or service. For example, on Facebook, if a consumer has liked clothing pages they will receive ads based on those page likes and the area they have said they live in, this allows advertisers to target very specific consumers as they can specify cities and interests to their needs. Social media also creates profiles of the consumer and only needs to look at one place, one the users' profile to find all interests and 'likes'.

E.g. 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 option

Television

Advertisements can be targeted to specific consumers watching digital cable or over-the-top video. Targeting can be done according to age, gender, location, or personal interests in films, etc. Cable box addresses can be cross-referenced with information from data brokers like AcxiomEquifax, and Experian, including information about marriage, education, criminal record, and credit history. Political campaigns may also match against public records such as party affiliation and which elections and party primaries the view has voted in.

Mobile devices

Since the early 2000s, 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 allows advertisers to produce advertisements that could cater to their schedule and a more specific changing environment.

No alt text provided for this image

Content and contextual targeting

Further information: Content marketing

The most straightforward method of targeting is content/contextual targeting. This is when advertisers put ads in a specific place, based on the relative content present. Another name used is content-oriented advertising, as it is corresponding to the context being consumed. 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 which analyses the contents on a page or finds keywords and presents a relevant advert, sometimes through pop-ups. Though sometimes the ad matching system can fail, as it can neglect to tell the difference between positive and negative correlations. This can result in placing contradictory adverts, which are not appropriate to the content.

Technical targetingEdit

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.

No alt text provided for this image

Time targeting

According to the journal of marketing, more than 1.8 billion clients spent a minimum of 118 minutes daily- via web-based networking media in 2016. Nearly 77% of these clients interact with the content through likes, commenting, and clicking on links related to content. 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 accurately 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 Chrono psychology 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 a "cerebrum framework that gives brief stockpiling and control of the data essential for such complex subjective undertakings as language perception, learning, and thinking" (Baddeley 1992, p. 556). Providing us with the vital capacities of putting away, recovering, and preparing quick data. For a great many people, working memory accessibility is most noteworthy when they get up toward the beginning of the day, most reduced in mid-evening, and moderate at night (Lupien et al. 2005).

Sociodemographic targeting

Sociodemographic targeting focuses on the characteristics of consumers, including their age, generation, gender, salary and nationality. The idea is to target users specifically, using this data about them collected, for example, targeting a male in the age bracket of 18–24. Facebook 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, or commercial videos.

Geographical and location-based targeting

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. Locations are then stored for users in static profiles, thus advertisers can easily target these individuals based on their geographic location. A location-based service (LBS) is a mobile information service which allows spatial and temporal data transmission and can be used to an advertiser's advantage. This data can be harnessed from applications on the device that allow access to the location information. This type of targeted advertising focuses on localizing content, for example, a user could be prompted with options of activities in the area, for example, places to eat, nearby shops, etc. 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.

Behavioral targeting

Behavioral targeting is centered around the activity/actions of users, and is more easily achieved on web pages.Information from browsing websites can be collected from data mining, which finds patterns in users search history. Advertisers using this method believe it produces ads that will be more relevant to users, thus leading consumers be more likely influenced by them. If a consumer was frequently searching for plane ticket prices, the targeting system would recognise this and start showing related adverts across unrelated websites, such as airfare deals on Facebook. 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,[12]) Many practitioners also refer to this process as "audience 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.

Onsite

See also: FTC regulation of behavioral advertising

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. 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 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 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.

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 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.

Network

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. Data from a visit to one website can be sent to many different companies, including Microsoft and Google subsidiaries, FacebookYahoo, many traffic-logging sites, and smaller ad firms. This data can sometimes be sent to more than 100 websites, and shared with business partners, advertisers, and other third parties for business purposes. The data is collected using cookies, web beacons and similar technologies, and/or a third-party ad serving software, to automatically collect information about site users and site activity. 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.

Online advertising uses cookies, a tool used specifically to identify users, as a means of delivering targeted advertising by monitoring the actions of a user on the website. For this purpose, the cookies used are called tracking cookies. An ad network company such as Google uses cookies to deliver advertisements that are relevant to the interests of the user, control the number of times that the user sees an ad and "measure" whether they are advertising the specific product to the customer's preferences.

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. 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 were 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.

Theoretical research

In the work titled An Economic Analysis of Online Advertising Using Behavioral Targeting, Chen and Stallaert (2014) 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 (2014) 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 (2014) 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 2006, BlueLithium (now Yahoo! Advertising) in a large online study, examined the effects of behavior targeted advertisements based on contextual content. The study used 400 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.

All measures for the study were taken in terms of click-through rates (CTR) and "action-through rates" (ATR), or conversions. So, for every impression that someone gets, the number of times they "click-through" to it will contribute to CTR data, and every time they go through with or convert on the advertisement the user adds "action-through" data. Results from the study show that advertisers looking for traffic on their advertisements should focus on behavioral targeting in context. Likewise, if they are looking for conversions on the advertisements, behavioral targeting out of context is the most effective process. The data was helpful in determining an "across-the-board rule of thumb"; however, results fluctuated widely by content categories. Overall results from the researchers indicate that the effectiveness of behavioral targeting is dependent on the goals of the advertiser and the primary target market the advertiser is trying to reach


要查看或添加评论,请登录

社区洞察

其他会员也浏览了