Data Mining, Not Just a Method But a Technique

Web data mining is segregating probable clients out of huge information available on the Internet by performing various searches. It could be well organized and structured, or raw, depending on the use of the data. Web data mining could be done using a simple database program or investing money in a costly program.

Start collecting basic contact information of probable clients, such as: names, addresses, landline and cell phone numbers, email addresses and education or occupation if required.

CART and CHAID data mining

While collecting data you will find that tree-shaped structures that represent decisions. These derived decisions give rules for the classification of data collected. Precise decision tree methods include Classification and Regression Trees also know as CART data mining and Chi Square Automatic Interaction Detection also known as CHAID data mining. CART and CHAID data mining are decision tree techniques used for classification of data collected. They provide a set of rules that could be applied to unclassified data collected in prediction. CART segments a dataset creating two-way splits whereas CHAID segments using chi square tests creating multi-way splits. CART requires less data preparation compared to CHAID.

Understanding customer's actions

Keep a track of customer's actions like: what does he buy, when does he buy, why does he buy, what is the use of his buying, etc. Knowing such simple things about your customer will help you to understand needs of your customer better and thus process of data mining services will be easier and quality data would be mined. This will increase your personal relations with your customer which would finally result in a better professional relationship.

Following demography

Mine the data as per demography, dependent on geography as well as socio economic background of business location. You can use government statistics as the source of your data collection. Keeping it in mind you can go ahead with the understanding of the community existing and thus the data required.

Use your informal conversation in serving your clients better

Use minute details of your conversation and understanding with your customers to serve them. If essential, conduct surveys, send a professional gift or use some other object that helps you understand better in fulfilling customer needs. This will increase the bonding between you and your customer and you will be able to serve your customer better in providing data mining services.

Insert the collect information in a desktop database. More the information is collected you will find that you can prepare specific templates in feeding information. Using a desktop database, it is easier to make changes later on as and when required.


Source: http://ezinearticles.com/?Data-Mining,-Not-Just-a-Method-But-a-Technique&id=5416129

Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

Basic process of CRM data mining includes:
1. Define business goal
2. Construct marketing database
3. Analyze data
4. Visualize a model
5. Explore model
6. Set up model & start monitoring

Let me explain last three steps in detail.

Visualize a Model:
Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:
Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:
To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.


Source: http://ezinearticles.com/?Customer-Relationship-Management-%28CRM%29-Using-Data-Mining-Services&id=4641198

Remuneration of Outsourcing Data Entry

Outsource Data entry is a fast growing industry. The world of business is dynamic, fast paced, and in constant change. In such an environment the accessibility of accurate, detailed information is a necessity. Entry is the main component of any business firm. Online data entry is a very lengthy and tiresome work, so the best option for companies to take care of this is through data entry outsourcing services.

The more you know about the market, your customers and other factors that influence an organization, the better you can understand your own business. Services by professionals appointed for this task play a crucial role in running a business successfully. In today's market, data entry solutions for different types of businesses are available at very competitive prices.

Core Benefits of Outsourcing Services

Affordable Cost: In this way, the companies can reduce the expenditure of resources and increase the efficiency and productivity. As the result of which, increase are the obvious outcome.

High Quality Work: data entry outsourcing services is getting fast track quality work as per the requirements. As bulk assignments delivered everyday without compromising on the quality issue, outsourcing data entry services is fast becoming the first choice of most of information technology companies.

Time saving and High Efficiency: Everything in or out of organization is primarily done to get maximum possible benefits in minimum possible time. Therefore, as one of the important benefits of outsourcing is that it minimizes time spending and this consequently leads to high efficiency in the business process.

Efficient Data Management: Since the data is entered afresh into different formats, it is managed and digitized to give an affable appeal, besides, high accuracy levels.

Easing out Burden: Benefits of outsourcing, is the easing of burden of companies, who are involved in strategic processes, which play an involved role in profits. By outsourcing the time-consuming, the company gets relieved of unnecessary pressure and can concentrate over the new projects.


