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John
Chesak
Director, Retail Product
Management
Spectra
Jim
Dippold
VP, Marketing
ACNielsen
If you see the
same customer each week or observe a customer with a cart
that’s heaped, do you equate their frequency or spending
level with loyalty? Retailers today can increasingly identify
their big spenders or find the ones that come in the door
most often, but without a perspective on the household’s
total spending, retailers do not know what percentage of their
customer’s total dollars they are losing to the competition.
Competition is getting tougher too. Most U.S. retailers are
feeling the squeeze—on one end, by price-focused mass
merchandisers, category killers and dollar stores, and on
the other end, by smaller “niche” merchants that
deliver specialty SKUs, high focus on customer service and/or
unique customer shopping experiences.
To compete, many retailers have looked to various forms of
customer loyalty marketing to develop a “profitable
differentiation” strategy to identify, monitor and increase
the yield of their best customers through interactive value-added
relationships. However, one of the most successful tactics—frequent
shopper programs (FSP)—have in many cases become ubiquitous
discount mechanisms that are not necessarily tied to targeting
specific shoppers or customer segments in order to build loyalty.
Frequent shopper programs in the U.S. are reaching their saturation
point. Slightly more than 80% of U.S. households participate
in a frequent shopper program—the same as a year ago
[See chart 1]. And while the majority of households recognize
the value of the program, a great majority of participants
have more than one retailer’s card [See charts 2 and
3]. The “loyalty” part of “loyalty marketing”
is not to be found in a typical frequent shopper program.
What Frequent Shopper Data Isn’t Telling You
Frequent shopper programs were intended to help the retailer
understand their current customers and create tailored marketing
programs that grow revenues and build affinity. But for many
retailers, that goal is not their reality. It is something
of a misnomer for retailers to assume that big spenders in
their stores are “loyal” customers. In actuality,
dollars spent in the store present only a partial picture.
To truly understand the level of loyalty a customer has to
a retailer (or to measure the effectiveness of building loyalty
over time), a retailer needs to understand who the customer
is and what portion of the household’s total dollars
are spent in-store and out-of-store—their “share
of consumer.”
Understanding “Share of Consumer”
Although most retailers have the capability to identify the
customers who make up their largest spenders, they do not
know what percentage of their customer’s total shopping
dollars are spent outside their store and given to the competition
or what key geodemographic elements are driving behaviors.
This limits a retailer’s understanding of who their
most valuable customer is and where the potential opportunities
for growth lie. Using Spectra and ACNielsen, retailers can
profile the households in their database and discover what
the customers in their stores, as well as total households,
are spending in the grocery channel and within categories.
With an understanding
of who their customers are and what portion of their wallet
the retailer is capturing within the grocer channel or at
the category level, the retailer will be able to develop a
profitable differentiation by more effectively targeting the
customers who are already in their store—turning them
from “shoppers” to “buyers” in more
of the retailer’s categories, taking dollars away from
the competition and attracting households like their most
valuable customers.
Chart 4 highlights this point. Analyzing specific households,
one can see that some of the top ranking households (measured
by sales inside the retail location) actually have only about
half that household’s total dollars spent. To attract
more of these households’ dollars, retailers must find
new and different ways of attracting and promoting to these
shoppers.
Simple Complexities
However, to add complexity to the task at hand, it is clear
that share of consumer on a household level doesn’t
equate to the same share of consumer on a category level.
Using the above example of “Julie,” the highest
dollar spender and one of the top in overall share of consumer
for this particular retailer, it is clear to see that her
share is not consistent across categories [See chart 5]. A
good portion of her purchases of dairy and bread occur at
this retailer, indicating higher loyalty to those particular
categories in this store. However, some categories show quite
a low share (low loyalty), requiring a focus by the retailer
to help incentivize “Julie” to shop these categories
in-store.
Unfortunately for
retailers, the same measures also can differ by category and
store, as well as customer groups. As illustrated below, all
categories may appear to attract the same share of consumer
within a store. But breaking it down based on customer segment,
or as a percentage of total category sales in-store, it becomes
clear that certain shoppers are more important than others
[See chart 6].
So even if retailers know who their loyal customers are and
what they spend in their stores, it is key to understand what
percentage of their customer’s total dollars they lose
to the competition for each key category. With this understanding,
retailers will be able to increase their overall share of
consumer by reducing the loss of existing loyals and by driving
less loyal customers, more frequently and with larger market
baskets, into their stores.
An Example
Looking at the shampoo category [See chart 7], we can see
that loyal shampoo customers (defined as those spending over
70% of their category purchases at the particular retailer)
make up only 5% of the total purchasers, while competitive
customers make up the majority. On a percent of sales basis,
it is the switchers that make up the majority of dollars.
Clearly, the retailer has opportunities to get more of these
competitive and switcher customers to purchase in the category.
A closer look at the category shows that switchers make up
a sizeable dollar potential ($9.7 million) within the category,
and would likely be more apt to purchase at the retailer than
the competitive customers.
Segmenting the Segment
Using the Spectra segmentation, the switcher category can
be segmented in a way that is meaningful from a marketing
perspective [See chart 8]. Looking at the shampoo switchers,
the top three demographic clusters (in terms of dollars spent
outside the retailer) were Down Scale with Kids, Upper Incomes
with Kids, and Senior Shoppers. These 99,159 current retailer
customers represent a targeted opportunity of $7 million.
And based on ACNielsen and Spectra information, one can identify
the specific households, where they live, and where they shop
for a focused direct-to-consumer campaign. Incorporating insights
on product “potentials,” media usage and attitudinal
data can help the retailer target specific customer segments.
Moving to Loyalty
The Segmentation Marketing approach, as demonstrated above,
creates a strong relationship with a retail client’s
most valuable customers. It is a key component to future success
in loyalty marketing, given the ubiquity and fragmentation
of today’s programs and consumers.
The next generation of “segmentation marketing”
lies in increasing the depth of customer analysis. By leveraging
ACNielsen and Spectra assets, one can dramatically improve
the ability to predict a household’s spending level
to a particular product category, and thus enable the creation
of strategies and tactics for changing or rewarding consumer
spending at the category level.
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