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Answer Upon - Gaining Business Intelligence
They say TV rots your brain, but maybe sitcoms of the past serve a purpose beyond amusement after all. While most TV programs are fiction -- aside from the onslaught of reality TV, that is -- shows of the past are sometimes based on fact and can provide viewers with accurate depictions of the lives of others.Take a career in advertising, for instance. On shows like "Bewitched" and "Who's the Boss?" viewers are clued in on the lives of advertising agents at home, as well as in the office. So if you're interested in earning an advertising degree and striving for advertising careers, read on (and watch the reruns) -- you might learn something. Creativity Required in Advertising CareersWhen it comes to advertising careers, while an advertising degree is a necessity, creativity also plays a large role. As was the case with Darrin Stephens, the mortal husband advertising executive on "Bewitched." From time to time, the source of his creativity was his wife Samantha. While she vowed to give up her witchcraft to become an ordinary suburban housewife, she never really gave up her heritage. Sometimes creeping into her husband's advertising career, Samantha's quirky ways would help her husband advance.For example, there was a Halloween episode in which Samantha actively defied the fun holiday because it perpetuat
Propensity models
Propensity models – also known as predictive models – have proven to be very valuable in predicting which customers are most likely to purchase a certain product based on a set of current customers. The results of such a model can be directly used to develop more appropriately targeted marketing campaigns.
Other recognised techniques to extract information from datasets are database segmentation, neural networking, and wavelet analysis among others. It can be intimidating to choose which method will provide the best results. As shown above, analysis tools can differ greatly in their approach of the problem. It is therefore very important for a company to consult someone with extensive experience in data mining processes before going ahead with a business intelligence project. The best method to use will vary greatly depending on the time available to do the analysis, what the results will be used for, and the type of data that is available for the analysis.
An important point to consider is whether your analysis is guided by pre-defined questions or not. Predefined points of analysis are aimed at understanding certain types of behaviours by analysing relationships
From the free encyclopedia Wikipedia, courage, it also has been known as bravery and fortitude, it is the ability to confront fear, pain, danger, uncertainty or intimidation. These nouns appear as a contrast of the courage one.For many philosophers, the courage is associated with the the soul largeness. It is a sort of virtue. There are many species of courage. It has the courage for the fight against the injustices; the fight against the poverty; the courage to marry and to assume commitments with a person; the courage to take risks in new businesses and enterprises.But the principle feeling that contrast with courage is the fear. Since early children have learned to have fear of the dark one, of the animals, monsters and the other oldest resources of scaring them, in order to make them to obey us. Later, when they have grown, we demand them courage, even so we have prepared them all the time to feel fear.For some studious the fear is a creation of the proper man. It is something that we learn in our culture. It has a phrase that it says that the luck favors the audacious, the courageous ones, and it retracts the shy, the fearful ones.The courage is essential to start an online jobs work from home. It is not so different from offline business. But it demands a new perspective of making money.For insta
In an increasingly competitive world, using your client database smartly, to gain a better understanding of your number one asset – your customers – can make or break the success of your company.
Most companies use databases to store information about their current customers, previous customers, business partners, and potential customers. The challenge lies in finding a way to harness the useful information contained within these high volume databases in order to produce intelligent business solutions.
Business intelligence (BI) refers to the process for increasing the competitive advantage of a company by intelligent use of available data in decision-making. Business intelligence consists of sourcing the data, filtering out unimportant information, analysing the data, assessing the situation, developing solutions, analysing risks and then supporting the decisions made. This white paper describes the business intelligence process, some elementary methods of data mining, and how you can use business intelligence in your company.
Database Enhancement
The first step towards gaining business intelligence is to start with a ‘clean’ database. Incomplete and inaccurate data invariably translate into incorrect management decisions. Duplicate data is also a problem as it can wrongly weigh management decisions to one side. Whilst a good quality database does not automatically lead to intelligent management decision-making, it is a pre-requisite for all types of analysis that attempt to elicit intelligent management. We could draw an analogy with cooking, where starting with the right ingredients does not guarantee you will bake a good cake, but there is very little chance you will bake a good cake if you start with the wrong set of ingredients.
One of the primary reasons companies do not fully realise the potential competitive advantages they can gain from their own databases is the lack of proper integration of datasets across departments. Even though all the information might reside within the company, it may remain elusive due to a fragmentation of the data across incompatible databases. Regrouping all internal data into a single dataset or a series of interconnected datasets could be the single most useful step a company might take towards providing a solid foundation on which quality business intelligence can be developped.
