steps to implement crm

8/11/2019 Steps to Implement CRM

1/16

Steps to implement CRM

Step 1: The identification of customers

The identification of customers enables the organisations to select those customers that they regard as

being strategically significant and who they believe can contribute to the success of the organisation.

These

customers have unique needs and due to their value to the organisation, will have products developed

to meet

these needs. It must be possible to identify these customers and so obtain as much detail as possible.

This

involves collecting as much data as possible in order to obtain as clear a picture as possible of the

customer and

their profile. This may require the development of a database or the continued maintenance of a

database in

order to ensure that the data stays as recent as possible. Having this information enables the

organisation to

determine those customers that have been with the organisation for a long period and those that have

recently

started using the products and services of the organisation.

The hypothesis regarding this aspect is formulated as follows:

H1: Identifying new and existing clients increases the level of customer service.

Step 2: The differentiation of service

The differentiation of service implies that different customers receive a different level of service and a

different product from the organisation, depending on the value to the organisation and their specific

needs.

This requires the organisation to identify the top (or most significant) customers and adapt serviceaccordingly.

Identification of these top customers takes place using sales figures or by calculating the CLV associated

with

each customer. As the organisation is aware of the value of their customers, service levels can be

adjusted


2/16

accordingly.


H2: Differentiating between the services offered to new and existing clients increases the level of

customer service.

Step 3: Interaction with customers

This step refers to the importance of interacting with the customer in relationship building efforts

through a variety of communication tools and technologies. This is necessary as the relationship can

only

develop and be sustained if there is communication with the customers regarding their needs,

perceptions and

desires. This involves developing methods of communication proactively with customers regarding the

organisationsproducts and attempting to initiate dialogue with customers. Use can be made of

technology, but

this is not essential (Brunjes & Roderick, 2002). The customers with whom communication takes place

are not

necessarily all the customers, but only those that the organisation regards as being strategically

significant.

This interaction with the organisation increases the expectations of the customers regarding the service

received as well as the quality of the relationship.


H3: The level of customer service is increased if there is an active interaction with potential and

existing clients. IMPLEMENTING A CUSTOMER RELATIONSHIP

Journal of Global Business and Technology, Volume 1, Number 2, Fall 2005 85

Step 4: Customisation of products, services and communication

Customisation is carried out by the organisation in order to ensure that customer needs are met. It

requires that the organisation adapts its product, service or communication in such as way have

something


3/16

unique for each customer. Communication can be customised to address the specific needs and profile

the

customer, and organisation also makes use of personalisation as part of this process. Products can be

customised as to the specific desires that the customer has of the organisation. In the case of the

financial

services, it refers to the product package that is offered to the customer. The purpose of customisation

is to Increase customer satisfaction, and the loyalty that is exhibited by customers.

Assessment for Loyalty Programs

SUMMARY:Loyalty programs offer repeat-purchase benefits to customers andbecome especially important during a tight economy. But theyre often viewedfrom the marketers perception and leave the customer out.

Weve put together a six-point checklist to help you assess your loyalty program,

plus tips on how to put consumers first.

Connecting with consumers isnt always easy. Many marketers use loyalty programs to deliver benefits

and value. Still, whether the card or club targets consumers or B-to-B customers, marketers must

understand the key drivers.

What makes a customer feel that a loyalty program is worth joining? What makes a customer loyal?

Start here: Customers wont participate in a program that doesnt offer sufficient value.

Loyalty programs are extremely important: A retail loyalty program study done by Carlson Marketing

in 2007 showed that 63% of customers are more likely to use a particular firms products and services

more frequently.

Here are six steps to help you assess the value of your loyalty program from a customers

perspective.

-> Step #1. Research your customer base

Emotionless as raw data is, it can reveal some truths and trends about a customers buying behavior

and inpiration. This requires effective database analysis and segmentation.

But companies often fail to ask their customers enough questions. Even a range of traditional

marketing research tools -- like focus groups, short online polls and surveys -- fail. What customers

say and do often dont correlate.

