How to Increase Stamina in Basketball with Physical Exercises Essay Example

How to Increase Stamina in Basketball with Physical Exercises Essay Example How to Increase Stamina in Basketball with Physical Exercises Paper How to Increase Stamina in Basketball with Physical Exercises Paper Basketball is a sport that needs high stamina, because basketball is a fast and energetic sport. Adrenaline is high in every game makes heart rate beating faster and only people who have high stamina that can hold out to play until the end of the game. Basketball players have to train hard to build the stamina in order to the body does not get tired quickly when playing basketball. Basketball players can do many training to improve stamina, and the best way to stamina is physical exercises. Physical exercises are very important to improve stamina of basketball players; players who never do physical exercises do not have enough stamina to play basketball until the end of the game. It is easy to improve stamina in basketball by following these three instructions, which are doing interval training, suicide training, and jumping rope. The first exercise to improve stamina for basketball players is interval training. Interval training translates into the game of basketball at times when there is fast running mixed in with jogging. Begin the exercises with warming up 5 to 10 minutes; warming up by jogging 1 to 3 laps around the court. After do warming up, start the main exercises which is interval training. Do the interval training with distance 100 meters, do sprint 50 meters, then jogging 50 meters, and walk back; or with distance 100 meters, do sprint 50 meters, then stride 50 meters, and walk back. Basketball players can manage the distance to do the interval training. After do interval training, take a short break for 15 minutes before start the next exercise. Interval training is helping to improve the stamina of basketball players and key in to reach the fullest potential as a basketball player. The next exercise is suicide training which is one of physical exercises in basketball to improve stamina and quickness to dribble of basketball players. Suicide is technical term for sprint training in basketball. After take a short rest, basketball players can continue to start the suicide training. Start suicide training from the baseline, run to the free-throw line, touch the floor and run back to the baseline. Then, run to half-court line, touch the floor and run back to the baseline. Then, go to the free-throw line opponent, touch the floor and run back. Finally, run coast-to-coast, touch the other baseline and run back. In this case do not slow down or stop running. Try this particular move for 20 minutes and then take a short break for 15 minutes to continue the next exercise. Suicide exercise is very useful to improve stamina and quickness to dribble for basketball players. The last exercise to improve stamina in basketball is doing jumping rope. Jumping rope is body exercise and it is excellent to improve stamina and footwork, especially for basketball players. After take a short break, basketball players continue jumping rope training. Firstly, choose the rope in accordance with the desired size. With rope folded in half, the rope should reach nearly to the shoulders of basketball players who would practice. Then, grab the jump rope by its ends, or the handles, one handle for each hand. Put the jump rope behind butt and let the loop hang behind crotch. Throw the jump rope over head and when it meets feet jump over it. After get better at jumping rope forwards, do the other trick of jumping rope; try to do jumping rope backwards. Start with the rope in front of feet and throw it over head to the back. Jump over the rope when it reaches the foot. Try this particular move for 15 minutes. A lot of people make mistake of bending the knees because it is easier to do the jumping rope. With doing jumping rope exercise, basketball players can build strong stamina and vertical jumping. Improving the stamina of basketball players is not difficult. By doing physical exercises such as interval training, suicide training, and jumping rope training routinely; these would make basketball players more quickly to have strong stamina. Physical training begins with warming up for 5 to 10 minutes, and then continues with the main exercises. The first is interval training which is doing by combining sprints and jogging with a distance of 100 meters or more. After do the interval training take a short break for 15 minutes. Continue with suicide exercises for 20 minutes, and then break for 15 minutes. The last exercise is jumping rope training, do jumping rope training for 15 minutes. Finish off all the exercises with flexibility exercises. In this case, the important things are managing the time for training and do the physical exercises regularly. With doing physical exercises for 1 to 2 hours each day, the stamina of basketball players can improve quickly. Bibliography 1. ehow. com/how_4830064_build-stamina-basketball. html 2. http://findarticles. com/p/articles/mi_m1608/is_10_23/ai_n21119011/pg_2/? tag=content;col1 3. http://basket-beezer10. blogspot. com/2010_03_01_archive. html 4. ehow. com/way_5434775_stamina-building-exercises. html

Humanity sammary 1 Essay Example | Topics and Well Written Essays - 500 words

Humanity sammary 1 - Essay Example She prays to Artemis, asking to be killed so that she could be with Odysseus in the Underworld. Penelope’s cries wakes up Odysseus, who prays to Zeus to give him a sign, and was reciprocated with a bang of thunder from Zeus. Odysseus asks for another sign and this time, one of Odysseus maids asks that this be the suitors last day. These signs were enough to encourage Odysseus to avenge himself on the suitors. Telemakhos gets up and the house springs to life as he puts on his full array. Eurykleia tells the maids to clean the house and fetch water for a feast day. Men went inside, bringing firewood, while the swineherd brings pigs, and the goatherd and two shepherds bring goats. Melanthios insults the beggar, who is actually Odysseus, but Odysseus restrains himself from fighting back. Philoitios was much kinder as he extends a warm welcome to the beggar saying that he reminds him of his master, Odysseus. Philoitios mentions that he also wants the suitors to be gone because they were making excessive demands on his cattle. The beggar tells him that Odysseus will soon come to kill them and to this, Philoitios replies that Odysseus can count on his help. Meanwhile, the suitors plot to kill Telemakhos, when an eagle with a dove in its talons flies by and so they drop the plan. Telemakhos seats Odysseus alone and warns the suitors to keep their hands and tongues to themselves. However, Athena prompts the suitors to continue abusing Odysseus and so Ktesippos throws a cow’s foot which did not hit Odysseus. Telemekhos becomes angry and threatens Ktesippos and the other suitors. The suitors conceded and agreed not to make fun of the beggar anymore. Then, Agelaos tells Telemakhos to talk with his mother and encourage her to marry one of them. Telemakhos says that he does encourage his mother but cannot force her. To this, the suitors burst out with laughter. Then, Theoklymenos the visionary tells