In some cases, data entry errors and/or missing data can also severely impair the quality of information that can be derived from corporate databases. Sorting these issues can range from very straightforward fixes (e.g. matching one list against another) to more time consuming processes (e.g. contacting all client companies to update contact details of individuals working there). Ideally, all inaccuracies should be weeded out of the databases. However limited time and monetary constraints dictate that you should bear in mind how this database will be used. The level of accuracy required will vary greatly depending on the expected use for that data.
Data cleansing and database integration can provide significant advantages for a company over the medium to long term. However, they are both extremely time-consuming activities and can create a significant strain on internal resources, making them difficult for a company to justify. Hiring a third-party to do this job is often the best solution, allowing valuable information to be gained, without disrupting day-to-day business activities.
Data Mining
Analysing the information that your company stores in connection with all customer interactions can reveal a lot of remarkable facts about the buying behaviour of your customers, what motivates them and what might make them stop buying from you. It also provides a scientific method to monitor your business performance.
When deciding to mine information from a database, one is faced with a wide number of available techniques. Some of the more popular data mining methods are described below:
Statistical models
Basic statistical measurements – such as means, variances, and correlation coefficients – are useful in the early stages of data analysis to gain an overall view of the structure of the data. By revealing simple inter-relations within the data, statistical modelling can show which in-depth technique is likely to bring further information relevant to your interests.
Clustering
Clustering is a technique that aggregates data according to a pre-determined set of characteristics. It can be used to differentiate groups of customers that behave similarly on certain factors, for example it can classify customer behaviours according to credit worthiness, income, age or any other factor of interest.
CHAID Analysis
CHAID, which stands for Chi-square Automatic Interaction Detection, can be seen as the opposite of clustering, in the sense that the CHAID analysis starts with the overall database, and then splits it according to the most important variable until it achieves homogeneous sub-groups that cannot be split any further. A major advantage of this technique is that the results can be presented as an easy-to-read classification tree; each split in the tree being accredited to a single variable (e.g. credit worthiness, income, age, etc).
Propensity models
Propensity models – also known as predictive models – have proven to be very valuable in predicting which customers are most likely to purchase a certain product based on a set of current customers. The results of such a model can be directly used to develop more appropriately targeted marketing campaigns.
Other recognised techniques to extract information from datasets are database segmentation, neural networking, and wavelet analysis among others. It can be intimidating to choose which method will provide the best results. As shown above, analysis tools can differ greatly in their approach of the problem. It is therefore very important for a company to consult someone with extensive experience in data mining processes before going ahead with a business intelligence project. The best method to use will vary greatly depending on the time available to do the analysis, what the results will be used for, and the type of data that is available for the analysis.
An important point to consider is whether your analysis is guided by pre-defined questions or not. Predefined points of analysis are aimed at understanding certain types of behaviours by analysing relationships
It is not surprising at all when many foreign investors complained when they do business in China. Many wondered why their years of experience in the business world could not be applied in China immediately. Doing business is about building mutual trust and benefit amidst establishing relationship with people. If you do not understand your counterpart well, it will be quite difficult to establish good cooperation with him/her. An old Chinese saying goes: know yourself and your enemy well and you can fight a hundred battles without any fear of defeat. This greatly emphasized the importance of knowing and understanding your counterpart.Modern economic model differ greatly from the traditional one, whereby people in the past ‘fight’ till the last man standing. Today, people seek to achieve a “win-win” situation, and pursue long-term trade cooperation under a fair and healthy competition environment. Understanding factors such as China’s history, humanity and culture will be the key to investors’ success in China. As Western thinking and China’s traditional values do differ, encountering the culture differences is therefore inevitable, thus a better understanding of the cultural differences is necessary when doing business in China:1. Learn how to handle Guanxi (relationship)In China, Guanxi (relationship) is a complica
One of the primary reasons companies do not fully realise the potential competitive advantages they can gain from their own databases is the lack of proper integration of datasets across departments. Even though all the information might reside within the company, it may remain elusive due to a fragmentation of the data across incompatible databases. Regrouping all internal data into a single dataset or a series of interconnected datasets could be the single most useful step a company might take towards providing a solid foundation on which quality business intelligence can be developped.