Source: http://ezinearticles.com/?Remuneration-of-Outsourcing-Data-Entry&id=2122790

Every Business Organization Needs Data Entry Services

Data entry is the main component of any business firm. They use this to maintain records of all sorts in a properly way. Although it seems to be an easier task but this is not the scenario, the work has to be done very cautiously and efficiently by the professional as data is very crucial. Data is priceless for any organization irrespective of their size and strength. Today, huge changes in the business industry have taken place and so businesses are adopting such new advanced techniques. These high end technologies have helped the data entry services in becoming much easier and efficient than ever before. If you are seeking to this service then must be prepared to spend more for this. So hiring this service will certainly help your business towards upward growth. Well, being the owner of your business, you are the best person to judge what will be a good strategy for your business. You can either hire a professional or can hire an outside firm to assist your data entry services task.

The newer methods of data entry services have over lapped the older and traditional methods of this service. Earlier, this service was done manually and obviously in-accuracy was found much more. So, information technology enabled services have come up with the new process that has made this service highly accurate and much easier. Indeed, every business wants to deal with this service very efficiently and accurately and so many have taken this highly enabled service for their firm. Data entry services are the key aspect of any business organization and every business needs a proper system to maintain its data and records. As data is crucial aspect of any firm irrespective of specialization or size and so they are in need of such an efficient system that can undertake their task.

An in-house data entry services would be more advantageous as you can keep a watch on the task done by professional. You can look into the procedure and other stuff that they do for your business. This can be bit expensive for your business as you will have to pay more as being an employee they are eligible for bonuses, allowances and other stuffs. If you are not satisfied with this option then you can undertake the services of a third party vendor. You can hand-over your entire task of data entry to them and can relieve of getting an efficient services. This can truly relieve you of getting a better service from them as you can get your task done in the way you desire. This option has proved to be more advantageous and proficient for many businesses. Now a day's data conversion process is highly accessed by many business firms and so gaining momentum on a large scale.

Data conversion is being done without any hassle and brings more customers to buy the products. Outsourcing of data entry services has seen huge success and businesses have seen huge profits through this service. This service has proved as a cost effective business strategy for businesses and have seen huge surge in their revenue.So, it's quite obvious that hiring data entry services from a third party vendor is better for the business then why to hire an in-house professional.



Source: http://ezinearticles.com/?Every-Business-Organization-Needs-Data-Entry-Services&id=596342

How Data Mining is Useful to Companies?

Every business, organization and government bodies are collecting large amount of data for research and development. Such huge database can make them to have the information on hand when required. But most important is that it takes much time to find important information from the data. "If you want to grow rapidly, you must take quick and accurate decisions to grab timely available opportunities."

By applying the process of data mining, you can easily extract and filter required information from data. It is a processing of refining data and extracting important information. This process is mainly divided into 3 sections; pre-processing, mining and validation. In pre-processing, large amount of relevant data are collected. The mining section includes data classification, clustering, error correction and linking information. The last but important is validate without which you can not make trust on information. In short, data mining is a process of converting data into authentic information.

Let's have look on how data mining is useful to companies.

Fast and Feasible Decisions: To search information from huge bundle of data require more time. It also irritates a person who is doing such. With annoyed mind one can not take accurate decisions that's for sure. By having help of data mining, one can easily get information and make fast decisions. It also helps to compare information with various factors so the decisions become more reliable. Data mining is helpful in every decision to make it quick and feasible.

Powerful Strategies: After data mining, information becomes precise and easy to understand. While making strategies, one can easily analyze information in various dimensions. This analysis helps to get real idea about the strategy implementation. Management bodies can implement powerful strategies effectively to expand business boundaries.

Competitive Advantage: Information is easily available and precise so that one can compare it with competitors' information. It is very much required that you must compare the data otherwise you will have to suffer in business. After doing competitive analysis, one can make corrective decisions to go ahead from competitors. This way company can gain competitive advantage.

Your business can get all the benefits of data mining at cutting rates through outsourcing.



Source: http://ezinearticles.com/?How-Data-Mining-is-Useful-to-Companies?&id=2835042

How Data Mining Can Help in Customer Relationship Management Or CRM?

Customer relationship management (CRM) is critical activity of improvising customer interactions while at the same time making the interactions more amicable through individualization. Data mining utilizes various data analysis and modeling methods to detect specific patterns and relationships in data. This helps in understanding what a customer wants and forecasting what they will do.