-> Step #2. Capture qualitative data

Examine your customers actual behavior to determine relevancy and value. Loyalty is not just

transactional. Captured data must go beyond an analysis of sales figures. The emotional triggers that

lead to a particular buying decision are just as important as the hard statistics.


4/16

For instance, you should know how a customer perceives your loyalty program from inception to the

end of its lifetime and how a customer interacts with your brand. Knowing the treatment and

experience customers have when engaging with the companys employees, partners, products and

services is vital.

Supported by quantitative data, its possible to find the overlap between what a customer says anddoes. You need to know each customer as an individual. Some customers may have higher

expectations than others, such as frequent-flier programs.

- Higher-value customers, for example, wont necessarily want to receive discounts like those typically

offered in retail outlets at the point of sale.

- B-to-B customers might want to be offered something of value to their company.

Marketers need to become each customers best friend and capture personal data that reveals more

about each individual.

-> Step #3. Maintain ongoing dialogues

Its not possible to know anyone well without having some form of continual dialogue with them.

Encourage your customers to interact with you frequently. They might prefer to speak with a rep in a

contact center, or communicate with you via the Web, or through a brick-and-mortar outlet.

Each interaction presents an opportunity to gain more information about them, to find out about their

lifestyles and what they value. It helps you to personalize the communication process. Indeed, the

ideal discussion should feel like a one-to-one dialogue.

Some companies make the mistake of using customer data aggressively.

- Loyalty programs should pull customers toward the brand by adding perceived value.

- A push model will often put customers off; they will tell you to go away and perhaps leave for a

competitor.

Give customers more control over the preferences, frequency, timeliness and means of dialogue.

-> Step #4. Make program simple

Loyalty programs need to be easy to join and understand. They should be accessible across all the

relevant touch points with customers.

The programs should encourage consumers to join and remain loyal to that program only -- not

several at a time.

Too many organizations require the customer to provide all of the input upfront, and the customer

does not see any value-add, says Patrick McHugh, Executive VP, Email Marketing and Loyalty

Specialist, Neolane. Marketers view loyalty cards as a way to get to know the customer better, but

they need to use it for the benefit of the customer as well as for that of the business.

Make it easy for everyone to redeem rewards as well and offer alternative rewards available if you run

out of promoted ones. Otherwise, customers might become disgruntled rather than loyal.

-> Step #5. Reward (but not too much)


5/16


6/16

In every buying decision, a consumer asks the same question: is what I am going to receive worth what

I have to give up in order to get it? The gain the consumer receives for the benefit is weighed against

the cost the consumer must pay to acquire the benefit. The value the individual consumer places on a

product or service becomes the customer value for that offering.

This customer value is weighed against

the customer values assigned for similar

products and services that provide a

similar benefit. Consumers will typically purchase the item with the highest customer value among all

offerings in the marketplace. When you are deciding where to go to lunch for example, do you consider

Subway to have a higher customer value than Burger King?

Every consumer has a unique set of needs and resources, so no two consumers will place the same

customer value on the same product or service. The highest-quality product or service does not always

provide the highest customer value, since the benefit of each item is measured against the cost. Someconsumers are willing to pay a high price for a quality product or a high level of service, but others will

make the decision that the same benefits 'are not worth the price'.

On your next vacation, would you rather stay at the Marriott or the Quality Inn? The Marriott will provide

you with a nicer room, a fancier lobby, and room service, but you might rather spend the money you

save by staying at the Quality Inn on souvenirs.

Customer Life time Value

In marketing, customer lifetime value (CLV) (or often CLTV), lifetime customer value (LCV), or userlifetime value (LTV) is a prediction of the net profit attributed to the entire future relationship with a

customer. The prediction model can have varying levels of sophistication and accuracy, ranging from a

crude heuristic to the use of complex predictive analytics techniques.

