PromotionMntSolutionExt_110428

…real time CRM
27.11.2016 Promotion tool, © Invite CRM, Ltd.,
02/2011
1
Promotion management solution
Introduction
© Invite CRM, Ltd., 02/2011
Based on data from

27.11.2016 Promotion tool, © Invite CRM, Ltd., 02/2011 2
Situation
• Over 50% of food sold in sales promotions and increasing
• In some categories promotions cover whole year
• All brands run on promotions – it is becoming market standard
• Missing ability to evaluate and predict promotion results
• Retailing shrinked to „leaflet management“
• Negative impact on profitability and brand value

Priorities

Methodology
System solutions
Project dimensions
Promotion analytics
Category management
Account management
ERP data
Basic Nielsen, Incoma leaflet monitor
Customer data – all sources
Retail systems data
Fixed data model
Data mining, fuzzy logic, dynamic models
ERP + Nielsen data
All relevant data
Price driven
Leaflet driven
Differentiation, non-price
Consumer insight driven
One solution for all
Price driven
Understanding specific market position
Understanding category and consumer specifics

Marketing and trade marketing requirements
• As the channels (share of international chains) are getting
importance trade marketing is becoming more important
• Strong link to production management forecasting and logistics
• Not only value and volumes but also brand attributes and long-term
measures
• Need for relationship and methodology building with key accounts –
new approach to category management
• New ways of cooperation – in-depth data exchange (ClubCard)
• Understanding clear roles of various channels – leaflets, point of
sale – getting the mix right
• Promotions based on non-price argumentation – come back to core
brand values
• Increased need for prioritisation – effectiveness, short x long-term
gains
• News definition of reporting, controls, risk and fraud management

Applied principles 1
• Holistic business view – complete business intelligence
– Combine „push“ and „pull“ perspectives (internal and customer views)
– Cover full pipeline – from identifying opportunity, through funnel mnt
(prioritisation in campaign pool) to evaluation
– Include account management – business relationships with customers
influencing promotion setting and value
– Understand the whole campaign process – from advertising message
exposure to purchase
• Uncover cause – effect relationships
– Get a complete picture of campaign result drivers by putting together
• Critical data sources
• Making link between customer – account actions – promotion results
– Ability to drill down in customer decision process
• From brand awareness – through campaign exposure – campaign
involvement (registering to competition) – purchase – post purchase
activities – repeat purchase

• Total channel management
– Combine off-trade and on-trade perspective
– Combine modern and traditional markets
• Share, collaborate, learn and achieve win-win
– Prompt active participation of all critical involved parties – such as all
participating depts, ontrade and offtrade customers, creative and
communication agencies AND consumers
• Understand channel and media role
– Consumer spend is driven by various channels and media
communication, whether it is public or retail (instore) media – for
effective campaign evaluation we have to control and monitor complete
channel mix
• Involve consumers directly
– By involving consumers directly via own channels and solutions supplier
can achieve better campaign results and understand better decision
process – being less dependent on customers‘ acts

• Build categories
– Promotions from retailer point of view should increase category
performance – share (volume), profit
• Build portfolio
– Understand parasite effects
– Create distinctive positioning of your brands
• Build brands
– Promotions should be perceived as part of total marketing mix with aim
to build long-term brand equity
– From this perspective discounts and high frequency of sales promotions
destroys brand values and undermine brand‘s ability to produce profit

Impact to other value driving processes
• Corporate strategy
– Insight and understanding of promotion results will have a major impact
to corporate strategy due to relationship to consumer and behaviour,
brand positioning and competitive strategy which is than reflected in
market yield
• Product design
– Understanding of driving forces behind consumer behaviour in
promotions and off-promotions is important for product design and
innovations – product attributes, speed of life cycle, parasite effects etc.
• Logistics
– Understanding promotion drivers and ability to predict promotion results
has a major impact to logistics model – right volumes at right places at
right time
• Production planning and optimisation
– Precise forecasting of promotion result and channel pipeline
management (ontrade and offtrade) is crucial for correct production
planning and optimisation

Solution – step 1
Understand what makes promotion effective
Brand choice
(own, competitive)
Occasion
Channel
Format
Communication
Price
Packaging
Display
In order to forecast promotions we have to understand cause-effect
relationships among various parameters influencing consumer decision
process and their impact to promotion results
Weather
Socio-demo

Solution – step 2
Manage promotions as part of category strategy
consumer
Awareness
Attitudes
Preferences
Category strategy and performance
Sub-category strategy and performance
Portfolio strategy and performance
Brand strategy and performance
SKU strategy and performance
Promotion planning and management
Impact to: category usage, brand, price perception etc.
retailsupplier

Manufacturer/Retailer Cooperation
Category
Management
Retailer/Manufacturer Cooperation
Efficient Assortments
Efficient Promotions
Efficient Product Introductions
Efficient Replenishment
Efficient promotions as part of category
performance scorecard
Chart by Jerry Singh

Value chain coverage model
value chain
retail
media
on-trade
off-trade
production
ERP sales&marketing application
wholesale

Data integration architecture
Invite CRM
Consumer
interface
Online
consumer
data
ERP
DWH
Price monitoring
+ other market data
Incoma/GfK
Nielsen
Customer
Supplier
Agency