Using Data mining you can find out right prospects and offer them right products. This results in improved revenue because you can respond to each customer in best way using fewer resources.

Basic process of CRM data mining includes:
1. Define business objective
2. Construct marketing database
3. Analyze data
4. Visualize a model
5. Explore model
6. Set up model & start monitoring

Let me explain above steps in detail.

Define the business objective:
Every CRM process has one or more business objective for which you need to construct the suitable model. This model varies depending on your specific goal. The more precise your statement for defining the problem is the more successful is your CRM project.

Construct a marketing database:
This step involves creation of constructive marketing database since your operational data often don't contain the information in the form you want it. The first step in building your database is to clean it up so that you can construct clean models with accurate data.

The data you need may be scattered across different databases such as the client database, operational database and sales databases. This means you have to integrate the data into a single marketing database. Inaccurately reconciled data is a major source of quality issues.

Analyze the data:
Prior to building a correct predictive model, you must analyze your data. Collect a variety of numerical summaries (such as averages, standard deviations and so forth). You may want to generate a cross-section of multi-dimensional data such as pivot tables.

Graphing and visualization tools are a vital aid in data analysis. Data visualization most often provides better insight that leads to innovative ideas and success.


Source: http://ezinearticles.com/?How-Data-Mining-Can-Help-in-Customer-Relationship-Management-Or-CRM?&id=4572272

Why Outsource Data Entry Services?

All large business and organizations are faced with the task of processing huge amounts of data on a daily basis. The data to be processed may range from indexing of vouchers and documents to collecting of information from customers and vendors. In order to save on the huge amount of time, energy and monetary resources which go into data entry, businesses world wide have discovered the multiple benefits of outsourcing their Data Entry Services to India. Along with quick turn around time, reliability of data accuracy and confidentiality of all client databases, outsourcing Data Entry Services to India also proves to be extremely cost-effective.

What are the kinds of Services that can be outsourced?

Most outsourcing companies provide custom made Data-Entry Services depending on the client's specifications. A few of them provided by Indian Outsourcing Companies are;

- Data entry from product catalogs to web based systems
- Entry from hard/soft copy to any preferred database format
- Insurance claims processing
- Image Entry
- Data mining and warehousing
- Data cleansing
- Entry from hospital records, patient notes and accident reports
- From e-book and e-magazine publications on the Internet
- Entry for mailing lists
- PDF document indexing
- Online data capture services
- Online order entry and follow up services
- Creating new databases and updating of existing databases for banks, airlines, government agencies
- direct marketing services and service providers
- Web based indexed document retrieval services, tools and support
- Entry of legal documents
- Indexing of vouchers and documents
- Hand written ballot/cards entry
- Online completion of surveys and responses of customers for various companies
- Business card indexing
- Custom data export/import interfaces with audits
- Bonded mail handling cash, credit and check processing
- Entry of Questionnaires
- Entry of Company Reports
- From Printed / Handwritten Source
- From Yellow Pages / White Pages
- Entry of Dictionaries, Manuals and Encyclopedia
- Entry of Surveys

What is the process?

Since most Indian companies hire only competent and highly qualified staff, outsourcing Data Entry Services to India ensures that the client is fully satisfied with the end result. Added to this the client's data confidentiality and security is viewed as extremely important. Each project goes through a specific data entry service plan that aims to fulfill the exact need of the customer and the error rate is always kept below 2-3%. The process is as follows:

- Data is processed, scanned and uploaded on to secure FTP online server
- Data is subsequently accessed over VPN and downloaded
- Data is individually indexed and sorted into private work folders
- Data is entered into specific applications as per client's requirements
- Data is checked and assessed for errors
- Data is finally sent to the customers

What are the benefits of outsourcing Services?

Oversees companies outsourcing their Data Entry Services to India have the assurance that their projects will be delivered on time with the highest levels of data quality and accuracy. The cost competitive prices, highly qualified employees, fast turnaround time and data security offered by outsourcing vendors, make sure that all of the client's objectives and goals are met. Outsourcing of these Services to India has been proven to be an advantageous choice for businesses worldwide.


