As apart of our talk on database marketing today we are going to discuss on analytical and modeling which is also important factor of the database marketing. We have already discussed on many important factors like consumer data, business data, and source of data for database marketing.
Analytics and modeling
Companies with large databases of customer information risk being "data rich and information poor." As a result, a considerable amount of attention is paid to the analysis of data. For instance, companies often segment their customers based on the analysis of differences in behavior, needs, or attitudes of their customers. A common method of behavioral segmentation is RFM, in which customers are placed into subsegments based on the recency, frequency, and monetary value of past purchases. Van den Poel (2003) gives an overview of the predictive performance of a large class of variables typically used in database-marketing modeling.
They may also develop predictive models, which forecast the propensity of customers to behave in certain ways. For instance, marketers may build a model that rank orders customers on their likelihood to respond to a promotion. Commonly employed statistical techniques for such models include logistic regression and neural networks.
Tuesday, December 30, 2008
Database Marketing – 3
Business data
For many business-to-business (B2B) company marketers, the number of customers and prospects will be smaller than that of comparable business-to-consumer (B2C) companies. Also, their relationships with customers will often rely on intermediaries, such as salespeople, agents, and dealers and the number of transactions per customer may be small. In B2c, business is having direct relation with customer. For example, an online blinds store who are selling roller shades and woven wood shades products.
They don’t have any intermediaries. Business is selling directly to customer. As a result, business-to-business marketers may not have as much data at their disposal. One other complication is that they may have many contacts for a single organization, and determining which contact to communicate with through direct marketing may be difficult. On the other hand the database of business-to-business marketers often include data on the business activity of the respective client that can be used to segment markets, e.g. special software packages for transport companies, for lawyers etc. Customers in Business-to-business environments often tend to be loyal since they need after-sales-service for their products and appreciate information on product upgrades and service offerings.
Sources of customer data often come from the sales force employed by the company and from the service engineers. Increasingly, online interactions with customers are providing b-to-b marketers with a lower cost source of customer information.
For prospect data, businesses can purchase data from compilers of business data, as well as gather information from their direct sales efforts, on-line sites, and specialty publications.
For many business-to-business (B2B) company marketers, the number of customers and prospects will be smaller than that of comparable business-to-consumer (B2C) companies. Also, their relationships with customers will often rely on intermediaries, such as salespeople, agents, and dealers and the number of transactions per customer may be small. In B2c, business is having direct relation with customer. For example, an online blinds store who are selling roller shades and woven wood shades products.
They don’t have any intermediaries. Business is selling directly to customer. As a result, business-to-business marketers may not have as much data at their disposal. One other complication is that they may have many contacts for a single organization, and determining which contact to communicate with through direct marketing may be difficult. On the other hand the database of business-to-business marketers often include data on the business activity of the respective client that can be used to segment markets, e.g. special software packages for transport companies, for lawyers etc. Customers in Business-to-business environments often tend to be loyal since they need after-sales-service for their products and appreciate information on product upgrades and service offerings.
Sources of customer data often come from the sales force employed by the company and from the service engineers. Increasingly, online interactions with customers are providing b-to-b marketers with a lower cost source of customer information.
For prospect data, businesses can purchase data from compilers of business data, as well as gather information from their direct sales efforts, on-line sites, and specialty publications.
Monday, December 29, 2008
Database Marketing - 2
Database marketing has flourished in sectors, such as financial services, telecommunications, and retail, all of which have the ability to generate significant amounts transaction data for millions of customers. Database marketing applications can be divided logically between those marketing programs that reach existing customers and those that are aimed at prospective customers.
Consumer data
In general, database marketers seek to have as much data available about customers and prospects as possible. For marketing to existing customers, more sophisticated marketers often build elaborate databases of customer information. These may include a variety of data, including name and address, history of shopping and purchases, demographics, and the history of past communications to and from customers. For larger companies with millions of customers, such data warehouses can often be multiple terabytes in size.
