Ashman, Sara M.

English

Research Papers in Economics

Grocery Store Buying Behavior:
Evidence From Loyalty Program Data
Sara M. Ashman
Card-based customer loyalty programs are de-
signed to track individual- and/or household-level
shopping behavior at the point of sale (POS). As
illustrated in Figure 1, card-based customer loyalty
programs use shopper identification cards (or cus-
tomer loyalty cards) to track consumer purchases
aud behaviors. Consamers receive a card from the
retailer with a unique number or bar code that can be
entered or scanned at the POS. To encourage use of
the card on every shopping trip, consumers are of-
fered rewards in the form of price discounts, promo-
tional programs, charity donations, etc. In additio~
when customers use their card at the POS, the re-
tailer is able to collect a vast amount of data on the
cardholder’s shopping behaviors. Through the
analysis of the&@ the retailer can silently observe
customer purchase behavior and track changes in
behavior over time, allowing the ret@lerto fkrther
reward their customers and to alter the products and
servicesthey oflkr to match customerdemand.
Adoption
The grocery store industry appears to be
adopting the use of customer loyalty programs.
According to Supermarket News, approximately
50 percent of retailers have launched a customer
loyalty program (Blair, 1999). Of the retailers
using the program, 60 percent feel it is successful
(Blair, 1999). The success of the program maybe
attributed to the characteristics of customer loy-
alty cardholders. According to the Food Mar-
keting Institute’s (FMI) 1997 “Electronic Mar-
keting Survey of Food Retailers,” consumers
who use their customer loyalty card when they
shop: (1) have higher average transaction sizes
overall; (2) have lower defection rates; (3) con-
tribute more to gross margin; (4) shop more of-
ten; and (5) spend more per week than customers
who do not use their customer loyalty card when
they shop (FMI, 1997).
Shopper Identification/
Customer Loyalty Cards
_.’--- —
/’ ‘“””Customer Re / Ier Collec;s%’’’%>”t,
\
\ Rewards )
‘+%.,
‘\___ _ _-~~”’”””
Figure 1. Customer Loyalty Programs, Card-Based.
Sara M. Ashman is a Ph.D. candidate, Department of Ap-
plied Economics, University of Minnesota.2 March 2000 Journal of Food Distribution Research
Consumers are also adopting the use of cus-
tomer loyalty cards at an aggressive rate. Ac-
cording to ACNielsen’s third annual frequent
shopper survey, 66 percent of U.S. households
participate in at least one supermarket customer
loyalty program, and 82 percent of these custom-
ers use their card every time they shop (ACNiel-
sen, 1999). The rate of consumer participation in
customer loyalty programs has been increasing
since its beginnings in the mid- 1990s (Figure 2).
From 1996 to 1997, consumer participation in-
creased 57 percent. From 1997 to 1999, participa-
tion increased an additional 20 percent.
Rewarding the Customer
The rewards that customers gain by using their
customer loyalty cards are the key driver in en-
couraging card use. According to the Retail Food
Industry Center’s (RFIC) “1999 Supermarket
Panel,” in the 100 retail stores participating in the
customer loyalty sectio~ reduced prices are the
most common form of reward across the indus~
(Figure 3). The retailer rewards the consumer by
offkring discounted prices on selected items
throughout the store. Consumers who purchase the
selected items will receive the discounted prices
when their loyalty card is scanned at the POS.
Sweepstake drawings are the second most
common form of reward. When customers use
their customer loyalty card at the POS, they are
electronically entered for the sweepstakes draw-
ing. If the sweepstakes promotion is co-sponsored
with a manufacturer, the consumer can be entered
an additional time when they purchase particular
products or brands. At the end of the promotional
period, winners are electronically drawn from the
quali&ing entries.
The third most common form of rewarding
consumers is through a non-tiered continuity
program. Typically, non-tiered continuity pro-
grams require consumers to spend a fixed dollar
amount over several weeks. If the consumer
reaches the spending threshold s/he receives a
free Thanksgiving turkey or Easter ham, for ex-
ample. A tiered continuity program would have
more than one quali&ing threshold level and
varying levels of rewards based on the threshold
reached. Less common forms of reward include
charity donations, front-end coupons, and news-
letters.
Collecting the Data
The range of data being collected by retailers
is immense. The data currently being collected
can be organized into the following two groups:
(1) demographic da@ or data that is given by the
customer, and (2) shopping trip daa or data gen-
erated at the POS.
w%
60%
NY%,
20%)
w,
1996 1997 1998
Figure 2. Supermarket Customer Loyalty Program Participation.