Source: http://ezinearticles.com/?Why-Outsource-Data-Entry-Services?&id=1428867

Outsource Data Mining Services to Offshore Data Entry Company

Companies in India offer complete solution services for all type of data mining services.

Data Mining Services and Web research services offered, help businesses get critical information for their analysis and marketing campaigns. As this process requires professionals with good knowledge in internet research or online research, customers can take advantage of outsourcing their Data Mining, Data extraction and Data Collection services to utilize resources at a very competitive price.

In the time of recession every company is very careful about cost. So companies are now trying to find ways to cut down cost and outsourcing is good option for reducing cost. It is essential for each size of business from small size to large size organization. Data entry is most famous work among all outsourcing work. To meet high quality and precise data entry demands most corporate firms prefer to outsource data entry services to offshore countries like India.

In India there are number of companies which offer high quality data entry work at cheapest rate. Outsourcing data mining work is the crucial requirement of all rapidly growing Companies who want to focus on their core areas and want to control their cost.

Why outsource your data entry requirements?

Easy and fast communication: Flexibility in communication method is provided where they will be ready to talk with you at your convenient time, as per demand of work dedicated resource or whole team will be assigned to drive the project.

Quality with high level of Accuracy: Experienced companies handling a variety of data-entry projects develop whole new type of quality process for maintaining best quality at work.

Turn Around Time: Capability to deliver fast turnaround time as per project requirements to meet up your project deadline, dedicated staff(s) can work 24/7 with high level of accuracy.

Affordable Rate: Services provided at affordable rates in the industry. For minimizing cost, customization of each and every aspect of the system is undertaken for efficiently handling work.

Outsourcing Service Providers are outsourcing companies providing business process outsourcing services specializing in data mining services and data entry services. Team of highly skilled and efficient people, with a singular focus on data processing, data mining and data entry outsourcing services catering to data entry projects of a varied nature and type.

Why outsource data mining services?

360 degree Data Processing Operations
Free Pilots Before You Hire
Years of Data Entry and Processing Experience
Domain Expertise in Multiple Industries
Best Outsourcing Prices in Industry
Highly Scalable Business Infrastructure
24X7 Round The Clock Services

The expertise management and teams have delivered millions of processed data and records to customers from USA, Canada, UK and other European Countries and Australia.

Outsourcing companies specialize in data entry operations and guarantee highest quality & on time delivery at the least expensive prices.


Source: http://ezinearticles.com/?Outsource-Data-Mining-Services-to-Offshore-Data-Entry-Company&id=4027029

Data Mining - You Have to Be Smarter Than the Data and That's the Rub!

The Department of Homeland Security is using all kinds of computer tools to do data mining and they are gathering the data from businesses and government records, where ever they can find them. Many decry these methods but all the information that the government has on each individual citizen is information that they do indeed own. When you do business with a certain company chances are of the information you give them is theirs to give out to whoever they choose, based on their privacy policy, which you submit to.

Some people believe that Department of Homeland Security has stopped collecting data and that is not true. Yes, some personal identity information, they are not allowed to seek without a court order, but for the most part the government has the opportunity to data mine all sorts of information that is already out there in the public record, the government record or with businesses that the government does contract with.

Additionally, all the is data mining done by Department of Homeland Security, has to do with trends and commonalities. By revealing this information, they can find anomalies in the data that alert them that something is going different or unexpected. This helps them predict patterns of behavior and know when something is out of place. The Department of Homeland Security is allowed to go through chat rooms, online blogs, the Internet, personal home pages, video surveillance footage and they also scan every phone call for data.

Why are they doing this? They are doing this to find data that jumps out at them and signals that something is going wrong. With the help of mathematicians, linguists, artificial intelligence and logicians is amazing what they can come up with. Is the government reading your blog? Yes, they are reading your blog, but is not as if they are snooping, they use search engine type spiders to go through all the pages on the Internet.

What else is the software good for or how can these strategies be used better? By knowing what types of people live in a certain area, or what type of events are occurring along with the amount of chatter going on in a specific area, or with a specific group of people that are linked in some way - the Department of Homeland security can predict an international terrorist attack or a "black swan event" such as someone going berserk at a post office.

