Many people have been victims of ineffective advertisements through pop-ups, which have invaded their computers screens and mobile device such as smartphones and tablets. Using a set of sensors placed on bodies, tools and equipment and other devices, in addition to people’s social networks, it is possible to collect information, which can in turn be used in delivery of relevant ads, which resonate with people’s feelings, moods, time and place, displaying them on our wireless devices. Advertisements on personal items such as body lotions, as well as foods can benefit from the sensors and social media, as they sense the type of skin and possibility of allergies to some foods, while the social media becomes a source of information for the preferred brand. By extension, the distinction of the sensors go to personalized ads according to time and place, as well as call for assistance to network of friends during an emergency. Such information can then be used to deliver accurately targeted advertisements.
Advertising pop-ups on screens, smartphones and tablets can be a nuisance, especially when the goods being advertised are of no relevance to the user. With such irritation, the idea of predictive advertising sounds like a great idea, as it allows the display of advertisements based on the user’s preferences, tastes and location (Popescu 2013). People share tons of information about themselves over the social media and through internet browsing, using this information, as well as the Internet of Things (IOT) through sensors attached to wearable devices, tools and equipment and the body, it is possible to develop more targeted and relevant advertisements, which resonate with users. This is possible especially with technologies that are capable of determining skin types and possibilities of allergies. This paper will look at the need for the new technology and its potential to change the world at its launch. It will additionally give an in depth overview of the technology.
2.0 Need for Targeted Advertisement using Social Networks and IOT
The current advertising market relies on personal user data collected through user demographics, browsing and purchase history, geographic location and information gleaned from preference surveys (Schumann, Wangenheim & Groene 2014, p. 3). Such statistics enable advertisers to display advertisements that they think are applicable to the user (Hoelzel 2014). Currently, such measures have been successful, making targeted advertising a marketing trend with projected $2.6 billion in spending on such advertisement (Schumann, Wangenheim & Groene 2014, p. 3).
However, many are the times when advertisements are irrelevant and irritating. Such advertisements can be intrusive (Popescu 2013), given that the information on the user’s preference, needs and moods are usually changing, information that may not be captured and processed fast enough by the analytic software used. It is for this reason therefore that targeted advertisement that collects information from users’ social networks, devices and sensors embedded on different devices as well as the user’s body is more relevant and effective.
The distinctive nature of using the sensors is that they give accurate information about the user. Given that the sensor are attached to the body, they are capable of relaying information about the user’s body such as allergies, skin type (whether dry or oily), and therefore suggest the best products according to these parameters. The need for accuracy in the advertisements, more functionality of connecting with the user’s friends or relative in case of a problem or the authorities therefore calls for advanced personalized advertisement and a deeper integration of the sensors with the user’s body and social networks.
3.0 Overview of Targeted Advertisement using Social Networks and IOT
Current technologies for targeted advertising use user data to present the most relevant advertisement according to the data collected on the user (Amir 2014, p. 45; Schumann, Wangenheim & Groene 2014, p. 3). Data is usually analyzed using algorithms, which in the end give advertisers information on patterns of shopping, internet use and places that the user visits. This information is gathered from the user’s internet activity, shopping, travelling destinations, as well as other places that the user has shown interest. Advertisers are then capable of making suggestions for travel destinations, new product arrivals, and even make and mail a catalogue with some of the items that the user has been interested in, or has bought over a duration.
Armed with the information, advertisers then follow users across the different devices that they use; smartphones, PCs and tablets (Leber 2012). Using the social networks and the processed information as a guide, the advertisements can be relevantly targeted to suit the user’s mood, location as well as the geographical region.