Marketing to prospects relies extensively on third-party sources of data. In most developed countries, there are a number of providers of such data. Such data is usually restricted to name, address, and telephone, along with demographics, some supplied by consumers, and others inferred by the data compiler. Companies may also acquire prospect data directly through the use of sweepstakes, contests, on-line registrations, and other lead generation activities.
Consumer data
In general, database marketers seek to have as much data available about customers and prospects as possible. For marketing to existing customers, more sophisticated marketers often build elaborate databases of customer information. These may include a variety of data, including name and address, history of shopping and purchases, demographics, and the history of past communications to and from customers. For larger companies with millions of customers, such data warehouses can often be multiple terabytes in size.
Marketing to prospects relies extensively on third-party sources of data. In most developed countries, there are a number of providers of such data. Such data is usually restricted to name, address, and telephone, along with demographics, some supplied by consumers, and others inferred by the data compiler. Companies may also acquire prospect data directly through the use of sweepstakes, contests, on-line registrations, and other lead generation activities.
Thursday, December 25, 2008
Database Marketing - 1
Direct and database marketing organizations, on the other hand, argue that a targeted letter or e-mail to a customer, who wants to be contacted about offerings that may interest the customer, benefits both the customer and the marketer. As a part of our talk on database marketing now we will talk on some important factors of the database marketing like source of data, customer data, business data etc….. Any business needs to have customer database and it always helps to use these customer databases for marketing. A blinds company with special products like roller shades and woven wood blinds require keeping customer database and using such database again and again to get more and more business from those customers.
Sources of data
Although organizations of any size can employ database marketing, it is particularly well-suited to companies with large numbers of customers. This is because a large population provides greater opportunity to find segments of customers or prospects that can be communicated with in a customized manner. In smaller (and more homogeneous) databases, it will be difficult to justify on economic terms the investment required to differentiate messages. CRM software with sales force automation helps manages marketing and maintain database too.
As a result, database marketing has flourished in sectors, such as financial services, telecommunications, and retail, all of which have the ability to generate significant amounts transaction data for millions of customers. Database marketing applications can be divided logically between those marketing programs that reach existing customers and those that are aimed at prospective customers.
Sources of data
Although organizations of any size can employ database marketing, it is particularly well-suited to companies with large numbers of customers. This is because a large population provides greater opportunity to find segments of customers or prospects that can be communicated with in a customized manner. In smaller (and more homogeneous) databases, it will be difficult to justify on economic terms the investment required to differentiate messages. CRM software with sales force automation helps manages marketing and maintain database too.
As a result, database marketing has flourished in sectors, such as financial services, telecommunications, and retail, all of which have the ability to generate significant amounts transaction data for millions of customers. Database marketing applications can be divided logically between those marketing programs that reach existing customers and those that are aimed at prospective customers.
Sunday, December 21, 2008
Database marketing
Database marketing is a form of direct marketing using databases of customers or potential customers to generate personalized communications in order to promote a product or service for marketing purposes. The method of communication can be any addressable medium, as in direct marketing.
The distinction between direct and database marketing stems primarily from the attention paid to the analysis of data. Database marketing emphasizes the use of statistical techniques to develop models of customer behavior, which are then used to select customers for communications. As a consequence, database marketers also tend to be heavy users of data warehouses, because having a greater amount of data about customers increases the likelihood that a more accurate model can be built. The "database" is usually name, address, and transaction history details from internal sales or delivery systems, or a bought-in compiled "list" from another organization, which has captured that information from its customers. Typical sources of compiled lists are charity donation forms, application forms for any free product or contest, product warranty cards, subscription forms, and credit application forms. The communications generated by database marketing may be described as junk mail or spam, if it is unwanted by the addressee.
The distinction between direct and database marketing stems primarily from the attention paid to the analysis of data. Database marketing emphasizes the use of statistical techniques to develop models of customer behavior, which are then used to select customers for communications. As a consequence, database marketers also tend to be heavy users of data warehouses, because having a greater amount of data about customers increases the likelihood that a more accurate model can be built. The "database" is usually name, address, and transaction history details from internal sales or delivery systems, or a bought-in compiled "list" from another organization, which has captured that information from its customers. Typical sources of compiled lists are charity donation forms, application forms for any free product or contest, product warranty cards, subscription forms, and credit application forms. The communications generated by database marketing may be described as junk mail or spam, if it is unwanted by the addressee.