Will they actually be able to prevent and predict events in this way? Theoretically, it is possible and such technologies are getting us to a closer place where we will soon know just how good we are predicting the future. Something to definitely contemplate in 2008.



Source: http://ezinearticles.com/?Data-Mining---You-Have-to-Be-Smarter-Than-the-Data-and-Thats-the-Rub!&id=884014

Data Mining

Data Mining is defined as the extraction of required information or knowledge from large databases. This is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. The tools related to this new technology predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analysis offered by data mining move beyond the analysis of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too time consuming to resolve. This new technology takes the process of knowledge and information acquisition beyond retrospective data access and navigation to prospective and proactive information delivery.

The Technology derives its name from the similarities between searching for valuable business information in a large database and mining a mountain for a vein of valuable ore. Both processes require either sifting through an immense amount of material, or intelligently probing it to find exactly where the value resides. Data mining automates the process of finding predictive information in large databases. Data mining tools sweep through databases and identify previously hidden patterns in one step. Data mining techniques can yield the benefits of automation on existing software and hardware platforms, and can be implemented on new systems as existing platforms are upgraded and new products developed.. Powerful systems for collecting data and managing it in large databases are in place in all large and mid-range companies.

Data Mining is predicted to be amongst the top five technologies of the world that are poised for fantastic growth and development in the next five years. Data Mining today assumes importance and significance because of the increasing thrust on knowledge and information which is an essential factor in successfully running ebusiness. Data Mining cannot replace completely human analysis and interaction. But it can greatly assist human intellect to take well thought out decisions through fast computing capabilities and through pinpointing thrust areas of the concerned business.

Data Mining is considered as the new thrust area technology, the blue-eyed boy of the ebusiness world, with great scope for expansion beyond the present day horizons of the e enterprises. Data is vital to the growth of ebusiness. And getting the right data at the right time is the crux of good business sense. Growth of web enterprises is dependent solely on knowledge and information processing. Data Mining therefore has arrived on the scene at the very appropriate time , helping these enterprises to achieve a number of complex tasks that would have taken up ages but for the advent of this marvelous new technology.


Source: http://ezinearticles.com/?Data-Mining&id=1217896

Lucrative and Main Advantages of Data Entry Outsourcing Services

This time, Data Entry services are playing profitable role in many large business houses in the world. The services are very useful for big organizations. Today, there is huge demand in BPO (Business Process Outsourcing) KPO (Knowledge Process Outsourcing) and LPO (Legal Process Outsourcing) companies. Data Entry services cover almost all business and professional services such as data conversion, online and offline data entry, document and image processing, image entry, insurance claim entry, data entry outsourcing, offline as well as online data entry jobs. The services also collect huge data related to certain topics and then to present them in meaningful & easy to understand presentations.

Data Entry Outsourcing functions as contracting with outside consultants, software firms and then to do analysis of systems, system programming and data center operations. The special purpose for doing outsourcing is the availability of qualified and experienced computer operators at low cost. The professionals excel at data processing are very detail oriented, quick typists, and able to check their work for errors as they go. The professionals do all types of Data Feeding operations for instance data conversion, data processing, catalog processing services, image enhancement, image editing and photo manipulation services, etc. There are a number of data feeding outsourcing companies which are getting profitable business from various parts of the world. They are saving time and money.

Most data processing outsourcing companies offer some sort of non-disclosure guarantee, to verify that the data will remain safe and secure. In addition, the company offers a quality guarantee, as well as the benefit of having qualified employees doing the work. The company also uses an experienced freelancer for small projects with longer deadlines. It is especially attractive for companies that only occasionally need the service, such as for producing annual or semi-annual reports. Working for a data processing company can be a great employment opportunity.

Many companies that do data feeding or punching work will train new employees on-site, and then allow them to work from home part-time or even full-time A freelancer can be a great way to earn extra income on the side, and often offers great flexibility regarding hours worked and workload. The freelancer to whom the work is outsourced is a specialist in the job and hence the work is completed with more precision and with lower turnaround time. Data Entry online services outsourcing, infrastructure and management problems, minimizes capital costs. These companies make their best possible use of international resources.