Customer lifetime value (CLV) can also be defined as the dollar value of a customer relationship, based

on the present value of the projected future cash flows from the customer relationship. Customer

lifetime value is an important concept in that it encourages firms to shift their focus from quarterly

profits to the long-term health of their customer relationships. Customer lifetime value is an important

number because it represents an upper limit on spending to acquire new customers.[1] For this reason it

is an important element in calculating payback of advertising spent in marketing mix modeling.


7/16

Dimensions to CLV

Customer Lifetime Value in Three DimensionsPosted byLothar Krauseon 06/12/2013

Tags:big datacustomer lifetime valuedigital marketingprogrammatic displaytutorial

Series: How Smarter Attribution Leads to Smarter eCommerce Marketing

This post is the eighth in a series about smarter attribution marketing.Need to catch up? Check

out the previous entries in the series:

1.All Attribution Models are Not Created Equal

2.Last-Click AttributionLast Click, Last Choice?

3.Beyond Last-Click AttributionThe Customer Journey to Conversion Model

4.Turning Your Attribution Model into Online Marketing Optimization

5.Taking Attribution to the Next Level: Customer Lifetime Value
https://www.sociomantic.com/search/author/lothar/https://www.sociomantic.com/search/author/lothar/https://www.sociomantic.com/search/author/lothar/https://www.sociomantic.com/search/tag/big-data/https://www.sociomantic.com/search/tag/big-data/https://www.sociomantic.com/search/tag/digital-marketing/https://www.sociomantic.com/search/tag/tutorial/https://www.sociomantic.com/search/tag/tutorial/https://www.sociomantic.com/blog/2013/06/all-attribution-models-are-not-created-equal/#.Uo8ybWRDtVshttps://www.sociomantic.com/blog/2013/06/all-attribution-models-are-not-created-equal/#.Uo8ybWRDtVshttps://www.sociomantic.com/blog/2013/06/all-attribution-models-are-not-created-equal/#.Uo8ybWRDtVshttps://www.sociomantic.com/blog/2013/08/last-click-attribution-last-click-last-choice/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/08/last-click-attribution-last-click-last-choice/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/08/last-click-attribution-last-click-last-choice/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/08/last-click-attribution-last-click-last-choice/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/08/last-click-attribution-last-click-last-choice/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/10/beyond-last-click-attribution-the-customer-journey-to-conversion-model/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/10/beyond-last-click-attribution-the-customer-journey-to-conversion-model/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/10/beyond-last-click-attribution-the-customer-journey-to-conversion-model/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/10/beyond-last-click-attribution-the-customer-journey-to-conversion-model/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/10/beyond-last-click-attribution-the-customer-journey-to-conversion-model/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/11/turning-your-attribution-model-into-online-marketing-optimization/#.Uo8yO2RDtVshttps://www.sociomantic.com/blog/2013/11/turning-your-attribution-model-into-online-marketing-optimization/#.Uo8yO2RDtVshttps://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.Uo80QmRDtVshttps://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.Uo80QmRDtVshttps://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.Uo80QmRDtVshttps://www.sociomantic.com/blog/2013/11/turning-your-attribution-model-into-online-marketing-optimization/#.Uo8yO2RDtVshttps://www.sociomantic.com/blog/2013/10/beyond-last-click-attribution-the-customer-journey-to-conversion-model/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/08/last-click-attribution-last-click-last-choice/#.Uo8yOmRDtVshttps://www.sociomantic.com/blog/2013/06/all-attribution-models-are-not-created-equal/#.Uo8ybWRDtVshttps://www.sociomantic.com/search/tag/tutorial/https://www.sociomantic.com/search/tag/digital-marketing/https://www.sociomantic.com/search/tag/digital-marketing/https://www.sociomantic.com/search/tag/big-data/https://www.sociomantic.com/search/tag/big-data/https://www.sociomantic.com/search/author/lothar/


8/16

6.Supporting Your Attribution Strategy with Real-Time Programmatic Display

7.Is View-Through Attribution a Good Look for Online Marketers?

