Article Preview
Top1. Introduction
Marketing research has always looked for specific components of proposed marketing plans that are performing better than others. These components can be the missing recipe which can forge a stronger bond between marketers and consumers, thus increasing the consistency, speed and control of brand communications leading to a competitive advantage over other organizations. Unfortunately, the vast majority of marketers lack the time, data, wherewithal, or inclination to create this knowledge. As a result, marketers are forced to allocate marketing investments in a vacuum using outdated strategies and tactics such as segmentation of markets and then targeting all customers in a particular region or people with a particular interest. Recent changes in media have made it both undesirable, and effectively impossible, to reach a given target audience with conventional mass-marketing tactics.
Many different flavors of online communities have surfaced over the years. However within the last few years, newly created communities are offering more rich interaction. These marketing strategies allow conversation, connection, and a sense of community among its members. If marketing content can be sent to those interested, that will lead to steadiness, swiftness and direct control over brand communications. The consumers who remain virtually connected to the advertised company's link are the ones who are most interested in who the company is, and what it has to offer and therefore more focused marketing of these groups are preferred.
This paper proposes techniques to market the right product to the most suitable group of online users using the data gathered from their group memberships and their corresponding social graph. Traditional offline channels of marketing products and services are important functions of business activities and more importantly extending these channels to include electronic marketing or e-marketing activities requires appropriate preparation, planning, and careful implementation. There are a number of different ways a marketer can brand their products or services. Yet, if the right advertisement reaches the right potential customer through the right channel at the right time, then competitive advantage and boosted sales will be a definite result. Marketers are always on the lookout for new data about the market. An excellent platform for Marketing is the World Wide Web in general and Social Networking platforms in specific. Social Networking can help the marketer identify a targeted marketing campaign based on almost true information gathered from people’s profile which are publicly accessible.
The current marketing strategies are the traditional ones which are used regularly and have been used over the years. First, markets are segmented - which is that markets are broken into fragments or parts by different aspects of customers like demographics, geographies, customer tastes and preferences. After segmenting, some of the market segments are chosen which have some potential for a company which is going to market a product or service to the customers. This is called target marketing, where markets are targeted. Once the target markets are chosen, these markets are positioned relatively with the products or services by a company in relation to competitors products and this way a product or a service occupies the mind of a customer and the marketing campaign reaches the customer which was part of the targeted market. Now with Web 2.0 and Web 3.0, new and effective marketing techniques are coming up and are being discussed. In this paper we will also discuss a new marketing technique which is marketing through social networks like FaceBook. In this paper, we discuss a set of Algorithms to extract customer’s details from social networking websites such as FaceBook and then store it in a database which has the design similar to those in companies like Google. The data in these tables are based on the users’ interest and the weight of their usage. Based on the stored data, we will try to intersect the customers details to customize the online campaigns and identify the key users for certain products. After the right target is well identified, a targeted spam is initiated which has much less network consumption than traditional spam marketing strategies.
The rest of this paper is organized as follows. Section 2 introduces the inter-browsing history recording techniques. Section 3 discussed some lessons learnt from Google and how they can be utilized for social networking targeted marketing. Section 4 presents our proposed algorithms and Section 5 shows some experimental results. Section 6 presents some research work related to the proposed techniques. We conclude this paper in Section 7 with some possible future directions.