In some cases, data entry errors and/or missing data can also severely impair the quality of information that can be derived from corporate databases. Sorting these issues can range from very straightforward fixes (e.g. matching one list against another) to more time consuming processes (e.g. contacting all client companies to update contact details of individuals working there). Ideally, all inaccuracies should be weeded out of the databases. However limited time and monetary constraints dictate that you should bear in mind how this database will be used. The level of accuracy required will vary greatly depending on the expected use for that data.
Data cleansing and database integration can provide significant advantages for a company over the medium to long term. However, they are both extremely time-consuming activities and can create a significant strain on internal resources, making them difficult for a company to justify. Hiring a third-party to do this job is often the best solution, allowing valuable information to be gained, without disrupting day-to-day business activities.
Data Mining
Analysing the information that your company stores in connection with all customer interactions can reveal a lot of remarkable facts about the buying behaviour of your customers, what motivates them and what might make them stop buying from you. It also provides a scientific method to monitor your business performance.
When deciding to mine information from a database, one is faced with a wide number of available techniques. Some of the more popular data mining methods are described below:
Statistical models
Basic statistical measurements – such as means, variances, and correlation coefficients – are useful in the early stages of data analysis to gain an overall view of the structure of the data. By revealing simple inter-relations within the data, statistical modelling can show which in-depth technique is likely to bring further information relevant to your interests.
Clustering
Clustering is a technique that aggregates data according to a pre-determined set of characteristics. It can be used to differentiate groups of customers that behave similarly on certain factors, for example it can classify customer behaviours according to credit worthiness, income, age or any other factor of interest.
CHAID Analysis
CHAID, which stands for Chi-square Automatic Interaction Detection, can be seen as the opposite of clustering, in the sense that the CHAID analysis starts with the overall database, and then splits it according to the most important variable until it achieves homogeneous sub-groups that cannot be split any further. A major advantage of this technique is that the results can be presented as an easy-to-read classification tree; each split in the tree being accredited to a single variable (e.g. credit worthiness, income, age, etc).
Propensity models
Propensity models – also known as predictive models – have proven to be very valuable in predicting which customers are most likely to purchase a certain product based on a set of current customers. The results of such a model can be directly used to develop more appropriately targeted marketing campaigns.
Other recognised techniques to extract information from datasets are database segmentation, neural networking, and wavelet analysis among others. It can be intimidating to choose which method will provide the best results. As shown above, analysis tools can differ greatly in their approach of the problem. It is therefore very important for a company to consult someone with extensive experience in data mining processes before going ahead with a business intelligence project. The best method to use will vary greatly depending on the time available to do the analysis, what the results will be used for, and the type of data that is available for the analysis.
An important point to consider is whether your analysis is guided by pre-defined questions or not. Predefined points of analysis are aimed at understanding certain types of behaviours by analysing relationships
In these days of restricted head count and tight budgets, the question of whether to outsource or hire in-house staff is more critical than ever. The technical publications function, however vital, is undergoing more scrutiny and also facing greater challenges than ever before. Companies that already employ an in-house technical publications department are looking at doing more with fewer resources. Start-ups, with no internal technical publications staff, are struggling with how to develop technical documents in the most cost-effective way.This article examines the pros and cons of entrusting all or part of the technical publications function to outside vendors. By examining a typical project, I will analyze costs and also answer questions about when to staff which functions internally.Numbers Speak for ThemselvesFor both start-up and mature companies, the basic questions are: When do you outsource your technical publications, and when do you staff technical publications internally? There are no quick answers to these questions, because there are several factors to consider. The easy part of the answer is straightforward number crunching. The more difficult part of the answer depends on how large your company is, the nature of your products/technologies, and how you operate internally. I can’t
Data cleansing and database integration can provide significant advantages for a company over the medium to long term. However, they are both extremely time-consuming activities and can create a significant strain on internal resources, making them difficult for a company to justify. Hiring a third-party to do this job is often the best solution, allowing valuable information to be gained, without disrupting day-to-day business activities.
Data Mining
Analysing the information that your company stores in connection with all customer interactions can reveal a lot of remarkable facts about the buying behaviour of your customers, what motivates them and what might make them stop buying from you. It also provides a scientific method to monitor your business performance.
