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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
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accordingly.
The hypothesis regarding this aspect is formulated as follows:
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.
The hypothesis regarding this aspect is formulated as follows:
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
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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.
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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)
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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.
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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
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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,
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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:
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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!
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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.
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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
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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
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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.
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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.