Friday, December 12, 2008
Privacy concerns-2
The danger occurs when the summarized data paints an untrue picture of things. This can lead to a company taking improper actions which could be detrimental to the prosperity of the company. The threat to an individual’s privacy comes into play when the data, once compiled, causes the data miner to be able to identify specific individuals, especially when originally the data was anonymous. Aggregating data from multiple sources allows profiles of individuals to be created . In order for the information derived from the data that is mined to be meaningful one must assume that the data which is in the repository is accurate and complete. In addition, one must assume that the analysis was done in a way that would produce a reliable result. A common saying is “garbage in garbage out” meaning if the data that is input into your repository is of poor quality, your analysis, or output, will also be of poor quality .
The steps that may be taken in order to protect your customers, from whom you are collecting data, and your company are to specify the purpose of the data collection and any data mining projects, how the data will be used, who will be able to mine the data and use it, the security surrounding access to the data, and in addition, to provide a way for individuals to update data which was collected from them. This also assists in ensuring the data is accurate. One may additionally modify the data so that it is anonymous so that individuals may not be readily identified.
blinds, roller shades, woven wood shades
The steps that may be taken in order to protect your customers, from whom you are collecting data, and your company are to specify the purpose of the data collection and any data mining projects, how the data will be used, who will be able to mine the data and use it, the security surrounding access to the data, and in addition, to provide a way for individuals to update data which was collected from them. This also assists in ensuring the data is accurate. One may additionally modify the data so that it is anonymous so that individuals may not be readily identified.
blinds, roller shades, woven wood shades
Thursday, December 11, 2008
Privacy concerns-1
There are also privacy and human rights concerns associated with data mining, specifically regarding the source of the data analyzed. Data mining provides information that may be difficult to obtain otherwise. When the data collected involves individual people, there are many questions concerning privacy, legality, and ethics. In particular, data mining government or commercial data sets for national security or law enforcement purposes, such as in the Total Information Awareness Program, has raised privacy concerns.
The following facts have increased the urgency and difficulty regarding data mining and protecting the privacy of the individuals about whom the data was collected: the decreased cost of data mining tools and the prevalence of those tools, an increase in the amount of data being collected and stored, an increase in the use of data aggregation, and the use of data warehouses as the stores for the data from several sources.
“Data mining by itself is ethically neutral”. There are several ethical issues which are raised by the topic of data mining: “the suitability and validity of the methods used in any given data mining application, the degree to which confidentiality and privacy obligations are respected, and the overall aims of a given data mining application”.
One must take into consideration the reliability of the source of the data which is being mined, the reason that the data was collected originally, and any aggregation that has taken place A danger which is inherent to data mining projects is the possibility of erroneous information resulting from data aggregation. Data aggregation is when the data which has been mined, possibly from various sources, has been put together so that it can be analyzed.
The following facts have increased the urgency and difficulty regarding data mining and protecting the privacy of the individuals about whom the data was collected: the decreased cost of data mining tools and the prevalence of those tools, an increase in the amount of data being collected and stored, an increase in the use of data aggregation, and the use of data warehouses as the stores for the data from several sources.
“Data mining by itself is ethically neutral”. There are several ethical issues which are raised by the topic of data mining: “the suitability and validity of the methods used in any given data mining application, the degree to which confidentiality and privacy obligations are respected, and the overall aims of a given data mining application”.
One must take into consideration the reliability of the source of the data which is being mined, the reason that the data was collected originally, and any aggregation that has taken place A danger which is inherent to data mining projects is the possibility of erroneous information resulting from data aggregation. Data aggregation is when the data which has been mined, possibly from various sources, has been put together so that it can be analyzed.