Source: http://ezinearticles.com/?Lucrative-and-Main-Advantages-of-Data-Entry-Outsourcing-Services&id=6080683

What Poker Data Mining Can Do for a Player

Anyone who wants to be more successful in many poker rooms online should take a look at what poker data mining can do. Poker data mining involves looking into all of the past hands in a series of poker games. This can be used to help with reviewing the ways how a player plays the game of poker. This will help to determine how well someone is working when trying to play this exciting game.

Poker data mining works in that a player will review all of the past hands that a player has gotten into. This includes taking a look at the individual hands that were involved. Every single card, bet and movement will be recorded in a hand.

All of the hands can be combined to help with figuring out the wins and losses in a game alongside all of the strategies that had been used throughout the course of a game. The analysis will be used to determine how well a player has gone in a game.

The review will be used to figure out the changes in one's winnings over the course of time. This can be used in conjunction with different types of things that are going on in a game and how the game is being played. This will be used to help figure out what is going on in a game and to see what should be done correctly and what should not be handled.

The data mining that is used is handled by a variety of different kinds of online poker sites. Many of these sites will allow its customers to buy information on various previous hands that they have gotten into. This is used by all of these places as a means of helping to figure out how well a player has done in a game.

Not all places are going to offer support for poker data mining. Some of these places will refuse to work with it due to how they might feel that poker data mining will give a player an unfair advantage over other players who are not willing to pay for it. The standards that these poker rooms will have are going to vary. It helps to review policies of different places when looking to use this service.

Poker data mining can prove to be a beneficial function for anyone to handle. Poker data mining can be smart because of how it can help to get anyone to figure out how one's hand histories are working in a poker room. It will be important to see that this is not accepted in all places though. Be sure to watch for this when playing the game of poker and looking to succeed in it.


Source: http://ezinearticles.com/?What-Poker-Data-Mining-Can-Do-for-a-Player&id=5563778

RFM - A Precursor to Data Mining

RFM was initially utilized by marketers in the B-2-C space - specifically in industries like Cataloging, Insurance, Retail Banking, Telecommunications and others. There are a number of scoring approaches that can be used with RFM. We'll take a look at three:

RFM - Basic Ranking
RFM - Within Parent Cell Ranking
RFM - Weighted Cell Ranking

Each approach has experienced proponents that argue one over the other. The point is to start somewhere and experiment to find the one that works best for your company and your customer base. Let's look at a few examples.

RFM - Basic Ranking

This approach involves scoring customers based on each RFM factor separately. It begins with sorting your customers based on Recency, i.e., the number of days or months since their last purchase. Once sorted in ascending order (most recent purchasers at the top), the customers are then split into quintiles, or five equal groups. The customers in the top quintile represent the 20% of your customers that most recently purchased from you.

This process is then undertaken for Frequency and Monetary as well. Each customer is in one of the five cells for R, F, and M

Experience tells us that the best prospects for an upcoming campaign are those customers that are in Quintile 5 for each factor - those customers that have purchased most recently, most frequently and have spent the most money. In fact, a common approach to creating an aggregated score is to concatenate the individual RFM scores together resulting in 125 cells (5x5x5).

A customer's score can range from 555 being the highest, to 111 being the lowest.

RFM - Within Parent Cell Ranking

This approach is advocated by Arthur Middleton Hughes - one of the biggest proponents of RFM analysis. It begins like the one above, i.e., all customer are initially grouped into 5 cells based on Recency. The next step takes customers in a given Recency cell - say cell number 5, and then ranks those customers based on Frequency. Then customers in the 55 (RF) cell are ranked by monetary value.

RFM - Weighted Ranking

Weightings used by RFM practitioners vary. For example some advocate adding the RFM score together - thus giving equal weight to each factor. Consequently, scores can range from 15 (5+5+5) to 3 (1+1+1). Another weighting arrangement often used is, 3xR + 2xF + 1xM. In this case, scores can range from 30 to 3.

So which to use? In reality, there are many other permutations of approaches that are being used today. Best-practice marketing analytics requires a fine mix of mathematical and statistical science, creativity and experimentation. Bottom line, test multiple scoring methods to see which works best for your unique customer base.