A Humorous Experience Essay Example | Topics and Well Written Essays - 1500 words

A Humorous Experience - Essay Example The place was essentially a ghost town, which made this the perfect setting for the following story, which is a little bit scary for someone who is in a foreign country by oneself, off on her own, doing her own thing-and unfortunately not being smart enough to stay with the group. Let me preface this by saying that originally, what happened was not a very humorous experience. Getting lost in a foreign country is not fun. I had a terrible feeling in the pit of my stomach for most of the experience because I was terrified of being left behind by my group in France. Running around not knowing where you're going is not fun. Knowing that you've made mistakes is not fun. Having that 'lost' feeling is not fun. Having to ask strangers for directions is not fun. Looking back, however, it seems very funny. First, I will tell it how the story happened. There were a group of about thirty of us-about half of us were American high school students, and the other half were Spanish high school host students. We were eating lunch on the beach that we had brought from home, and I told the group (I'm paraphrasing here), "Yeah, well, I'm going to head off now by myself." I told them this in no uncertain terms. No one seemed to think this odd. After all, Biarritz was a little town; it wasn't very large; how could I get lost I must preface this story... Seven Streets is basically is a shopping district of seven streets horizontally lined up next to each other. I had run out of money, which was back then the Spanish peseta and not yet the Euro. I had to ask the people at the store to hold the postcards for me while I ran to the local bank on Siete Calles. When I got to the bank, somehow I was able to jump the line. I don't know if it was because they were feeling sorry for my plight of being in a terrible hurry or what it was, but I asked some elderly Spanish ladies to translate for me so I could get some Spanish pesetas quickly, in order to get back to the store in order to pay for the postcards faster. Meanwhile, I was late in getting back to our meeting place at the church in the center of town and everyone feared the worst for me since I had not gotten back on time-when in reality I was just buying about 100 or so postcards that were on sale! I promised not to be late again and that was that. Well, little did I know that I would again find myself in another pickle. This time was really not much different. After I had told the Spanish students "So long" at lunch and had gone along on my merry way, I found myself going to various stores in Biarritz, because really this place was quite interesting. They had all sorts of different knick-knacks that were fun to look at, and it really was quite a charming little town. It was the kind of place you could get lost in. That was the key word. The kind of town you could get lost in. Unfortunately, I was going to be one of those people in a few minutes. I found myself finally at a French confectionary and candy store investigating all the different kinds of sweets that this particular place

Pre-Destination V.S Free

Pre-Destination V.S Free Will Essay For years Christians have argued about what role God has in humans attaining salvation. The most popular belief in American culture is the concept of free will. Free will is the belief that coming to Christ and being saved is a freewill choice of the person. Most churches believe this concept to be true at least to some degree. The other belief is the concept of Predestination. Predestination is the belief that God chooses who to save and who to damn. The biggest denomination in the United States that believes this is the Calvinists or more commonly known as the Reformed denomination. The debate will probably continue for many years to come. By reading Romans 9:1-29 we can tell clearly which concept Paul believes to be true. While I read Romans 9:1-29 I kept clearly in my mind the two beliefs of freewill and predestination. After reading it was apparent to me that Paul believes strongly in predestination. This, in my opinion, goes against human nature. I, at least, find it very hard to believe that if God chooses not to extend grace to a person that person cannot attain salvation no matter what they believe or what they do. Paul uses an example about Jacob and Esau. In Romans 9: 10-13 Paul uses Malachi 1:2-3 that says that â€Å" I have loved Jacob, but I have loved Jacob† Paul then says that God had decided that before they were even born so as it says in verse 11-12 â€Å" that Gods purpose of election might continue, not by works, but by his call. † If Paul is right about this and you interpret the Bible literally than predestination has to be true. It is completely possible that Paul is biased though when writing about predestination. Paul believes strongly in salvation by faith not works. In Romans 3: 27- 28 Paul says â€Å"Where, then, is boasting? It is excluded. Because of what law? The law that requires works? No, because of the law that requires faith. For we maintain that a person is justified by faith apart from the works of the law. † This is just one of many examples of how much Paul hates the idea of faith by works. There are many other examples of this in books written by Paul outside of Romans that convey the same message. Since Paul believes strongly in salvation by faith this would, in theory, make him lean towards predestination. Freewill means that we as humans make a choice to believe in God and be saved. Paul would see this as an example of justification by works and he clearly states in Ephesians 2:8-9 â€Å"For it is by grace you have been saved, through faith and this is not from yourselves, it is the gift of God not by works, so that no one can boast. † Paul believes that nothing we