This post is part of Series Business Intelligence – Tools & Theory
Currently running topic for this series is listed as below :
Series Business Intelligence – Tools & Theory
>>Chapter 1 : Business Intelligence an Introduction
>>Chapter 2 : Business Intelligence Essentials
>>Chapter 3 : Business Intelligence Types
>>Chapter 4 : Architecting the Data
>>Chapter 5 : Introduction of Data Mining
>>Chapter 6 : Data Mining Techniques
>>Chapter 7 : Introduction to Data Warehousing
>>Chapter 8 :Different Ways of Data Warehousing<You are here>
Continuing from my previous post on this series, If you have missed any link please visit link below
We are going to Cover the Following Points in this article
- B2C Business Intelligence model
- Need of B2C model Data Warehousing
B2C Business Intelligence model
Business-to-consumer (B2C) also known as Business-to-Customer depicts the activities of businesses serving end consumers with products and/or services.
Example of B2C transaction is a person buying 2 pairs of shoes from a retailer. The transactions led to the shoes being available for purchase which in turn led to the purchase of the leather, laces, rubber, etc. as well as the sale of the shoes from the shoemaker to the retailer would be considered (B2B) transactions.
Examples of online Business to Consumer (B2C) model: The following are the two examples which show the concept of the B2C business model for online music store which sells audio CDs and DVDs to the users or customers through orders on internet:
A project of SareIndia Ltd, an SPG enterprise Company. HamarCD.com is a distinctive concept where the customers have wonderful options and complete freedom of creating their own audio CDs of their favorite songs. Their selection can be further personalized with their preferred image, CD Title and a message of their choice. Till date,
HamarCD is the largest, most popular and possibly the only legal site offering CD customization facility for the Indian songs globally.
Amazon.com is the best online retailer of products that informs, educates, entertains and inspires about the product. The Amazon group has online stores in countries like United States, Germany, France, Japan and Canada. The use of Amazon.com website is as follows:
The Amazon.com, Inc is a publicly traded company. Amazon.co.uk apart from selling books, sells millions of other products which ranges from cameras to coffee machines, exercise videos to Elvis Presley’s CDs. It also allows independent sellers to sell new and used items on the website through Amazon.co.uk Marketplace. In addition, it also gives the customers to choose from a wide variety of resources that is already available and also includes customer reviews, feedbacks and also personal recommendations.
Business to consumer describes the activities of businesses which serves end consumers with products and/or services. The technology used includes the Internet to enhance the sales, marketing and delivery of products or services to end customers. There are a range of B2C strategic and delivery services which includes internet and e-marketing strategies and solutions, online trading strategies and e-business portfolio of assistance which is focused on helping the customers find smarter ways to work or interact with the customers using information and communication technology.
The business to consumer solution helps the clients to support the commercial objectives. In business-to-consumer, project planning and implementation services are given to the consumer through their in house technical team.
The ongoing support services will be given to the client especially for organizations which use the internet for mission critical purposes. Also a range of management services including eBusiness to consumer hosting services and management are given to the consumer.
Need of B2C model Data Warehousing
In Data warehousing, there are two main categories of usage, which are Consumer-focused Business Intelligence and Operational-focused Business Intelligence.
Customer-Focused Data Warehousing and Business Intelligence:
The internet side of B2C company’s business operations unlike the traditional customer-focused data warehousing gives the opportunity for not only after-the-fact analysis but also the pro-active customer interaction.
Basic Customer Intelligence Services:
The B2C basic customer intelligence services are functionally similar to the the brick-and-mortar businesses.
As data about the customer and the prospective activity is brought into the data warehousing environment from transactional systems, it is synthesized and also made available for reporting and analysis.
There are two key forms of customer intelligence functionality:
· Rule engine
· Statistical modeling
· Rule engine
The rule engine uses the synthesized kept in the data warehouse and mostly, processes the data through a complex set of if-then-else logic to determine the customer segmentation, customer valuation or anything that is being used.
B2C businesses are best served when they extend the basic customer intelligence services beyond reporting and analysis as an end point in the series of automated functionality into feeding directly into critical business operations.
There are many data warehousing strategists and technologists who classify an integrated data environment as a data warehouse only if the contents are used for reporting and analysis. The view is that if the contents are used for operational purposes the environment should be called an operational data store (ODS).
