1The high street retailer Boots launched its Advantage loy-
alty card in 1997. Today, there are over 15 million card
holders of which 10 million are active. Boots describes the
benefits for its card-holders as follows:
The scheme offers the most generous base reward rate
of all UK retailers of 4 points per £1 spent on products,
with average card holders receiving 6.5 points per £1
when taking into account all other tactical points offers.
There are 23 analysts in the Customer Insight team run by
Helen James who mine the data available about card users
and their transactional behaviour. They use tools including
MicroStrategy’s DSS Agent and Andyne’s GQL which are
used for the majority of queries. IBM's Intelligent Miner for
Data is used for more advanced data mining such as seg-
mentation and predictive modelling. Helen James
describes the benefits of data mining as follows:
From our traditional Electronic Point-of-sale data we
knew what was being sold, but now [through
data mining] we can determine what different groups of
customers are buying and monitor their behaviour
over time.
The IBM case study gives these examples of the applica-
tions of data mining:
What interests the analysts most is the behaviour of
groups of customers. They are interested, for example,
in the effect of Boots’ marketing activity on customers –
such as the impact of promotional offers on buying pat-
terns over time. They can make a valuable input to
decisions about layout, ranging and promotions by
using market basket analysis to provide insight into the
product purchasing repertoires of different groups of
customers.
Like others, Boots has made a feature of multi-buy pro-
motional schemes in recent years with numerous ‘three
for the price of two’ and even ‘two for the price of one’
offers. Using the card data the Insight team has now been
able to identify four groups of promotion buyers:
the deal seekers who only ever buy promotional lines;
the stockpilers who buy in bulk when goods are on
offer and then don't visit the store for weeks;
the loyalists – existing buyers who will buy a little more
of a line when it is on offer but soon revert to their usual
buying patterns;
the new market – customers who start buying items
when on promotion and then continue to purchase the
same product once it reverts to normal price.‘This sort of analysis helps marketeers to understand what
they are achieving via their promotions, rather than just
identifying the uplift. They can see whether they are
attracting new long term business or just generating short
term uplift and also the extent to which they are cannibal-
ising existing lines,’ says Helen. Analysing market basket
trends by shopper over time is also providing Boots with
a new view of its traditional product categories and
departmental spanides. Customers buying skin-care
products, for example, often buy hair-care products as
well so this is a good link to use in promotions, direct mail
and in-store activity.
Other linkings which emerge from the data – as Helen
says, quite obvious when one thinks about them – include
films and suntan lotion; sensitive skin products – be they
washing up gloves, cosmetics or skincare; and films and
photograph frames with new baby products. ‘Like many
large retailers we are still organised along product cate-
gory lines,’ she says, ‘so it would never really occur to the
baby products buyers to create a special offer linked to
picture frames – yet these are the very thing which new
parents are likely to want.’
‘We’re also able to see how much shoppers participate
in a particular range,’ says Helen. ‘They may buy tooth-
brushes, but do they also buy toothpaste and dental
floss?’ It may well be more profitable to encourage exist-
ing customers to buy deeper in the range than to attract
new ones.
Monitoring purchases over time is also helping to iden-
tify buying patterns which fuel further marketing effort.
Disposable nappy purchases, for example, are generally
limited by the number of packs a customer can carry. A
shopper visiting Boots once a fortnight and buying nap-
pies is probably buying from a number of supply sources
whereas one calling at the store twice a week probably
gets most of her baby’s nappy needs from Boots.
Encouraging the first shopper to visit more would proba-
bly also increase nappy sales. Boots combines its basic
customer demographic data (data such as age, gender,
number of children and postcode) with externally available
data. However, according to Helen ‘the real power comes
from being able to combine this with detailed purchase
behaviour data – and this is now being used to fuel busi-
ness decisions outside of the marketing arena.’
An analysis of how Boots customers shop a group of
stores in a particular geographical area has led to a greatly
improved understanding of the role different stores play
within that area and the repertoire of goods that should be
offered across the stores. For example, Boots stores have
typically been grouped and merchandised according toCASE STUDY 6Case Study 6 Boots mine diamonds in their customer data
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