Database Reference
In-Depth Information
Customized Relationship Marketing recommends that companies identify their most valuable
customers (MVCs) and then have a close relationship with them. Many companies may use ABC
analysis (e.g., identify the top 20% of customers who account for 80% of sales) to identify their
MVCs. However, this maybe a misguided effort because, this being a lag measure, this would
lead to concentration of efforts on customers, who although are currently contributing to the
profitability of the company may not necessarily have a long-term profit potential. The best way of
assessing the long-term profit potential of customers is through their Lifetime Value (LTV), which
we discuss in Section 1.2.7.2 “Customer Lifetime Value.”
While most companies measure some form of customer satisfaction, that measure does not
determine customer loyalty: reasonably satisfied customers often defect to the competition.
Customer loyalty is different from customer satisfaction per se. For instance, higher levels of cus-
tomer satisfaction do not necessarily translate into repeat purchases and, therefore, increased sales
and profits. A related problem is that even enterprises such as department stores, which are critically
dependent on access to data on
loyalty schemes
, may possibly be using only about 2% of the data to
which they have access to. One of the primary reasons for this is the sheer volume of data that is
being captured inside these organizations. For instance, a regular shopper may buy 50-100 items
during a monthly visit. Many of these stores have 10-20 checkout points operating at any moment
in time. These can process on an average about 12 customers an hour for 10 h a day. So, each and
every day, they are open, and they are gathering between 60,000 and 240,000 data points per store.
Even for a midsized supermarket chain with about 200 stores, working 7 days a week, this would
result in something like 65-340 million data points per working week!
Table 1.5 compares the traditional customer satisfaction-oriented approach with that of the
value orientation of relationship marketing.
Customer loyalty is characterized by repeat purchases and a willingness to continue the rela-
tionship. Loyal customers
◾
Stay longer
◾
Cost less to service
◾
Buy more
◾
Provide higher margins
◾
Purchase across product lines
◾
Demonstrate immunity to the lure of competition
◾
Demonstrate less price sensitivity
There are various ways to represent progress up the ladder of customer loyalty. Customer Pyramid
is one such approach that assists in planning for enhanced relationship with the company's pros-
pects and customers and is also helpful in visualizing the progress toward higher-value relation-
ships. Figure 1.7
presents the Customer Pyramid consisting of the following:
1.
Top
that are the top 1% revenue customers
2.
Big
that are the next 4% revenue customers
3.
Medium
that are the next 15% revenue customers
4.
Small
that are the next 70% revenue customers
5.
Inactive
that are the remaining 10% revenue customers