When deciding to mine information from a database, one is faced with a wide number of available techniques. Some of the more popular data mining methods are described below:
Statistical models
Basic statistical measurements – such as means, variances, and correlation coefficients – are useful in the early stages of data analysis to gain an overall view of the structure of the data. By revealing simple inter-relations within the data, statistical modelling can show which in-depth technique is likely to bring further information relevant to your interests.
Clustering
Clustering is a technique that aggregates data according to a pre-determined set of characteristics. It can be used to differentiate groups of customers that behave similarly on certain factors, for example it can classify customer behaviours according to credit worthiness, income, age or any other factor of interest.
CHAID Analysis
CHAID, which stands for Chi-square Automatic Interaction Detection, can be seen as the opposite of clustering, in the sense that the CHAID analysis starts with the overall database, and then splits it according to the most important variable until it achieves homogeneous sub-groups that cannot be split any further. A major advantage of this technique is that the results can be presented as an easy-to-read classification tree; each split in the tree being accredited to a single variable (e.g. credit worthiness, income, age, etc).
Propensity models
Propensity models – also known as predictive models – have proven to be very valuable in predicting which customers are most likely to purchase a certain product based on a set of current customers. The results of such a model can be directly used to develop more appropriately targeted marketing campaigns.
Other recognised techniques to extract information from datasets are database segmentation, neural networking, and wavelet analysis among others. It can be intimidating to choose which method will provide the best results. As shown above, analysis tools can differ greatly in their approach of the problem. It is therefore very important for a company to consult someone with extensive experience in data mining processes before going ahead with a business intelligence project. The best method to use will vary greatly depending on the time available to do the analysis, what the results will be used for, and the type of data that is available for the analysis.
An important point to consider is whether your analysis is guided by pre-defined questions or not. Predefined points of analysis are aimed at understanding certain types of behaviours by analysing relationships
Over the years I have heard the frustrations from students about the lack of knowledge when it comes to choosing a job or career after college. They know they should have some type of idea but from what I have gathered most do not. Even though their parents are pushing them to get a job they have no idea what they are suppose to be doing. More importantly they have no idea what they want to do. It is one thing to have a job but it is another thing to have a job you love doing!Therefore, I have put together a plan for college students that should give every student, who sticks to the plan, a guide to help them determine what future career they may want to explore. At the crux of this plan are two words… experiential education. Every student must get out of the classroom and into the real world, while they are in school in order to determine what they want to do with their life. It is extremely difficult to ask someone what they want to do with their life if they have no idea what their options are. Ignorance is never bliss when it comes to career development!Here is a conversation that has taken place between parents and college seniors thousands of times. Can you relate?What are you going to do with your degree?... "I don't know?"Where have you applied for a job?... "Do they pay people for updating t
Statistical models
Basic statistical measurements – such as means, variances, and correlation coefficients – are useful in the early stages of data analysis to gain an overall view of the structure of the data. By revealing simple inter-relations within the data, statistical modelling can show which in-depth technique is likely to bring further information relevant to your interests.
Clustering
Clustering is a technique that aggregates data according to a pre-determined set of characteristics. It can be used to differentiate groups of customers that behave similarly on certain factors, for example it can classify customer behaviours according to credit worthiness, income, age or any other factor of interest.
CHAID Analysis
CHAID, which stands for Chi-square Automatic Interaction Detection, can be seen as the opposite of clustering, in the sense that the CHAID analysis starts with the overall database, and then splits it according to the most important variable until it achieves homogeneous sub-groups that cannot be split any further. A major advantage of this technique is that the results can be presented as an easy-to-read classification tree; each split in the tree being accredited to a single variable (e.g. credit worthiness, income, age, etc).
Propensity models
Propensity models – also known as predictive models – have proven to be very valuable in predicting which customers are most likely to purchase a certain product based on a set of current customers. The results of such a model can be directly used to develop more appropriately targeted marketing campaigns.
Other recognised techniques to extract information from datasets are database segmentation, neural networking, and wavelet analysis among others. It can be intimidating to choose which method will provide the best results. As shown above, analysis tools can differ greatly in their approach of the problem. It is therefore very important for a company to consult someone with extensive experience in data mining processes before going ahead with a business intelligence project. The best method to use will vary greatly depending on the time available to do the analysis, what the results will be used for, and the type of data that is available for the analysis.