can do nothing to save ourselves which is the main idea of freewill. This makes Paul potentially biased toward predestination. I believe that this passage isnt trying to address personal salvation as a main point, but I think we infer Pauls view on personal salvation through the verse. I believe that Paul was more trying to point out that we can do nothing to save ourselves. It is completely up to God. Paul was trying to stress that firstly, but then through that seems to make a case, as far as personal salvation goes, for predestination. He specifically mentions how he picked Jacob over Esau. If God chooses individually like that then I, at least, deduce from this passage according to Paul that God must choose who to save on a personal level. My rational human side tells me that predestination cannot be right, but then I read Romans and Paul says that predestination is right and freewill is wrong. The question then is if I believe Paul just because that is his opinion, even though it is most likely biased, or do I believe what seems right to me? Im still torn between the two because what I want to believe is contradicted by Paul. Maybe well never know for sure because the concept of God is impossible for our minds to completely understand in the first place.

Internet Inventions :: essays research papers

Internet Inventions Several inventions have changed the way people communicate with each other. From the old fashioned telegraph to today's modern electronic forms of communicating, people have beencreating easier ways to correspond. Electronic communication, such as e-mail and other internet offerings, have created a cheap and incredibly fast communications system which is gaining steady popularity. E-mail is basically information, usually in letter form,addressed to a destination on the internet. The internet is aninternational web of interconnected networks--in essence,  anetwork of networks; these consist of government, education, and business networks. Software on these networks between the source and destination networks "read" the addresses on packets and forward them toward their destinations. E-mail is a very fast and efficient way of sending information to any internet location. Once an e-mail is sent, it arrives at its destination almost instantly. This provides people with a way to communicate with people anywhere in the world quickly without the costs of other forms of communicating such as telephone calls or postage for letters. The savings to be gained from e-mail were enough of an inducement for many businesses to invest heavily in equipment and network connections in the early 1990s. The employees of a large corporation may send hundreds of thousands of pieces of E-mail over the Internet every month, thereby cutting back on postal and telephone costs. It is not uncommon to find internet providers from twenty to thirty dollars a month for unlimited access to internet features. Many online services such as America Online and Prodigy offer e-mail software and internet connections which work in an almost identical way, however, the cost is more expensive. The World Wide Web (WWW) and USENET Newsgroups are amongother internet offerings which have changed the way people communicate with each other. The WWW can be compared to a electronic bulletin board where information consisting o fanything can be posted. One can create visual pages consisting of text and graphics which become viewable to anyone with WWW access. Anything from advertisements to providing people with information and services can be found on the WWW. File transfers between networks can also be accomplished on the WWW though Gopher and FTP (File Transfer Protocol) sites. Newsgroups are very similar, but run in a different way. Newsgroups basically create a forum where people can discuss a vast array of subjects. There are thousands of newsgroups available. Once one finds a subject that interests them, they may post notes which are visible to anyone visiting that particular newsgroup, and others may respond to such notes. Again, this can be advertising, information, or, more commonly, gossip. Though the internet can be a convenient way of communication, it can become

Marketing Segmentation Essay

Market segmentation is the process of dividing up a market into more-or-less homogenous subsets for which it is possible to create different value propositions. At the end of the process the company can decide which segment(s) it wants to serve. If it chooses, each segment can be served with a different value proposition and managed in a different way. Market segmentation processes can be used during CPM for two main purposes. They can be used to segment potential markets to identify which customers to acquire, and to cluster current customers with a view to offering differentiated value propositions supported by different relationship management strategies. In this discussion we’ll focus on the application of market segmentation processes to identify which customers to acquire. What distinguishes market segmentation for this CRM purpose is its very clear focus on customer value. The outcome of the process should be the identification of the value potential of each identified segment. Companies will want to identify and target customers that can generate profit in the future: these will be those customers that the company and its network are better placed to serve and satisfy than their competitors. Market segmentation in many companies is highly intuitive. The marketing team will develop profiles of customer groups based upon their insight and experience. This is then used to guide the development of marketing strategies across the segments. In a CRM context, market segmentation is highly data dependent. The data might be generated internally or sourced externally. Internal data from marketing, sales and finance records are often enhanced with additional data from external sources such as marketing research companies, partner organizations in the company’s network and data specialists (see Figure 5.2 ). The market segmentation process can be broken down into a number of steps: 1. identify the business you are in 2. identify relevant segmentation variables 3. analyse the market using these variables 4. assess the value of the market segments 5. select target market(s) to serve. Sales forecasting: Slide #6 (p. 136-8) The second discipline that can be used for CPM is sales forecasting. One major issue commonly facing companies that conduct CPM is that the data available for clustering customers takes a historical or, at