Source: ACNielsen (1999).Ashman, Sara M. Grocery Store Buying Behavior: Evidence@om Loyalty Program Data
1
_______i
—
I
—.--—. —
3
0% 20’!4B 40% w%-) 80!4
Figure 3. How Retailers are Rewarding Customers.
Source: RFIC (1999).
The demographic data collected is unique to
customer loyalty databases; the traditional POS
scanner data collected by grocery store retailers
does not contain any demographic data. Demo-
graphic data is usually collected when the cus-
tomer obtains a customer loyalty card by filling
out a registration form. According to the RFIC’s
“1999 Supermarket Panel,” the most common
demographic data collected is name and address,
with phone number being collected to a slightly
lesser extent (Figure 4). These results are not snr-
pnsi.ng; this type of information is asked of con-
sumers on a regular basis and is consequently the
easiest to collect.
Very few retailers are collecting the most
informative, and perhaps most useful, demog-
raphic data. Household size, household makeup,
and competitor stores shopped are collected by
less than 15 percent of retailers surveyed. This
type of demographic data is harder to obtain from
consumers, especially if the consumer sees no
benefit in disclosing this type of information.
The second broad catego~ of data being
collected by retailers pertains to shopping trip be-
haviors and preferences. Shopping trip data is
collected at the POS via scanning and then loaded
into a retailer’s customer loyalty database. What
makes this type of data different from traditional
POS scanner data is that customer loyalty data is
tied to individual consumers and/or households
via the shopper identification card number. Scan-
ner data cannot tell you if a customer has been in
the store once during the past two weeks or every
day. Customer loyalty dat% however, can tell you
exactly how many times a customer has been in
the store in the last two weeks, month, or year.
Scanner data cannot tell you what days of the
week or time of day the consumer visited the
store. Customer loyalty data can tell you the day
of the week, the time they were at the checkout,
the checkout lane they were ~ and how they paid
for their groceries. Scanner data cannot tell you
what was in the basket of the consumer each time
s/he was in the store. Customer loyalty data can
tell you exactly what was in the consumer’s bas-
ket each time s/he was in the store; it can also tell
you the prices pai& units purchase~ total dollars
spent, and coupons redeemed.4 March 2000 Journal of Food Dis@ibution Research
J“- 8
—“——-”———
0 :/” 20% 40% Ml% WV!!, 100%
Figure 4. Data Collected, Demographics.
Source: RFIC {1999).
According to the RFIC’S “1999 Supermarket data would include information specific to each
Panel,” total dollars spent, frequency of transac- individual item purchased by the customer. For ex-
tions, and days shopped are the most commonly ample, the retailer would know the exaet size, vari-
collected shopping trip data (Figure 5). ety, flavor, price, and quantities of frozen pizzas
At the other end of the data collection spec- purchased. Or, the retailer could diseem customers
trum, less than 25 percent of retailers collect data who purchased a specific item on promotion fi-om
at the stock-keeping unit (SKU) level. This type of those who purchased a competing brand.
I
I
I
o‘% 2w% 40’% 60% 80’%,
Figure 5. Data Collected, Shopping Trips.
Source: RFIC (1999).Ashman, Sara M Groce~ Store Buying Behmior: Evidencefiom Loyalty Program Data 5
Analyzing the Data
Through the analysis of the&@ a retailer can
silently observe its customers’ purchase behavior
and track changes in behavior over time. The man-
ner in which the grocery store industry is currently
using the data can be organized into two groups:
(1) data used to impact key customer groups and
(2) data used to make store-level decisions.
Before retailers can use the data to impact key
customer groups or to make decisions, they must
fist analyze the data to understand their consum-
ers’ grocery store buying behaviors. For example,
at the very least retailers can analyze the data to
determine who their best customers are. Or, the
retailer can choose to analyze the data to determine
not only who the best customers are but what the
best customers are buying, what they are not buy-
ing how often they shop, how profitable they are,
and the amount of savings that they realize. This
type of analysis can be performed for any number
of customer groupings by simply replacing the
word “best” with other relative adjectives, such as
new customers, lost customers, untapped potential
customers, or declining customers. Thoroug,bly
analyzing customer loyalty data to understand gro-
cery store buying behavior allows retailers to fidly
exploit the power of the data.
