Presentation on theme: "RFM Analysis Collaboration Excercise Chapter 9 (page. 366) MGS 3040-03 Group F Maria Del Moral, Marcela Lascano Brian Varela, Nayon Powlett."— Presentation transcript:
RFM Analysis Collaboration Excercise Chapter 9 (page. 366) MGS 3040-03 Group F Maria Del Moral, Marcela Lascano Brian Varela, Nayon Powlett
How RFM analysis works? It is used to analyze and rank customers according to their purchasing patterns. It is a marketing technique used to determine quantitatively which customers are the best. RFM considers: -How recently (R) a customer has ordered. -How frequently (F) a customer has ordered. -How much money (M) the customer has expent.
How RFM analysis works? RFM first sorts customer purchase records by date of their most recent (R) purchase. Then divides customers into 5 groups & gives them in each group a score of 1 to 5. The hightest score would be 1 & lowest 5. The 20 % of the customers having the most recent orders & order most frequently & ordered the most expensive items would have a score R =1, F=1, M=1.
Innovating RFM Analysis (pag.351). It could be applyed to different scenarios: -How recently (R) a customer has ordered. -How frequently (F) a customer has ordered. -How much money (M) the customer has expent. ( A company compute value (D) number of days that expire between invoice & arrival payment) -Value (P) who pay fastest. Customers would be given four-value score based on RFMP A customer having [1,1,1,1] is indeed valuable customer. It could be used to rank suppliers, inventory parts, employees, airlines, hotels, etc.
Effectiveness & Strengths -RFM is a database marketing technique that can be used in any industry to support marketing and sales decisions for developing marketing and sales strategies and tactics. -RFM tool is used for analyzing customer behavior and identifying customer groups with similar behaviors. -RFM segments behave differently on different marketing approaches such as promotions and advertising so RFM helps marketing managers develop customized marketing strategies for different RFM segments. -RFM also helps with identifying who are the best / most profitable customers and who are the customers who are more likely to respond to a certain marketing strategy. -RFM Analysis is a simple quantitative approach and gives marketing managers business insight into their customer base.
Effectiveness of an RFMP analysis (C.) An RFMP analysis consists of all the components of an RFM analysis but suggests adding a "P" criterion. The P criterion is to sort out which customers pay the quickest from the day of the invoice. It is an effective tool in the sense that it helps businesses determine how quick they will be reimbursed for their product/services. - In many cases, businesses can judge whether or not they can afford sell to these customers.
Examples: [1, 1, 1, 5] [3, 3, 3, 1] [5, 5, 5, 1] (C.) Now that we know how an RFMP analysis works: - what action can be taken with a [1, 1, 1, 5] customer? - what action can be taken with a [3, 3, 3, 1] customer? - what action can be taken with a [5, 5, 5, 1] customer?
[1, 1, 1, 5] customer (C.) From the numbers above we know that they: 1. Are recent shoppers  2. Are frequent shoppers  3. Buy the most expensive items  4. Take very long to pay  What needs to be improved? Obviously it is P Possible solutions - They can set up some type of automatic withdrawal from the customers account; They can make the customer pay at time of purchase; If the business has weak financial support, they may have to decline products/services to this customer.
[3, 3, 3, 1] customer (C.) From the numbers above we know that they: 1. Not a recent shopper but does shop from time to time 2. Does not shop frequently but does seem to use them 3. Does not buy the most expensive goods nor the cheapest 4. They are a fast payer They are an "ok" customer. Possible solutions: Perhaps there can be some type of automated system to take their orders; The company can make arrangements to automatically send them the same supplies, items, etc every 3 months
[5, 5, 5, 1] Customer (C.) From the numbers above we know that they: 1. Haven't ordered in awhile 2. Rarely order if they still order at all 3. Purchase cheap items/services 4. Fast payers This customer has very little effect over the business, let them go to the competition. The loss will be minimal and not worth the effort.
Under what circumstances, if any, is RFMP preferred over RFM? (C.) RFMP only has 1 extra component: - How fast does the customer pay (P) Therefore, RFMP should be preferred in any type of business where transactions occur. RFM may be preferred in anything that does not involve account receivables in the transaction.
RFM Analysis: Rank suppliers (D.) The RFM analysis can be tweaked to rank suppliers: - R: How recently you used them? - F: How frequently you deal with them? - M: Do you buy their most expensive supplies? The results can be used to identify what opportunities you have to negotiate better pricing, faster delivery or perhaps if it would be in your benefit to establish credit with them. This will give you some sort of idea of whether or not you are a priority client and how you can use that to your advantage.
Devise a version of the RFM analysis to rank sales-people. What critera would you use to rank them ?
Describe what you think is the proper domain for RFM ranking systems? (G.) Such proper domains for RFM ranking systems are such websites like ebay.com, amazon.com, renditionx.com, and many others The Recency, Frequency, Monetary value (RFM) model works everywhere, in virtually every high activity business RFM works for just about any kind of "action-oriented" behavior. Businesses are trying to get a customer to repeat, whether it’s purchases, visits, sign-ups, surveys, games or anything else.
What kinds of problems or data are best suited for this type of analysis? (G.) To do RFM analysis, history data is the best suited for this type of analysis. In each customer record you must maintain three pieces of information such as the most recent date, frequency, and monetary amount. By using these three pieces of data will construct RFM codes. a) the most recent date that the customer has requested a change in his service, purchased a discretionary item, etc. b) a counter for the frequency – the number of times he has made a purchase, or continued his service with you. For a telephone company, for example, it might be the number of months of continuous service; for a retail store, it would be the total number of store visits. This counter is incremented by one every time a purchase is made. c) a counter for the monetary amount – the total dollar amount the customer has purchased from you since the beginning of time.
What kinds of problems or data worst suited for this type of analysis? (G.) - Most RFM implementations are linear. Any linear method involves a constant "trade-off" between variables. Linear models have poor scores discrimination for the large majority of customers because of these tradeoffs. - RFM typically ignores product data, and has no way to examine purchase patterns - Determining the recency data can also be a problem with RFM. -Another problem that can be seen from the analysis, RFM only works with a customer database. Only with customer databases that contain the necessary data. It is of no use with a prospect database.