best, present day view. The data identifies those customers who have been, or presently are, important for sales, profit or other strategic reasons. If management believes the future will be the same as the past, this presents no problem. However, if the business environment is changeable, this does present a problem. Because CPMs goal is to identify those customers that will be strategically important in the future, sales forecasting can be a useful discipline. Sales forecasting, some pessimists argue, is a waste of time, because the business environment is rapidly changing and unpredictable. Major world events such as terrorist attacks, war, drought and market-based changes, such as new products from competitors or high visibility promotional campaigns, can make any sales forecas ts invalid. There are a number of sales forecasting techniques that can be applied, providing useful information for CPM. These techniques, which fall into three major groups, are appropriate for different circumstances. ââ€"  qualitative methods: customer surveys sales team estimates ââ€"  time-series methods: moving average exponential smoothing time-series decomposition ââ€"  causal methods: leading indicators regression models. Qualitative methods are probably the most widely used forecasting methods. Customer surveys ask consumers or purchasing officers to give an opinion on what they are likely to buy in the forecasting period. This makes sense when customers forward-plan their purchasing. Data can be obtained by inserting a question into a customer satisfaction survey. For example, ‘In the next six months are you likely to buy more, the same or less from us than in the  current period? ’ And, ‘If more, or less, what volume do you expect to buy from us? ’ Sometimes, third party organizations such as industry associations or trans-industry groups such as the Chamber of Commerce or the Institute of Directors collect data that indicate future buying intentions or proxies for intention, such as business confidence. Sales team estimates can be useful when salespeople have built close relationships with their customers. A key account management team might be well placed to generate s everal individual forecasts from the team membership. These can be averaged or weighted in some way that reflects the estimator’s closeness to the customer. Account managers for Dyno Nobel, a supplier of commercial explosives for the mining and quarrying industries, are so close to their customers that they are able to forecast sales two to three years ahead. Operational CRM systems support the qualitative sales forecasting methods, in particular sales team estimates. The CRM system takes into account the value of the sale, the probability of closing the sale and the anticipated period to closure. Many CRM systems also allow management to adjust the estimates of their sales team members, to allow for overly optimistic or pessimistic salespeople. Time-series approaches take historical data and extrapolate them forward in a linear or curvilinear trend. This approach makes sense when there are historical sales data, and the assumption can be safely made that the future will reflect the past. The moving average method is the simplest of these. This takes sales in a number of previous periods and averages them. The averaging process reduces o r eliminates random variation. The moving average is computed on successive periods of data, moving on one period at a time, as in Figure 5.10 . Moving averages based on different periods can be calculated on historic data to generate an accurate method. A variation is to weight the more recent periods more heavily. The rationale is that more recent periods are better predictors. In producing  an estimate for year 2009 in Figure 5.10 , one could weight the previous four years’ sales performance by 0.4, 0.3, 0.2, and 0.1, respectively, to reach an estimate. This would generate a forecast of 5461. This approach is called exponential smoothing. The decomposition method is applied when there is evidence of cyclical or seasonal patterns in the historical data. The method attempts to separate out four components of the time series: trend factor,  cyclical factor, seasonal factor and random factor. The trend factor is the longterm direction of the trend after the other three elements are removed. The cyclical factor represents regular long-term recurrent influences on sales; seasonal influences generally occur within annual cycles. It is sometimes possible to predict sales using leading indicators. A leading indicator is some contemporary activity or event that indicates that another activity or event will happen in the future. At a macro level, for example, housing starts are good predictors of future sales of kitchen furniture. At a micro level, when a credit card customer calls into a contact centre to ask about the current rate of interest, this is a strong indicator that the customer will switch to another supplier in the future. Regression models work by employing data on a number of predictor variables to estimate future demand. The variable being predicted is called the dependent variable; the variables being used as predictors are called independent variables. For example, if you wanted to predict demand for cars (the dependent variable) you might use data on population size, average disposable income, average car price for the category being predicted and average fuel price (the independent variables). The regression equation can be tested and validated on historical data before being adopted. New predictor variables can be substituted or added to see if they improve the accuracy of the forecast. This can be a useful approach for predicting demand from a segment. Activity-Based Costing: Slide #7 (p. 138-40) Customer Acquisition costs Terms of Trade Customer service costs Working capital costs Activity-based costing The third discipline that is useful for CPM is activity-based costing. Many companies, particularly those in a B2B context, can trace revenues to customers. In a B2C environment, it is usually only possible to trace revenues to identifiable customers if the company operates a billing system requiring customer details, or a membership scheme such as a customer club, store-card or a loyalty programme. In a B2B context, revenues can be tracked in the sales and accounts databases. Costs are an entirely different matter. Because the goal of CPM is to cluster customers according to their strategic value, it is desirable to be able to identify which customers are, or will be, profitable. Clearly, if