According to the RFIC’S “1999 Supermarket
Panel,” targeted mailings are the most common
way that retailers are using their data (Figure 6).
By analyzing customer loyalty dat% the retailer
can, at the very least, determine the target group
for the mailing. With more in-depth analysis, the
retailer also can use the data to determine what
type of offer would be meaningfid and most ef-
fective for the targeted customer group.
Thanking customers is also a common use of
the data across the industry. Retailers can, at the
very least, analyze the data to determine whom
they wish to thank. If retailers want to detmmine
the most effective way to thank their customers—
for example, with a free item, dollars off their
next visit, or through a special service-the re-
tailer can analyze the data to determine which
venue would be most appreciated and would have
the greatest impact.
More than 65 percent of participating retail-
ers are using the data to impact declining or lost
customers while more than 50 percent are using
the data to impact new customers (RFIC, 1999).
At the ve~ least, the retailer can analyze the data
to determine which customers fall into each
group. By analyzing the data further, the retailer
can develop a program to effectively communic-
ate with each customer group. In the case of lost
or declining customers, retailers need to rebuild
their relationship with these consumers. With new
customers, retailers need to focus on strengthen-
ing their relationships.
W% 20% w% w% 8W?4 Itlo%
Figure 6. Using the Data to Impact Key Customer Groups.
Source: RFIC (1999).6 A4arch 2000 Journal of Food Distribution Research
Very fewretailers areusingthe data to seg-
ment their customer base to impact key customer
groups. Multi-dimensional segmentation involves
using more than one variable to segment your
customer base; for example, total doLlars spent
and frequency of transactions are used to segment
the customer base. By analyzing the data beyond
who belongs in each segment, the retailer can ef-
fectively communicate and strengthen their rela-
tionships with their consumers.
The second broad category of how retailers
are using customer loyalty data pertains to making
promotional and store-level decisions, Based on the
RFIC’S “1999 Supermarket Pane~” retailers are
using the data to make item-specific promotion
decisions (Figure 7). Retailers can analyze the data
to determine which items would be the most effec-
tive to use in a promotion across all customers. Or,
retailers could analyze the data to determine what
item would be most effixtive for unique customer
groups. For example, households with small chil-
dren would value promotions of baby items more
highly than one-person households would.
Retailers are also using customer loyalty data
to conduct targeted research. For example, if a
competitor store opens right across the street tiom
a retailer’s store, the retailer can analyze the cus-
tomer loyalty data to determine which customers
may be inclined to shop at the new store. By
identi~ng the vulnerable, or middle-tier, custom-
ers, the retailer can develop promotions specific to
those customers and can attempt to prevent them
from switching to the competitor store.
Retailers are also using customer loyalty data
to make category management and merchandising
decisions. A retailer can analyze its customer loy-
alty database with a particular group of customers
in mind, for example, the most profitable custom-
ers. By determining which types of products the
profitable customers find most valuable, the re-
tailer can then use this information to make deci-
sions that meet and potentially exceed the profit-
able customer’s expectations. For example, using
this type of information in conjunction with tradi-
tional category management information the re-
tailer can make product assortment and shelf
space allocation decisions in alignment with its
most profitable consumers. Or, the retailer can
determine which new products would likely be
well-received by its profitable customers.
Finally, less than 25 percent of retailers are
using customer loyalty data to make pricing or
labor-scheduling decisions (RFIC, 1999). Ideally,
a retailer could analyze its customer loyalty data-
base to determine a pricing strategy for an indi-
vidual store or an entire chain. For example, each
department or category could have its own pricing
strategy based on the preferences of the consum-
ers who shop the department or category. Or, a
retailer could align its entire store’s pricing strat-
egy to complement its most profitable or untapped
potential customers’ preferences.
-4
-b
-1
w% 2w% m% 6W?% $30%
Figure 7. Using the Data to Make Store-Level Decisions.
Source: RFIC (1999).Ashman, Sara M Groceiy Store Buying Behavior: Evidence@onz Loyalty Program Data 7
In terms of labor scheduling, a retailer could
ensure its most profitable customers that when
they shop the retailer’s stores, the shelves will be
filly stocked and the customers will be able to
efficiently move through the checkout line. Using
a customer loyalty database, a retailer can deter-
mine the days, and time of day, the most profit-
able customers are in the store. With this type of
information, eaeh store could adjust its labor
schedule to ensure that its shelves are stocked and
its checkout lines are fally staffed to better serve
the store’s profitable customers.