Going Deeper on the CLV

In postnumber fivein the series, we introduced why marketers should concentrate on long

term optimization based on the customer lifetime value (CLV) of their users instead of a pure

cost-per-order (CPO) optimization calculated for each single purchase. We talked about how

concentrating investment on new customers can help to achieve sustainable growth for your

customer base. But even with this differentiation, questions remain. Who are the right

customers (in terms of long-term value), and how should I treat my existing customers?

The goal of this article is to give you some additional insights not only on why, but also how to

calculate the CLV. The basic idea behind CLV calculation is to understand the total value in

terms of either sales or (in the best case scenario) margin that a customer creates within a given

time frame. If you look more closely at the subject, a customers purchases can be broken down

into three dimensions:

RRecency

FFrequency

MMonetization

Purchase Recency:

For recency, you must be able to calculate how recently a customer has completed a purchase.

When examining the recency dimensions of your customers, you can gain additional insights by

analyzing the customer groups that purchased certain items to understand which items are most

likely the next purchase, and to discover the average time until the next purchase for given

products or categories. This kind of analysis is typically the backbone of product

recommendation engines or post-purchase retargeting engines.

Pur chase Frequency:

Frequency, like recency, it a matter of timein this case a measure of how often a user is

completing a purchase on the website. Even as a stand-alone data point on a per-user basis,
https://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.Uo8yM2RDtVshttps://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.Uo8yM2RDtVshttps://www.sociomantic.com/blog/2013/11/is-view-through-attribution-a-good-look-for-online-marketers/https://www.sociomantic.com/blog/2013/11/is-view-through-attribution-a-good-look-for-online-marketers/https://www.sociomantic.com/blog/2013/11/is-view-through-attribution-a-good-look-for-online-marketers/https://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.UwsS-FtdXJ6https://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.UwsS-FtdXJ6https://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.UwsS-FtdXJ6https://www.sociomantic.com/blog/2013/11/taking-attribution-to-the-next-level-customer-lifetime-value/#.UwsS-FtdXJ6https://www.sociomantic.com/blog/2013/11/is-view-through-attribution-a-good-look-for-online-marketers/https://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.Uo8yM2RDtVs


9/16

purchase frequency can be a very useful dimension when deciding a customers potential value

(higher frequency = higher potential value for a given time period). It becomes even more

valuable if you begin to analyze aggregated user data, using cluster analysis to identify trends

and understand which shopping behaviors indicate which CLV. For example, as an online winereseller, your frequency analysis might reveal that buyers of red wine buy more often and more

consistently than their white-wine-buying counterparts. (This examplewas discussed by Florian

Heinemann of Project A Ventures in our dmexco seminar this year.)

Monetization:

The third (and trickiest) dimension of the three is monetization, a hard measure of how much

value a user has generatedbut it goes beyond pure revenues. Monetization means taking into

account the actual margin generated from the products purchased (not every product generates

the same margin), as well as taking product returns into account. Especially for shops with a high

return rate, the CLV per customer (and likewise the CRM group) can change dramatically once

returns are taken into account.

From a tracking and analytics standpoint, monetization is the toughest dimension to measure.

While recency and frequency can be evaluated with an advanced web tracking solution,

measuring monetization requires much bigger data muscles, because the data warehouse where

the data is stored has to be able to intelligently communicate with the business intelligence (BI)

mechanisms. Dont forget that, depending on the policy of the shop, returns can happen quite a

while after the original purchaseto properly measure monetization, you need to be able to

hold onto all that data in a usable way!

Advancing Your CLV Strategy

It sure sounds like a lot of work, but if youre looking to sharpen your strategy, switching from a

last-click to a customer journey attribution model as a first step will already dramatically impact

how you distribute your marketing spends per channel. If you take it one step further to start

working around not the single-transaction CPO but the potential CLV of your customers, the

implications for long-term value creation are tremendous. You could break the CLV strategy

down to three levels of refinement:
https://www.sociomantic.com/blog/2013/09/dmexco-2013-in-review/https://www.sociomantic.com/blog/2013/09/dmexco-2013-in-review/https://www.sociomantic.com/blog/2013/09/dmexco-2013-in-review/https://www.sociomantic.com/blog/2013/09/dmexco-2013-in-review/


10/16

1. Splitting between new and existing customers,

2. Splitting based on the CLV of existing customers (CRM groups),

3. Predicting the CLV of new customers based on analysis of historical data of existing

customers.