An important point to consider is whether your analysis is guided by pre-defined questions or not. Predefined points of analysis are aimed at understanding certain types of behaviours by analysing relationships
Need for ServiceMost manufactures view service as an added expense and burden. Their goal is to build a product that does not require service. Upper management and sales usually present design with a need for a product, and when the product has been designed and sales estimates have been made, it is up to manufacturing to produce the product at the lowest possible cost. Serviceability is usually over looked unless the company has a strong service department that becomes involved in the design and manufacturing stages.New Product PhaseDuring the new product stage manufacturing may look to the service department for flaws or early problems. This is usually a very short time frame with few numbers of equipment to work with. So it is very important to keep the factory advised of all failures during this period and supply as much detail as possible. It is very tempting to make easy repairs at this stage and not inform manufacturing, however these problems will continue to occur throughout the life of the product, resulting in a poor image for the company. A tempting trap for the service department, is to find an easy fix and not share the problem with manufacturing. This problem is usually lumped into the list of easy repairs shared between repair technicians, and in some cases
Propensity models
Propensity models – also known as predictive models – have proven to be very valuable in predicting which customers are most likely to purchase a certain product based on a set of current customers. The results of such a model can be directly used to develop more appropriately targeted marketing campaigns.
Other recognised techniques to extract information from datasets are database segmentation, neural networking, and wavelet analysis among others. It can be intimidating to choose which method will provide the best results. As shown above, analysis tools can differ greatly in their approach of the problem. It is therefore very important for a company to consult someone with extensive experience in data mining processes before going ahead with a business intelligence project. The best method to use will vary greatly depending on the time available to do the analysis, what the results will be used for, and the type of data that is available for the analysis.
An important point to consider is whether your analysis is guided by pre-defined questions or not. Predefined points of analysis are aimed at understanding certain types of behaviours by analysing relationships between various pre-decided influencing factors. For example, a predefined analysis of customer service Vs sales would illustrate the effect of good and bad customer service on sales, and would answer questions such as how important customer service is to customers and how much it influences future sales. On the contrary, the objective of an open-ended analysis is to discover trends that are not anticipated by ordinary immersion in the day-to-day business. Performing an open-ended analysis internally is often impaired by the expectations brought on by individuals working within the company.
The techniques used to analyse data are complex. In order for your company to be able to use the results of the data analysis, it is crucial that the results should not be clouded by the complexity of the calculations but are delivered in a straightforward manner.
Intelligent Marketing
It is important for a company to recognise that a good understanding of its customers is useful only to the extent to which this knowledge can be translated into real business practices. Business intelligence refers not only to the data analysis in itself, but also to how you relate the results from the data analysis to every day business decisions and how you translate the recommended actions stemming from the analysis into live campaigns.
It is therefore important for you to ensure that the marketing department in your company interacts with the data analysts constantly throughout the process. That way, when the data analysis is complete, the marketing personnel will already be in tune with the issues the company is facing, and will be able to develop campaigns to capitalise on opportunities and strategies to mend weaknesses quickly and effectively.
Detailed analysis of your customer data will provide you insight into their needs and wants. The exercise will analyse and segment customers’ buying patterns and identify potential services that are in demand. You can use this information to shorten response times to market changes, which then allows for better alignment of your products and services with your customers’ needs.
An in-depth understanding of your customers, provided through comprehensive data-analysis, will also allow you to pick and target better prospects, achieve a higher response rate from marketing programs, and at the same time identify reasons for customer attrition and create or alter programs and services accordingly.
Understanding how external market conditions affect your business will enable you to react quickly to future changes in the market. Finally, understanding customer behaviour and the way they use your products and services will enable your company to improve its service to its current client base as well as to target new business more effectively.
Visit http://www.accuracast-marketing-agency.co.uk/business-intelligence.shtml to learn more about gaining business intelligence.
About AccuraCast
AccuraCast is an integrated marketing, business intelligence and data analysis agency, providing small and medium sized companies in the UK a more accurate picture of their business environment via comprehensive data analysis, business intelligence, and marketing consultancy services.
AccuraCast helps companies gain a better understanding of their customers and market their products and services more effectively. The company uses high-tech data analysis methodologies to investigate client databases smartly, and proven sales and marketing methods to reach the target markets. AccuraCast delivers costumer specific marketing solutions and information based on tailor-made analysis of the databases, allowing companies to gain the necessary edge over the competition.
© AccuraCast Limited 2004
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