Monday, December 8, 2008
Algorithms
There are various data mining algorithms which can be used to build the mining model. But choosing the right algorithm for the right business task is critical. Different algorithms can be used to do the same business tasks but each algorithm produces different results.
The various types of algorithms are as follows:
1. Classification algorithm predicts one or more discrete variables, based on the other attributes in the dataset. eg: Microsoft Decision Trees Algorithm.
2. Regression algorithm predicts one or more continuous variables, such as profit or loss, based on other attributes in the dataset. eg: Microsoft Time Series Algorithm.
3. Segmentation algorithm divides data into groups, or clusters, of items that have similar properties. eg: Microsoft Clustering Algorithm.
4. Association algorithm finds correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis. eg: Microsoft Association Algorithm.
5. Sequence analysis algorithm summarizes frequent sequences or episodes in data, such as a Web path flow. eg: Microsoft Sequence Clustering Algorithm.
A data mining application can adopt different algorithms for different functions, for example we can use segmentation algorithms for exploring data and regression algorithms for prediction functionalities.
roman shades, vertical blinds, window blinds
The various types of algorithms are as follows:
1. Classification algorithm predicts one or more discrete variables, based on the other attributes in the dataset. eg: Microsoft Decision Trees Algorithm.
2. Regression algorithm predicts one or more continuous variables, such as profit or loss, based on other attributes in the dataset. eg: Microsoft Time Series Algorithm.
3. Segmentation algorithm divides data into groups, or clusters, of items that have similar properties. eg: Microsoft Clustering Algorithm.
4. Association algorithm finds correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis. eg: Microsoft Association Algorithm.
5. Sequence analysis algorithm summarizes frequent sequences or episodes in data, such as a Web path flow. eg: Microsoft Sequence Clustering Algorithm.
A data mining application can adopt different algorithms for different functions, for example we can use segmentation algorithms for exploring data and regression algorithms for prediction functionalities.
roman shades, vertical blinds, window blinds
Tuesday, December 2, 2008
Search for Window Treatments-1
Yesterday I and my family visited one mall. It is very big and well known shopping mall in our area. I was there to buy something unique and different for my house. I saw so many antique things which are useful to decorate the house like wall picture, flower vas etc…. Actually I was interested in window treatments items. Fortunately I found one store and they have many types of blinds on their display. For the first time I have seen these much collections of blinds at one place. The way they have displayed their product range was so attractive.
They are having window blind & shade products. That includes wood blinds, faux wood blinds, mini blinds, and vertical blinds. Their window shades includes roman shades, cellular shades, pleated shades, roller shades, and woven wood bamboo shades. I was interested in vertical blinds for my drawing room. Salesman their explain me vertical blinds are very popular and appealing for sliding glass doors and larger windows. He told me to select between cord and chain operation and wand controlled blinds. My kids are already grown so, I don’t have any threat to my kids safety. We decided to go with chain instead of cord.
Than he told us to select from a variety of wood, fabric patterns, and basic vinyl on our verticals so that our blinds are coordinated with the rest of our decorations. He told us that for more unique look, sliding panel shades offer both shade and safety with their baton draw design. These large panels will add ambiance to any formal room in your home! So, at last I decided to go with vertical blinds for my drawing room.
They are having window blind & shade products. That includes wood blinds, faux wood blinds, mini blinds, and vertical blinds. Their window shades includes roman shades, cellular shades, pleated shades, roller shades, and woven wood bamboo shades. I was interested in vertical blinds for my drawing room. Salesman their explain me vertical blinds are very popular and appealing for sliding glass doors and larger windows. He told me to select between cord and chain operation and wand controlled blinds. My kids are already grown so, I don’t have any threat to my kids safety. We decided to go with chain instead of cord.
Than he told us to select from a variety of wood, fabric patterns, and basic vinyl on our verticals so that our blinds are coordinated with the rest of our decorations. He told us that for more unique look, sliding panel shades offer both shade and safety with their baton draw design. These large panels will add ambiance to any formal room in your home! So, at last I decided to go with vertical blinds for my drawing room.
Subscribe to:
Posts (Atom)