4.0 Towards an Accurately Targeted Advert World
Even with such the bulk of information collected by advertisers, it is possible that the advertisements will sometimes not resonate with the users. However, using sensors attached to the body and devices around the user it is possible to target users accurately with advertisement that not only resonate with their preferences, but also are well suited for them. The sensors, collecting information from the social networks and processing them, then filter the user’s likes and preferences based on the processing of human changes within the user’s body. The synthesized information from both the social network and the user’s body can then be used to single out only advertisements that resonate with the user’s location, moods, preferences and taste, with an extension to the user’s body type and health. The user will therefore not get adverts on peanut when they allergic to them, or sugary foods when they have diabetes. The idea is to get precise advertising; therefore, expectant mothers can be sure to get adverts on baby items, magazines on motherhood as well as information on facilities dealing with parenthood.
The sensors attached to the user’s body are also sensitive the user’s environment and can be used to send discrete information via the social network to the user’s network of friends when the user is in trouble. By sensing changes in the user’s heartbeat and adrenaline levels, and sensing impact on the user’s body, for example in an attack, these sensors can send SOS messages to the user’s friends, especially those with whom the user is in constant communication. This way, the sensor’s, through social media can help save lives.
Yet these sensors and social network do not stop at that; users with medical conditions can plan appointments and schedule taking of drugs; the technology therefore synchronizes with the user’s calendar to extend its use and relevance with the user. Given that they are embedded on the body of the user, they can easily remind the user through notifications on scheduled appointments with doctors, as well as on taking drugs. In case the user’s condition gets worse and they are not able to call for help, the sensors can easily contact the user’s network of friends to ask for help on behalf of the user.
This technology offers a promise of relevantly targeted advertising. It offers an opportunity to both advertisers and users in relevance of content in time, place and location. The fact that computing has changed over the past few years to become more mobile across different devices makes, this technology cutting-edge and relevant across different devices, offering a promise for better advertising. It brings a promise of value and relevance to users and revenue to advertisers (Popescu 2013). Additionally, it hopes to keep users safe from attacks, and acts as a personal assistant to the user at different situations.
Targeted advertising offers a promise, by cutting across the board of several devices, of relevance and none irritation over pop-up and irrelevant advertisements. By using IOT and social networks, targeted advertising filters adverts ensuring that only those relevant to the user appear on the user’s screen. This presents a win-win situation for both the advertisers and users, who have higher chances of getting clicks and purchases, and finding items relevant to their preferences and taste respectively. The attachment of sensor on users’ bodies ensures even more accuracy, and by extension safety on the part of the users, for not only advertisements, but at different situation that the user may find him/herself in. Therefore, it is much better to get relevant adverts suited to personal taste and preference based on accurate data, than a plethora of adverts that are irrelevant and therefore irritating to the user.
Amir, Imran, A. 2014. “Effects of Pre-Purchase Search Motivation on User Attitude toward Online Social Network Advertising: A Case of University Students.” Journal of Competitiveness, vol. 6, no. 2, pp. 42-55
Hoelzel, Mark. 2014. “The Future of Social Media Advertising: Programmatic, Mobile and Improved Analytics Fuel Aggressive Spending.” Business Insider. Available at http://www.businessinsider.com/social-media-advertising-industry-growth-2014-9
Leber, Jessica 2012. “Drawbridge, From an Ex-Google Scientist, Lets Ads Follow You Between Devices.”MIT Technology Review. Available at: http://www.technologyreview.com/news/508176/get-ready-for-ads-that-follow-you-from-one-device-to-the-next/ [Accessed 26 Oct. 2014].
Popescu, Adam. 2013. “The Next Wave of Ads Knows Everything About You — Before You Do.” Mashable. Available at: http://mashable.com/2013/07/26/inference-advertising/ [Accessed 24 Oct. 2014].
Schumann, Jan, H., Wangenheim, Florian von & Groene, Nicole. 2014. “Targeted Online Advertising: Using Reciprocity Appeals to Increase Acceptance Among Users of Free Web Services.” Journal of Marketing. Available at: http://journals.ama.org/doi/abs/10.1509/jm.11.0316 [Accessed 26 Oct. 2014].