· Statistical Modeling
The second variation in customer intelligence functionality is the statistical modeling. It is used as the foundation for the analytical functionality. For
example, a model can be built that can process large volumes of customer data with the intention of identifying the characteristics and data items which regularly occur together. Therefore, the promotions and campaigns can be created that can exclusively target customers and prospects in a focused manner.
Extending Customer Intelligence Services
As with fundamental customer intelligence, the extended capabilities such as campaign management exceed B2C e-commerce, and in fact have been available through some CRM products. In a B2C environment, the data Bows are very firmly included with the transactional environment with which the customers and the prospects interact for example the Web site to which they connect with their browsers. Furthermore, these inter application data flows are improved by other means of communicating with customers and prospects through e-mail, online banner, advertisement, faxes and so on.
The main objective of extended customer intelligence services is to significantly reduce the time elapsed between the business and the technical processes that use information in the data warehouse to provide insight into the customer’s behavior which could be past behavior as well as the likely future behavior and also the other business processes that make use of the insight to tailor interactions and dialogs so that they can to be more productive and profitable. The inbuilt connectivity between the B2C business and its customer base provided through the openness of the Internet gives the mechanism for evolving from the data flows and business processes.
Even the extended B2C customer intelligence such as highly automated campaign management doesn’t have to fully take advantage of the inbuilt Internet that is which provides connectivity between the business and its customer base. In particular, the contents of the data warehouse used for customer intelligence purposes are historical in nature. Past purchases, past support requests, click stream data representing past Internet usage patterns help in building a customer intelligence infrastructure based on the batch-oriented processes of classical data warehousing which is often not sufficient for what an online business needs.
Consider the communication between a human salesperson and a customer to whom he or she has sold merchandise in the past. A good salesperson will know when and what the customer has previously purchased, will know what the person’s likes and dislikes are, will know the customer’s understanding to merchandise pricing and will know what new products are in stock that might be of interest to that customer. Further, though, the salesman can also process the data points from the in-progress customer interaction such as what the customer says, or the nonverbal clues, for example a male customer having a sparkle in his eye while looking at a suit but then winces after reading the price tag and the other real-time information. It is, therefore, combination of (1) the historical information and (2) the real-time data points that gives far greater shopping-time customer intelligence than available.
Many B2C e-tailers have long been provided with some variation of this integrated customer intelligence for example, an online bookseller suggesting specific titles based on the customer’s past purchases along with browsing patterns of the current session. It is important, though, for click- and-mortar B2C companies to implement some similar capabilities from across all of their channels, though doing so is far more complex than for their pure-play counterparts. All of the issues serve to complicate the processes which are necessary to provide shopping-time intelligence. An emerging necessary form of shopping-time intelligence is called dialog marketing.
Bidirectional Data Warehousing Services
No one can disagree with the fact that Internet technologies allow B2C companies to build far more complete pictures of customers and prospects than ever before. The meeting of traditional forms of data warehousing content with data with respect to online behavior allows companies to know more and more about people with whom they will deal.
There is a growing reaction within the general population against what is increasingly viewed as invasion of privacy. One way a B2C company can suppress some of the uneasiness among its base of customers and prospects with respect to how it uses its data warehouse for customer intelligence is to offer data warehousing services of its own to customers, prospects or both which is basically a bidirectional approach to both CRM1 and data warehousing. For example, an online packager of automobile purchasing services can make available portions of their own data warehouse about vehicles. This also includes financial institutions and their products, the insurance companies and their ratings and perhaps external market data that it purchases gives details of customer satisfaction ratings with companies in each of these categories.
For example, an online grocer may make reports of product popularity and evaluations available to its customer base about what healthy products are rated as having the best taste. The data made available to the public must of course be subject to contractual and legal guidelines. Some externally purchased data may not be able to resell or republish, for example, and it certainly wouldn’t be sensible to publish the names and addresses of the company’s highest volume customers.
In reality, the information provided to customers and their prospects is likely to be of insignificant. The primary business strategy in providing bidirectional CRM and data warehousing capabilities is to reduce consumer concerns about a company’s own data collection policies by giving the results of other data collection to the public.
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