For the third point, advanced marketers with strong BI teams can analyze historical data from

existing customers (usually in windows of 30-60 days) to find clusters of behaviors that indicate

a certain CLV. In this way, marketers can predict the CLV of new customers either from the

users shopping behavior or by the channel(s) through which the user reached the site both

dimensions can be a key indication of potential value. Depending on your product range, the

category of the first-time-purchased product could also be a strong indicator of CLV.

Beyond the division between new and existing customers, many online shops are also starting to

put more strategy into reactivation of existing customers. For example, a given shopping

behavior may indicate that the next buy is probably on the horizon within a certain time frame

lets say buying a laptop might mean youre likely to buy a hard drive in 60 days. If the user

(especially a frequent buyer, or taking seasonality into account) does not purchase within the

expected time frame, it could make sense for the marketer to increase the CPO target for the push

channels (such as display advertising or email) to convince the shopper to purchase again. This

reactivation methodology of course works best with channels in which the marketer can make

adjustments at a user level, such asprogrammatic display.

Whats Next in the Life of the CLV?

In time, we may seeand expect to seethat marketers will no longer have CRM groups,

but rather that each individual user will comprise his very own dynamically changing CRM

group, with a constantly changing CLV and strategy assigned to him, based on the indications of

his shopping or browsing behaviors.

In the wonderful world of programmatic display, we can already see the benefits of reaching

users on different devices with the CLV approach, which can help the marketer to adjust

spendings, reach the user at the right time and track the entire customer journey across channels

and devices. Youll find more on that topic in our next post in the series!
https://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.UqGuLGRDtVthttps://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.UqGuLGRDtVthttps://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.UqGuLGRDtVthttps://www.sociomantic.com/blog/2013/11/supporting-your-attribution-strategy-with-real-time-programmatic-display/#.UqGuLGRDtVt


11/16


12/16

2. 2

Determine the average first purchase amount by each new customer.

Make a list of first purchase totals. Look through your records to gather data for this list.

Sum the figures on the first purchase list, and divide by the total number of purchases on the

list.

3. 3

Discover the number of times most customers make purchases within a set time

frame.For example, a retail business that sells household necessities may wish to use the

timeframe of 1 year. However, a business that has a more specialized market, such as

appliance sales, may benefit by using a longer timeframe. The timeframe should represent a

reasonable length of time that a typical customer could be expected to make more than 1

purchase.

4. 4

Establish an average transaction amount for follow-up transactions by using a list of

customer transactions.The average transaction amount puts your customer's buying potential

into perspective.


13/16

5. 5

Discover the total amount a customer has spent with your business. Add together all

purchases of a particular customer during the lifetime of your relationship with her.

6. 6

Determine the profit on a customer's lifetime purchases based on your typical profit

margin.If your profit margin is 25 percent and a customer's lifetime purchases add up to $500,

the profit you received from his purchases is $125.

7.

7

Subtract the customer acquisition cost from the profit of a customer's lifetime purchases

to determine the customer lifetime value.

8. 8Use your best estimates for the requested data if documented information is

unavailable.Not all record-keeping systems supply detailed data. However, consider


14/16

implementing a record-keeping system that is capable of keeping track of more data if you wish

to determine customer lifetime value and other marketing calculations in the future for your

business.

Recency Frequency Monetary Value Model

Recency Frequency Monetary Modeling (RFM)

RFM analysis is a technique used to group or segment existing customers based on historic behavior in

the hopes that history can, with the right motivators, be caused to repeat or even improve upon its self.

The acronym is short for Recency, Frequency and Monetary value and each of these measures aligns to

one or more of the three methods of increasing revenue for a business.