a company is to understand customer profitability, it has to be able to trace costs, as well as revenues, to customers. Costs do vary from customer to customer. Some customers are very costly to acquire and serve, others are not. There can be considerable variance across the customer base within several categories of cost: ââ€"  customer acquisition costs : some customers require considerable sales effort to move them from prospect to fi rst-time customer status: more sales calls, visits to reference customer sites, free samples, engineering advice, guarantees that switching costs will be met by the vendor ââ€"  terms of trade : price discounts, advertising and promotion support, slotting allowances (cash paid to retailers for shelf space), extended invoice due dates ââ€"  customer service costs : han dling queries, claims and complaints, demands on salespeople and contact centre, small order sizes, high order frequency, just-in-time delivery, part load shipments, breaking bulk for delivery to multiple sites ââ€"  working capital costs : carrying inventory for the customer, cost of credit. Traditional product-based or general ledger costing systems do not provide this type of detail, and do not enable companies to estimate customer profitability. Product costing systems track material, labour and energy costs to products, often comparing actual to standard costs. They do not, however, cover the customer-facing activities of marketing, sales and service. General ledger costing systems do track costs across all parts of the business, but are normally too highly aggregated to establish which customers or segments are responsible for generating those costs. Activity-based costing (ABC) is an approach to costing that splits costs into two groups: volume-based costs and order-related costs. Volume based (product-related) costs are variable against the size of the order, but fixed per unit for any order and any customer. Material and direct labour costs are examples. Order-related (customer-related) costs vary according to the product and process requirements of each particular customer. Imagine two retail customers, each purchasing the same volumes of product from a manufacturer. Customer 1 makes no product or process demands. The sales revenue is $5000; the gross margin for the vendor is $1000. Customer 2 is a different story: customized  product, special overprinted outer packaging, just-in-time delivery to three sites, provision of point-of-sale material, sale or return conditions and discounted price. Not only that, but Customer 2 spends a lot of time agreeing these terms and conditions with a salesperson who has had to call three times before closing the sale. The sales revenue is $5000, but after accounting for product and process costs to meet the demands of this particular customer, the margin retained by the vendor is $250. Other things being equal, Customer 1 is four times as valuable as Customer 2. Whereas conventional cost accounti ng practices report what was spent, ABC reports what the money was spent doing. Whereas the conventional general ledger approach to costing identifies resource costs such as payroll, equipment and materials, the ABC approach shows what was being done when these costs were incurred. Figure 5.11 shows how an ABC view of costs in an insurance company’s claims processing department gives an entirely different picture to the traditional view. ABC gives the manager of the claims-processing department a much clearer idea of which activities create cost. The next question from a CPM perspective is ‘ which customers create the activity? ’ Put another way, which customers are the cost drivers? If you were to examine the activity cost item ‘ Analyse claims: $121 000 ’ , and find that 80 per cent of the claims were made by drivers under the age of 20, you’d have a clear understanding of the customer group that was creating that activity cost for the business. CRM needs ABC because of its overriding goal of generating profitable relationships with customers. Unless there is a costing system in place to trace costs to customers, CRM will find it very difficult to deliver on a promise of improved customer profitability. Overall, ABC serves customer portfolio management in a number of ways: 1. when combined with revenue figures, it tells you the absolute and relative levels of profit generated by eac h customer, segment or cohort 2. it guides you towards actions that can be taken to return customers to profit 3. it helps prioritize and direct customer acquisition, retention and development strategies 4. it helps establish whether customization and other forms of value creation for customers pay off. ABC sometimes justifies management’s confidence in the Pareto principle, otherwise known as the 80:20 rule. This rule suggests that  80 per cent of profits come from 20 per cent of customers. ABC tells you which customers fall into the important 20 per cent. Research generally supports the 80: 0 rule. For example, one report from Coopers and Lybrand found that, in the retail industry, the top 4 per cent of customers account for 29 per cent of profits, the next 26 per cent of customers account for 55 per cent of profits and the remaining 70 per cent account for only 16 per cent of profits. Lifetime Value Estimation: Slide# 8 (p. 141-2) The fourth discipline that can be used for CPM is customer lifetime value (LTV) estimation, which was first introduced in Chapter 2. LTV is measured by computing the present day value of all net margins (gross margins less cost-to-serve) earned from a relationship with a customer, segment or cohort. LTV estimates provide important insights that guide companies in their customer management strategies. Clearly, companies want to protect and ring-fence their relationships with customers, segments or cohorts that will generate significant amounts of profit. Sunil Gupta and Donald Lehmann suggest that customer lifetime value can be computed as follows: Application of this formula means that you do not have to estimate customer tenure. As customer retention rate rises there is an automatic lift in customer tenure, as shown in Table 2.2 in Chapter 2. This formula can be adjusted to consider change in both future margins and retention rates either up or down, as described in Gupta and Lehmann’s book Managing Customers as Investments. The table can be used to assess the impact of a number of customer management strategies: what would be the impact of reducing cost-toserve by shifting customers to low-cost self-serve channels? What would be the result of