Establishing a Score Threshold

After a test or production campaign, you will find that some of the cells were profitable while some were not. Let's turn to a case study to see how you can establish a threshold that will help maximize your profitability. This study comes from Professor Charlotte Mason of the Kenan-Flagler Business School and utilizes a real-life marketing study performed by The BookBinders Book Club (Source:Recency, Frequency and Monetary (RFM) Analysis, Professor Charlotte Mason, Kenan-Flagler Business School, University of North Carolina, 2003).

BookBinders is a specialty book seller that utilizes multiple marketing channels. BookBinders traditionally did mass marketing and wanted to test the power of RFM. To do so, they initially did a random mailing to 50,000 customers. The customers were mailed an offer to purchase The Art History of Florence. Response data was captured and a "post-RFM" analysis was completed. This "post analysis" was done by freezing the files of the 50,000 test customers prior to the actual test offer. Thus, the impact of this test campaign did not effect the analysis by coding many (the actual buyers) of the 50,000 test subjects as the most recent purchasers. The results firmly support the use of RFM as a highly effective segmentation approach.

Purchased the book = yes; months since last purchase = 8.61; total # purchases = 5.22; dollars spent = 234.30
Purchased the book = no; Months since last purchase = 12.73; total # purchases = 3.76; dollars spent = 205.74

Customers that purchased the book were more recent purchasers, more frequent purchasers and had spent the most with BookBinders.

The response rate for the top decile (18%) was twice the response rate associated with the 5th decile (9%).

Results from this test were then used by BookBinders to identify which of their remaining customers should receive the same mailing. BookBinders used a breakeven response rate calculation to determine the appropriate RFM cells to mail.

The following cost information was used as input:

Cost per Mail-piece $0.50

Selling Price $18.00

BookBinders Book Cost $9.00

Shipping Costs $3.00

Breakeven is achieved when the cost of the mailing is equal to the net profit from a sale. In this case:

Breakeven = (cost to mail the offer/net profit from a single sale)

= $0.50/($18-9-3)

= ($0.50/6)

= 8.3% = Breakeven Response rate

So, according to the test offer, profit can be obtained by mailing to cells that exhibited a response rate of greater than 8.3%

RFM dramatically improved profitability by capturing 71% of buyers (3,214/4,522) while mailing only 46% of their customers (22,731/50,000). And the return on marketing expenditures using RFM was more than eight times (69.7/8.5) that of a mass mailing.

Number of Cells and Cell Size Considerations

As previously mentioned, RFM was initially utilized by companies that operated in the B-to-C marketplace and generally possessed a very large number of customers. The idea of generating 125 cells using quintiles for R, F and M has been a very good practice as an initial modeling effort. But what if you are a B-to-B marketer with relatively fewer customers? Or, what if you are a B-to-C marketer with an extremely large file with millions of customers? The answer is to use the same approach that is used in data mining -- be flexible and experiment.

Establishing a minimum test cell size is a good place to start. Arthur Hughes recommends the following formula:

Test Cell Size = 4 / Breakeven Response Rate.

The Breakeven Response Rate was addressed above in the BookBinders case study. The number "4" is a number that Hughes has found works successfully based on many studies he has performed. BookBinders Breakeven Response Rate was 8.3%. Using the above formula, you would need a minimum of 48 customers in each cell (4/0.083). BookBinders actually had 400 customers per cell, so they had more than adequate comfort in the significance of their test. In reality, BookBinders could have created as many as 1,041 cells if they were comfortable using the minimum of 48 per cell. As an example, they could have used deciles as opposed to quintiles and established 1,000 cells (10 x 10 x 10). The more cells the finer the analysis, but of course the law of diminishing returns will arise.

Other weighting considerations can be used for small files. If your Breakeven Response Rate is 3%, your minimum cell size would be 133 customers (4/0.03). Therefore, if you have 12,000 customers you could have about 90 cells (12,000/133). As such, a 5 x 5 x 4 (100 cells) or a 5 x 4 x 4 (80 cells) approach may be appropriate.

Conclusions

RFM, BI and data mining are all part of an evolutionary path that is common to many marketing organizations. While RFM has been practiced for over 40 years, it still holds great value for many organizations. Its merits include:

- Simplicity - easy to understand and implement

- Relatively low cost

- Proven ROI

- The demand on data requirements are relatively low in terms of variables required and the number of records

- Once utilized, it sets up a broader foundation (from an infrastructure and business case perspective) to undertake more sophisticated data mining efforts

RFM's challenges include:

- Contact fatigue can be a problem for the higher scoring customers. A high level cross-campaign communication strategy can help prevent this.

