¶ … product is a software application that gathers information from consumers via credit and debit card purchases. This information is then used to predict future purchases. This application is basically an extension of the buyer predictive software that is used by many online retailers already, except that is uses a broader purchasing pattern, giving more data points when compared with current applications on the market. Where Amazon might use past Amazon purchases to predict future purchases, this software would use all debit and credit purchases, thereby improving its predictive power.
This application is useful for retail marketers. These marketers will benefit from the app's predictive power, as it will help them to better target customers. The software, therefore, increases the efficiency of advertising as measured by return on investment. This benefit is superior to existing similar applications on the market because there are more data points, from multiple vendors. This provides a clearer picture of the buying patterns of each individual, which allows for more accurate targeting.
The software works by gathering information from credit and debit card companies through their point of purchase software. The data is then aggregated across the different retail stores and online retailers. Furthermore, where possible the data is linked across multiple cards, by social security number, name/address or some other distinct variable. The results are then analyzed to find patterns, and these results are expected to have greater predictive powers than other similar apps because for each customer there will be more data points.
Company Description
Our company has a pre-existing business, but this venture is an intrapreneurial effort within that business. Thus, we are already equipped with an allotment of capital, some talent and established customer contacts. These are all things that will help us to be able to grow more quickly than if this was a start-up. In senior management can be convinced that this project has a high enough ROI, we will have access to considerable resources to make this project succeed.
Industry Overview
Marketing in the United States is the driver of entire industries. Advertising is worth $171 billion in the United States (eMarketer, 2013). The main customers in this industry are manufacturers and retails, who are seeking to reach the consumer market. With the large amount of money that is spent, it is important for these firms to maximize their efficiency. With an Olympics, World Cup and midterm elections, it is expected that 2014 will be a year of strong growth in the business. The industry will also benefit from modest improvement in the economy, which should spur an increase in consumer spending. The biggest growth segment in advertising is mobile, which is expected to nearly double in size by 2017 (eMarketer, 2013).
Firms that provide business intelligence to enhance advertiser outcomes typically enjoy tremendous success. The leader in this industry today is Google, but several other online firms have also been successful, including software providers. Online is the biggest market for this sort of business intelligence because of the ability for companies to gather vast amounts of data. This trend, known as Big Data, is where our company will make its mark, by bringing the most refined, useful Big Data to the market (Bradbury & Anderson, 2013).
Target Market
The application will provide our company with data that we will then send. Our target market will consist of advertisers. These are generally going to be medium or large retailers. This is because we are seeking to predict consumer retail buying patterns. The retailers will need to be large enough to get value from our data, and have the means to buy. We estimate that our target market contains many of the nation's largest advertisers. We are also going to target the competitors of these large advertisers, companies that feel that a technological edge is going to be critical to their success in the long-run.
The value of the target market is quite high. Our services will be priced based on the value we offer customers, but using Google as a reference point, the target market is worth tens of billions per year. The key selling point to attract this market will be our superior data. There is some price elasticity of demand. Our customers have substitution options and will compare our service against those options in order to determine where the best cost-benefit ratio lies. As long as we have the best cost-benefit ratio, we can expect low price elasticity of demand, but when our cost-benefit ratio is closer to that of the competition, price elasticity of demand is going to be high. This ratio is going to be...
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