cross-selling higher margin products? What would be the outcome of a loyalty programme designed to increase retention rate from 80 to 82 per cent? An important additional benefit of this LTV calculation is that it enables you to estimate a company’s value. For example, it has been computed that the LTV of the average US-based American Airlines customer is $166.94. American Airlines has 43.7 million such customers, yielding an estimated company value of $7.3 billion. Roland Rust and his co-researchers noted that, given the absence of international  passengers and freight considerations from this computation, it was remarkably close to the company’s market capitalization at the time their research was undertaken. Clustering (144): slide #9 Clustering techniques are used to find naturally occurring groupings within a dataset. As applied to customer data, these techniques generally function as follows: 1. Each customer is allocated to just one group. The customer possesses attributes that are more closely associated with that group than any other group. 2. Each group is relatively homogenous. 3. The groups collectively are very different from each other. In other words, clustering techniques generally try to maximize both within-group homogeneity and between-group heterogeneity. There are a number of clustering techniques, including CART (classification and regression trees) and CHAID (chi-square automatic interaction detection).7 Once statistically homogenous clusters have been formed they need to be interpreted. CRM strategists are often interested in the future behaviours of a customer: segment, cohort or individual. Customers ’ potential value is determined by their propensity to buy products in the future. Data miners can build predictive models by examining patterns and relationships within historic data. Predictive models can be generated to identify: 1. Which customer, segment or cohort is most likely to buy a given product? 2. Which customers are likely to default on payment? 3. Which customers are most likely to defect (churn)? Data analysts scour historic data looking for predictor and outcome variables. Then a model is built and validated on these historic data. When the model seems to work well on the historic data, it is run on contemporary data, where the predictor data are known but the outcome data are not. This is known as ‘ scoring ’ . Scores are answers to questions such as the propensity-to-buy, default and churn questions listed above. Predictive modelling is based on three assumptions, each of which may be true to a greater or lesser extent: 1. The past is a good predictor of the future †¦ BUT this may not be true. Sales of many products are cyclical or seasonal. Others have fashion or fad lifecycles. 2. The data are available †¦ BUT this may not be true. Data used to train the model may no longer be collected. Data may be too costly to collect, or may be in the wrong format. 3. Customer-related databases contain what you want to predict †¦ BUT this may not be true. The data may not be available. If you want to predict which customers are most likely to buy mortgage protection insurance, and you only have data on life policies, you will not be able to answer the question. Two tools that are used for predicting future behaviours are decision trees and neural networks. Decision trees (145): slide #9 Decision trees are so called because the graphical model output has the appearance of a branch structure. Decision trees work by analyzing a dataset to find the independent variable that, when used to split the population, results in nodes that are most different from each other with respect to the variable you are tying to predict. Figure 5.12 contains a set of data about five customers and their credit risk profile. We want to use the data in four of the fi ve columns to predict the risk rating in the fifth column. A decision tree can be constructed for this purpose. In decision tree analysis, Risk is in the ‘ dependent ’ column. This is also known as the target variable. The other four columns are independent columns. It is unlikely that the customer’s name is a predictor of Risk, so we will use the three other pieces of data as independent variables: debt, income and marital status. In the example, each of these is a simple categorical item, each of which only has two possible values (high or low; yes or no). The data from Figure 5.12 are represented in a different form in Figure 5.13 , in a way which lets you see which independent variable is best at predicting risk. As you examine the data, you will see that the best split is income (four instances highlighted in bold on the diagonal: two high income/good risk plus two low income/poor risk). Debt and marital status each s core three on their diagonals. Once a node is split, the same process is performed on each successive node, either until no further splits are possible or until you have reached a managerially useful model. The graphical output of this decision tree analysis is shown in Figure 5.14 . Each box is a node. Nodes are linked by branches. The top node is the root node. The data from the root node is split into two groups based on income. The right-hand, low income box, does not split any further because both low income customers are classified as poor credit risks. The left-hand, high-income box does split further, into married and not married customers. Neither of these split further because the one unmarried customer is a poor credit risk and the two remaining married customers are good credit risks. As a result of this process the company knows that customers who have the lowest credit risk will be high income and married. They will also note that debt, one of the variables inserted into the training model, did not perform well. It is not a predictor of creditworthiness. Decision trees that work with categorical data such as these are known as classification trees. When decision trees are applied to continuous data they are known as regression trees. Neural Networks (147): slide #9 Neural networks are another way of fitting a model to existing data for prediction purposes. The expression ‘ neural network ’ has its origins in the work of machine learning and artificial intelligence. Researchers in this field have tried to learn from the natural neural networks of living creatures. Neural networks can produce excellent predictions from large and complex datasets containing hundreds of interactive predictor variables, but the neural networks are neither easy to understand nor straightforward to use. Neural networks