- Your lowest scoring customers may never hear from you. Again, a cross-campaign communications plan should ensure that all of your customers are communicated with periodically to ensure low scoring customers are given the opportunity to meet their potential. Also, data mining and the prediction of customer lifetime value can help address this shortcoming.

- RFM includes only three variables. Data mining typically finds RFM-based variables to be quite important in response models. But there are additional variables that data mining typically use (e.g., detailed transaction, demographic and firmographic) that help produce improved results. Moreover, data mining techniques can also increase response rates via the development of richer segment/cell profiles that can be used to vary offer content and incentives.

As stated before, successful marketing efforts require analytics and experimentation. RFM has proven itself as an effective approach to predicting response and improving profitability. It can be an important stage in your company's evolution in marketing analytics.



Source: http://ezinearticles.com/?RFM---A-Precursor-to-Data-Mining&id=1962283

Why Web Scraping Software Won't Help

How to get continuous stream of data from these websites without getting stopped? Scraping logic depends upon the HTML sent out by the web server on page requests, if anything changes in the output, its most likely going to break your scraper setup.

If you are running a website which depends upon getting continuous updated data from some websites, it can be dangerous to reply on just a software.

Some of the challenges you should think:

1. Web masters keep changing their websites to be more user friendly and look better, in turn it breaks the delicate scraper data extraction logic.

2. IP address block: If you continuously keep scraping from a website from your office, your IP is going to get blocked by the "security guards" one day.

3. Websites are increasingly using better ways to send data, Ajax, client side web service calls etc. Making it increasingly harder to scrap data off from these websites. Unless you are an expert in programing, you will not be able to get the data out.

4. Think of a situation, where your newly setup website has started flourishing and suddenly the dream data feed that you used to get stops. In today's society of abundant resources, your users will switch to a service which is still serving them fresh data.

Getting over these challenges

Let experts help you, people who have been in this business for a long time and have been serving clients day in and out. They run their own servers which are there just to do one job, extract data. IP blocking is no issue for them as they can switch servers in minutes and get the scraping exercise back on track. Try this service and you will see what I mean here.



Source: http://ezinearticles.com/?Why-Web-Scraping-Software-Wont-Help&id=4550594

Data Mining's Importance in Today's Corporate Industry

A large amount of information is collected normally in business, government departments and research & development organizations. They are typically stored in large information warehouses or bases. For data mining tasks suitable data has to be extracted, linked, cleaned and integrated with external sources. In other words, it is the retrieval of useful information from large masses of information, which is also presented in an analyzed form for specific decision-making.

Data mining is the automated analysis of large information sets to find patterns and trends that might otherwise go undiscovered. It is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, telecommunications and so on. Data Mining is based on mathematical algorithm and analytical skills to drive the desired results from the huge database collection.

It can be technically defined as the automated mining of hidden information from large databases for predictive analysis. Web mining requires the use of mathematical algorithms and statistical techniques integrated with software tools.

Data mining includes a number of different technical approaches, such as:

    Clustering
    Data Summarization
    Learning Classification Rules
    Finding Dependency Networks
    Analyzing Changes
    Detecting Anomalies

The software enables users to analyze large databases to provide solutions to business decision problems. Data mining is a technology and not a business solution like statistics. Thus the data mining software provides an idea about the customers that would be intrigued by the new product.

It is available in various forms like text, web, audio & video data mining, pictorial data mining, relational databases, and social networks. Data mining is thus also known as Knowledge Discovery in Databases since it involves searching for implicit information in large databases. The main kinds of data mining software are: clustering and segmentation software, statistical analysis software, text analysis, mining and information retrieval software and visualization software.

Data Mining therefore has arrived on the scene at the very appropriate time, helping these enterprises to achieve a number of complex tasks that would have taken up ages but for the advent of this marvelous new technology.


Source: http://ezinearticles.com/?Data-Minings-Importance-in-Todays-Corporate-Industry&id=2057401