RFM is an effective process for marketing to your loyal customers and uses purchase behavior by

recency, frequency and monetary to determine what offers work for what type of customers. Generally,

only small percentages of customers respond to typical offers. But with RFM, you can ensure you are

targeting the right set of customers who are most likely to respond. RFM is a powerful segmentation

method for predicting customer response and ensures improvement in response as well as profits.

It is used primarily for targeted campaigning, customer acquisition, cross-sell, up-sell, retention, etc and

is a guarantor of campaign effectiveness and optimization.

One of the most commonly used forms of segmentation is RFM (recency, frequency and monetary

value). RFM is a good way to define and understand customer value. As well as helping customer

development it can also form the basis of a good customer retention strategy.

Defining the Terms of RFM

Just what are recency, frequency, and monetary measures? The concepts are simple, even

intuitive but turning them into measures that you can use to produce RFM scores can be somewhat

tricky.

Keep in mind that the measures you use to rank your list are not the same numbers as the 5-4-3-2-1

score that you assign to each customer. For recency, youll figure out how long its been since each

customer interacted, in days, weeks, or months. You then use those time-based measures to rank your

list in order, from most recent to the long-lapsed. The recency score comes from that ranked list, with

the 20 percent who gave most recently assigned a score of 5.For frequency, the measure is number of

interactions in a given period. For monetary, the measure is total transaction value.

-Recency


15/16

When did the customer last place an order, visit our store or interact with us in a material way? A

customer who recently had a favorable interaction with our firm is, we hope, predisposed to repeating

that interaction and thus susceptible to an offer that would encourage future business. Similarly a

customer who hasnt done business with us for sometime may be open to an offer of resumption that

draws them back.

-Frequency

How many interactions, over a period of time, has the customer had with us? Assuming the interactions

have been favorable for both parties, we would hope that we can sustain or increase the frequency of

the interactions to our advantage. As with a customer who has not done business with us recently,

frequency of interaction is a trigger you will want to pay attention to when it falls off over a period of

time. This is where the frequency measure is often correlated to the recency one.

-Monetary

Over a given period of time, or number of interactions, what is the value of the customers businesseither in terms of revenue or profitability? Grouped in with monetary analysis is often inventory and

channel analysis to get a sense of customers whose purchases reflect higher margin activities for the

business such as buying large volumes through automated channels or the purchase of inventory items

that have higher margins, are slow moving in various periods or are ends or remnants of other jobs.

Why does my business need RFM?

RFM will be of benefit to your business in any number of ways. If your business is wasting money

speaking to customers who are of little worth to you, or may have even ceased being a customer, then

RFM segmentation can help. The Recency segment tells you which customers have ceased trading with

you, and the monetary segments tell you who your real big hitters are. Lets suppose that your

marketing budget is slashed next year by half. Who are you going to spend that money on talking to?

RFM allows you to segment your customer base in a way that empowers your business to spend that

budget in the right way, on the right customers. Single purchasers make up a large portion of most

customer bases. Businesses buy from you, and then you never see them again. If you are trying to

identify and get these businesses to repeat purchase, then RFM segmentation is for you. Regular RFM

reporting will give you visibility on who your newest customers are. You can then market to them to try

and get that repeat purchase.

Some examples:

i) Catalog and direct-mail marketers were early adopters of RFM techniques to determine which

customers got which catalogs, how often and with what special incentives, coupons or savings. With the

advent of high capacity colour digital presses, many companies now custom print each catalog, varying

the items on pages, prices for items and even specialized promotional offers for each customer based on

the findings of RFM analysis.


16/16

ii) RFM analysis forms the basis of every customer loyalty program in operation from frequent flyer or

hotel guest programs to retail shopper reward cards.

iii) If youve ever been to a casino youve seen RFM analysis combined with life-time value analysis.

These are the principles upon which casinos issues complementary hotel rooms, meals, show tickets and

everything else they offer for free to patrons of their establishments. Even the so called free drinksyou can get in a casino are carefully distributed based on a real time size-up of your value to the casino

based on RFM analysis.

steps to implement crm

Documents