represent complex mathematical equations, with many summations, exponential functions and parameters. Like decision trees and clustering techniques, neural networks need to be trained to recognize patterns on sample datasets. Once trained, they can be used to predict customer behaviour from new data. They work well when there are many potential predictor variables, some of which are redundant. Case 5.2 Customer portfolio management at Tesco Tesco, the largest and most successful supermarket chain in the UK, has developed a CRM strategy that is the envy of many of its competitors. Principally a food retailer in a mature market that has grown little in the  last 20 years, Tesco realized that the only route to growth was taking market share from competitors. Consequently, the development of a CRM strategy was seen as imperative. In developing its CRM strategy, Tesco first analysed its customer base. It found that the top 100 customers were worth the same as the bottom 4000. It also found that the bottom 25 per cent of customers represented only 2 per cent of sales, and that the top 5 per cent of customers were responsible for 20 per cent of sales. The results of this analysis were used to segment Tesco’s customers and to develop its successful loyalty programmes. SWOT and PESTE (p. 154-5): slide# 10 SWOT is an acronym for strengths, weaknesses, opportunities and threats. SWOT analysis explores the internal environment (S and W) and the external environment (O and T) of a strategic business unit. The internal (SW) audit looks for strengths and weaknesses in the business functions of sales, marketing, manufacturing or operations, finance and people management. It then looks cross-functionally for strengths and weaknesses in, for example, cross-functional processes (such as new product development) and organizational culture. The external (OT) audit analyses the macro- and micro-environments in which the customer operates. The macro-environment includes a number of broad conditions that might impact on a company. These conditions are identified by a PESTE analysis. PESTE is an acronym for political, economic, social, technological and environmental conditions. An analysis would try to pick out major conditions that impact on a business, as illustrated below: political environment : demand for international air travel contracted as worldwide political stability was reduced after September 11, 2001 economic environment : demand for mortgages falls when the economy enters recession. social environment : as a population ages, demand for healthcare and residential homes increase technological environment : as more households become owners of computers, demand for Internet banking increases environmental conditions : as customers become  more concerned about environmental quality, demand for more energy efficient products increases. The micro environmental part of the external (OT) audit examines relationships between a company and its immediate external stakeholders: customers, suppliers, business partners and investors. A CRM-oriented SWOT analysis would be searching for customers or potential customers that emerge well from the analysis. Th ese would be customers that: 1. possess relevant strengths to exploit the opportunities open to them 2. are overcoming weaknesses by partnering with other organizations to take advantage of opportunities 3. are investing in turning around the company to exploit the opportunities 4. are responding to external threats in their current markets by exploiting their strengths for diversification. Five forces The five-forces analysis was developed by Michael Porter. 17 He claimed that the profitability of an industry, as measured by its return on capital employed relative to its cost of capital, was determined by five sources of competitive pressure. These five sources include three horizontal and two vertical conditions. The horizontal conditions are: competition within the established businesses in the market competition from potential new entrants competition from potential substitutes. The vertical conditions reflect supply and demand chain considerations: the bargaining power of buyers  the bargaining power of suppliers.  Porter’s basic premise is that competitors in an industry will be more profitable if these five conditions are benign. For example, if buyers are very powerful, they can demand high levels of service and low prices, thus negatively influencing the profitability of the supplier. However, if barriers to entry are high, say because of large capital requirements or dominance of the market by very powerful brands, then current players will be relatively immune from new entrants and enjoy the possibility of better profits. Why would a CRM-strategist be interested in a five-forces evaluation of customers? Fundamentally, a financially healthy customer offers better potential for a supplier than a customer in financial  distress. The analysis points to different CRM solutions: 1. Customers in a profitable industry are more likely to be stable for the near-term, and are better placed to invest in opportunities for the future. They therefore have stronger value potential. These are customers with whom a supplier would want to build an exclusive and well-protected relationship. 2. Customers in a stressed industry might be looking for reduced cost inputs from its suppliers, or for other ways that they can add value to their offer to their own customers. A CRM-oriented supplier would be trying to find ways to serve this customer more effectively, perhaps by stripping out elements of the value proposition that are not critical, or by adding elements that enable the customer to compete more strongly. Strategically Significant Customers (157) slide #11 The goal of this entire analytical process is to cluster customers into groups so that differentiated value propositions and relationship management strategies can be applied. One outcome will be the identification of customers that will be strategically significant for the company’s future. We call these strategically significant customers (SSCs). There are several classes of SSC, as follows: 1. High future lifetime value customers : these customers will contribute significantly to the company’s profitability in the future. 