5. We’re generating
huge volumes
of data
All of which helps to define
us, through our
behaviours:- what we like
- the brands we buy
- how we use channels
- what we think and feel
11. Holistic view of customers
What they look like
• Gender, age, life-stage (kids etc.)
• Hobbies and interests, lifestyle
• Socio-economic type
• Geographic location
What they think and feel
• Needs and values
• Motivations and barriers
• Attitudes and perceptions
• Preferences
Individual level data enables us to group customers into like-profiled
segments
Which in turn means we can create a content strategy for each segment
• Channel usage
• Web engagement
• Social engagement
• Purchasing behaviour
How they behave
12. Customer migration & segmentation
Using layered data to put
customers into discreet
like-profiled segments
15. Marketing and content calendar
Seasonal themes
Tactical and partner campaigns
Brand messaging
1-2-1 always on (behaviour driven)
Segmented
Content
(regular)
Individual
Level Content
(triggered)
16. Slightly more affluent family groups buy
infrequently – but spend the most when
they buy
The data also tells us that they appear
to be much more likely to buy large
pizza meals in the middle of the week,
specifically Wednesday’s when sales
from this group peaks dramatically
Source: Dominos customer database
Data tells us…
More after school clubs happen in the
middle of the week in the UK,
Wednesday’s being the most popular
day
Source: National statistics research
Research tells us…
They have busy careers and an equally
busy family to manage. Their lives are
hectic!
The last thing they want to do in the
middle of the week is dash back from
work, pick the kids up from school
clubs, and franticly race home to cook.
Source: Consumer focus groups
Psychology tells us…
17. Behavioural insights
Infrequent buyers…
but they buy a lot of pizza
when they do (so they
spend a lot), they don’t
buy on offer (so they’re
profitable)… and there
are quite a lot of them (so
any small increase in
frequency drives a lot of
revenue!)
19. Putting it all together
Regular communications
• Propositions and messaging
driven by content calendar
• Propositions vary based on
segment, so different groups
get discreetly different messages
• Frequency and communication
day also based on segment
and/or proposition
Always on triggers
• Next purchase
• Bounce-back offer
• Follow up trigger
• Lapsing trigger
• Birthday trigger
• Offer elapse reminder
• Thank you message
Segment Behaviour Product/offer Proposition Day
Meals for
One
Small /medium
pizza with
starters
Small pizza with free
starters and cookies
FA Cup Final meal deal Friday
Pizza for
Two
Large pizza with
few starters
Free Box Office
movie with Large
pizza and drink
Stay in and stay dry with a
movie and meal tomorrow
Saturday
Vouchers on
the side
1 or 2 pizzas with
starters & offers
BOGOF pizza deal
with sides and
desserts
FA Cup Final meal deal Friday
Family meals Large family /
pizza meals, Tues
or Weds
Midweek family
meal proposition
Midweek rescue service Wednesday
Two free
bottles of
Coke
With every third
order where drinks
previously ordered
Two eat for
the cost of
one!
When 3 purchases
made in the past
month
Not seen you
for a while
Get a free starter
or dessert (x days
since last order)
Just to say
thanks
Free pizza meal for
two with every 3rd
order over £20
20. The commercial case proving
incrementality
Set tangible
customer migration
objectives – which
can be benchmarked
and tracked
Measure incremental
revenue by ‘ring
fencing’ control
groups