Issues and Concerns
Issues and concerns are rarely absent from
any new innovation or form of technology. In
the case of customer loyalty programs, several
issues and concerns exist. First, the volume of
data being collected is immense. Immediate is-
sues surrounding this concern include where the
data is going to be stored, how long it will be
stored, and whether sufficient technical knowl-
edge and support exist within the organization.
According to FMI’s 1998 “Electronic Marketing
Survey of Food Retailers,” 39 percent of the
respondents are limiting, or expect to limit, how
long the data is saved, and 24 percent of the re-
spondents limit, or expect to limit, the amount
of data collected and saved per customer (FMI,
1998).
The second concern is associated with ana-
lyzing the data. Appropriate software needs to be
purchased or developed, and analysts need to be
trained to utilize the software and to understand
and manipulate the results. Finally, priorities need
to be set with regard to how the data should be
analyzed.
The third concern relates to data integrity.
Maintaining a clean database is essential in ob-
taining meaningful and accurate results. Ad-
dresses change every week; customer loyalty
cards are 10SGcards are abused at the store level;
new cards are issued without obtaining accurate
customer information; price and item-level infor-
mation needs to be updated; new products need to
be added; and old products need to be removed
from the database. Processes need to be developed
to ensure that the data is accurate and that it is
maintained on a regular basis.
The fourth eoncem relates to customer privacy.
RetaMs have established policies that prevent the
privacy of their customers from being abused. Ty-pi-
cally, to receive the customer loyalty ear~ a state-
ment is provided on the registration form that the
customer fills out. It is essential that retailers con-
tinue to ensure the customers that their privacy will
be protected.
Finally, and perhaps most importantly, all
levels of management need to realize and accept
the value and power in analyzing customer loy-
alty data. Without the support and use of this
data by top levels of management, customer loy-
alty data will never become an acceptable tool
for impacting key customer groups and for mak-
ing effective and meaningful promotional and
store-level decisions.
Conclusion
The use of customer loyalty programs by the
grocery store industry is becoming more com-
mon. Through customer loyalty programs, retail-
ers can begin to understand their consumers’
shopping behaviors. Using the data collected at
the POS, retailers can impact key customer
groups and can make effective store-level deci-
sions. According to the Boston Consulting Group
(1997), using information appropriately will be
the most important challenge for retailers in the
next five to 10years.
Customer loyalty programs are also begin-
ning to impact store performance. According to
the RFIC’S “1999 Supermarket Panel,” 21 per-
cent of respondents are very satisfie~ and 62
percent are somewhat satisfied with the effect of
their customer loyalty program on store perform-
ance”(RFIC, 1999). According to FMI, increase
in sales volume and increase in transaction size
are the most common performance measure-
ments used to evaluate customer loyalty pro-
grams (FMI, 1999).
The costs associated with adopting and
maintaining a customer loyalty program are also
beginning to be offset. According to the RFIC’S
“1999 Supermarket Panel,” 15 percent of respon-
dents agree that a great deal of the cost associated
with a customer loyalty program is offset by in-
creased revenue, and 61 percent feel that some of
the cost is offset (RFIC, 1999). According to FMI,
more than one-half of respondents defray the cost
of a customer loyalty program, either through
manufheturers’ support or discontinuation of other
promotional programs (FMI, 1999).8 March 2000
References
ACNielsen. 1999. “Third Annual Frequent Shopper Survey
Study.”
Blair, Adam. 1999. “Supermarket Technology, The Big Pic-
ture.” SupermarketNews. February 22:1A–19A.
Boston Consulting Group. 1997. “Knowing Your Customer:
How Customer Information Will Revolutionize Food
Retailing, Project VII.” Coca-Cola Retailing Research
(hOtlp.March.
FMI (Food Marketing Institute). 1997. “Electronic Marketing
Survey of Food Retailers.”
FMI (Food Marketing Institute). 1998. “Electronic Marketing
Survey of Food Retailers.”
RFIC (Retail Food Industry Center). 1999. “1999 Supermar-
ket Panel.” Privately Held Database, RFIC, Department
of Applied Economics, University of Minnesota.
Journal of Food Distribution Research

GROCERY STORE BUYING BEHAVIOR: EVIDENCE FROM LOYALTY PROGRAM DATA

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Research Papers in Economics