2. High volume customers : these customers might not generate much profit, but they are strategically significant because of their absorption of fixed costs, and the economies of scale they generate to keep unit costs low. 3. Benchmark customers : these are customers that other customers follow. For example, Nippon Conlux supplies the hardware and software for Coca Cola’s vending operation. While they might not make much margin from that rela tionship, it has allowed them to gain access to many other markets. ‘ If we are good enough for Coke, we are good enough for you ’ , is the implied promise. Some IT companies create ‘ reference sites ’ at some of their more demanding customers. 4. Inspirations : these are customers who bring about improvement in the supplier’s business. They may identify new applications for a product, product improvements, or opportunities for cost reductions. They may complain loudly and make unreasonable demands, but in doing so, force change for the better. 5. Door  openers : these are customers that allow the supplier to gain access to a new market. This may be done for no initial profit, but with a view to proving credentials for further expansion. This may be particularly important if crossing cultural boundaries, say between west and east. One company, a Scandinavian processor of timber, has identified five major customer groups that are strategically signi ficant, as in Figure 5.22 . The Seven Core Customer Management Strategies (158-9) slide # 12 This sort of analysis pays off when it helps companies develop and implement differentiated CRM strategies for clusters of customers in the portfolio. There are several core customer management strategies: 1. Protect the relationship : this makes sense when the customer is strategically significant and attractive to competitors. We discuss the creation of exit barriers in our review of customer retention strategies in Chapter 9. 2. Re-engineer the relationship : in this case, the customer is currently unprofitable or less profitable than desired. However, the customer could be converted to profit if costs were trimmed from the relationship. This might mean reducing or automating service levels, or servicing customers through lower cost channels. In the banking industry, transaction processing costs, as a multiple of online processing costs are as follows. If Internet transaction processing has a unit cost of 1, an in-bank teller transaction costs 120 units, an ATM transaction costs 40, telephone costs 30 and PC banking costs 20. In other words, it is 120 times more expensive to conduct an in-bank transaction than the identical online transaction. Cost-reduction programmes have motivated banks to migrate their customers, or at least some segments of customers, to other lower cost channels. An Australian electricity company has found that its average annual margin per customer is $60. It costs $13 to serve a c ustomer who pays by credit card, but only 64 cents to service a direct debit customer. Each customer moved to the lower cost channel therefore produces a transaction cost saving of more than $12, which increases the average customer value by 20 per cent. Re-engineering a relationship requires a clear understanding of the activities that create costs in the relationship (see Case 5.3). 3. Enhance the relationship : like  the strategy above, the goal is to migrate the customer up the value ladder. In this case it is done not by re-engineering the relationship, but by increasing your share of customer spend on the category, and by identifying up-selling and cross-selling opportunities. 4. Harvest the relationship : when your share of wallet is stable, and you do not want to invest more resources in customer development, you may feel that the customer has reached maximum value. Under these conditions you may wish to harvest, that is, optimize cash flow from the customer with a view to using the cash generated to develop other customers. This may be particularly appealing if the customer is in a declining market, has a high cost-to-serve or has a high propensity-to-switch to competitors. 5. End the relationship : sacking customers is ge nerally anathema to sales and marketing people. However, when the customer shows no sign of making a significant contribution in the future it may be the best option.You can read about strategies for sacking customers in Chapter 9. 6. Win back the customer : sometimes customers take some or all of their business to other suppliers. If they are not strategically signifi cant, it may make sense to let them go. However, when the customer is important, you may need to develop and implement win back strategies. The starting point must be to understand why they took their business away. 7. Start a relationship : you’ve identified a prospect as having potential strategic significance for the future. You need to develop an acquisition plan to recruit the customer onto the value ladder. You can read about customer acquisition strategies in Chapter 8.

Volunteering At A Food Pantry - 890 Words

Have you ever wondered where you would rest your head at night? Where you would find your next meal? How would support your family given unforeseen sudden circumstances? I’ve never thought about the importance of these questions until a recent experience I had volunteering at a food pantry. There are organizations whose main purpose is to help those in need and provide resources to members of the community who are going through difficult times. A food pantry is a non-profit community serviced organization that provides members of the community with groceries and resources. From volunteering at this food pantry I learned more than ever to never â€Å"judge a book, by its cover†, or in other words, even though I person may look well put together on the outside, you never know what it is they are dealing with on the inside. I’ve encountered homeless members of the community, people who have suffered from physical abuse, and people who have experienced unexpected dis asters such as house fires to expected job layoffs while volunteering at a food pantry. I’ve also come to appreciate everything that I have in my life from the roof over my head to the food in my stomach and that some people are less fortunate than me. Recently I was given the opportunity to volunteer at the grand opening of a food pantry ran buy a local church. I was first approached with this opportunity by a family member, I wasn’t quite sure what exactly what a food pantry was and what it took to operate it. IShow MoreRelatedEssay about Persuasive Speech: The Benefits of Volunteering1127 Words   |  5 PagesStatement: Volunteering in your local community will help those around you and help you feel like you have contributed something positive and it is easier than most people think. C. 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