Promotion effectiveness data model
promo
data
model
store
time
event
consumer
income
transaction
media
packaging price
customer
EAN
wheater
brand
perception
society

Promotion effectiveness data model
• Essential data
– Incoma GfK Leaflet monitor
– Incoma GfK Shopping monitor
– Incoma GfK Instore
communication
– Incoma GfK Price sensitivity
– Incoma GfK Key account shopper
profile
– Nielsen Market data
– Nielsen Promo monitor
(Distribution, Price, Promo types,
Secondary display, Facings,
Shelve shares)
– Nielsen Indepth promo analyses
– Beer category pricing monitor
– SAP (sales) data
– GfK Consumer panel data
– Consumer response to campaigns
(CTR etc.)
• Extended data
– Retailers‘ transaction data
– Online behaviour tracking
– …
In order to build complete
data base for evaluating
promotion effectiveness and
understanding cause-effect
relationship following data
sources are suggested

Data model – sample

Data sources roles
Strategic
Depth
OperationalFrequency
ERP
ERP
Retail
Retail
GfK
panel
GfK
panel
Nielsen
Incoma
Nielsen
Incoma

Promotion evaluation:
current assessment weaknesses
• Current sales and promotion data
do not provide clear explanation of
the promotion success drivers
• There is no clear evidence or
relationship between key
parameters such as price,
discount and volume sold
• Also competitive promotion impact
= consumer switching behaviour
and patterns is very difficult to
understand without „consumer
perspective“ just based on sales
data

Promotion evaluation:
current assessment weaknesses
• Price elasticity analyses
focusing on promotional price ie
discount provided again does
not provide explanation and
clear evidence – relationship
between best discount/volume
mix
• In our experience from complex
retail data analyses only
complex data model covering
most possible influence factors
and relation data mining can
identify possible drivers and
provide „guide“ to best
promotion mix

Supplier-retailer cooperation model
ECR concept
• Joint planning and management
– Assortment management
– ATL and BTL campaigns management
– Event management
• Market data exchange
– Basic sales data – categories, SKUs
– Sales data combined with customer (data from
loyalty program)
– Complex data – substitutes, associations
(transaction and market data)
• Supply chain optimisation
– De/listing
– Document management
– Stock management
– Settlement
Connectivity to most cash
register systems allow for
advanced ECR models

Unified supplier management interface
supplier retailer
EDI/ECR
Trading data
Stock data
Market data (Nielsen, GfK)
Consumer data
Planning & forecasting
Replenishment
Campaign management

Examples of data outputs for retail promotion
• This particular promotion was
focusing on establishing and
developing beer as destination
category – it was one month long
and promoted mainly premium
brands
• In all aspects (value, volume,
margin) after promotion results
were significantly better then
before = category has grown –
with more weight towards
premium brands
• Profit in after promotion period
went up by 17%!
Tržba (Kč)
0
20000
40000
60000
80000
100000
120000
KRUŠOVICE
M
UŠKETÝR
0,5l
HEINEKEN
0,5lSKLOSVIJANSKÝ
M
ÁZ
11%
0,5l
HOEGAARDEN
W
HITE
0,33lsklo
FRISCO
0,33lSKLO
PIVO
M
ASTER
POLOTM
AVÝSPECIÁL0,355l
PIVO
M
ASTER
TM
AVÝSPECIÁL0,355l
PIVO
M
ASTER
ZLATÝ
SPECIÁL0,355l
FRISCO
DRY0,33l
22.9. - 1
Beerfes
3.11. - 2
Množství (ks)
0
2000
4000
6000
8000
10000
12000
14000
KRUŠO
VICE
M
UŠKETÝR
0,5l
HEINEKEN
0,5lSKLOSVIJAN
SKÝ
M
ÁZ
11%
0,5l
HOEGAARDEN
W
HITE
0,33lsklo
FRISCO
0,33lSKLO
PIVO
M
ASTER
PO
LO
TM
AVÝ
SPECIÁL0,355l
PIVO
M
ASTER
TM
AVÝ
SPECIÁL0,355l
PIVO
M
ASTER
ZLATÝSPECIÁL0,355l
FRISCO
DRY
0,33l
22.9. - 10.1
Beerfest (1
3.11. - 21.1
Zisk (Kč)
0
5000
10000
15000
20000
25000
30000
KRUŠOVICE
M
UŠKETÝR
0,5l
HEINEKEN
0,5lSKLOSVIJANSKÝ
M
ÁZ
11%
0,5l
HO
EGAARDEN
W
HITE
0,33lsklo
FRISCO
0,33lSKLO
PIVO
M
ASTER
PO
LO
TM
AVÝ
SPECIÁL0,355l
PIVO
M
ASTER
TM
AVÝ
SPECIÁL0,355l
PIVO
M
ASTER
ZLATÝSPECIÁL0,355l
FRISCO
DRY0,33l
22.9. - 10.1
Beerfest (1
3.11. - 21.1

Example of basket data analyses:
beer basket
• Example from our work for
retail chain – typology of
consumer basket/spend
• Separate beer basket was
identified as one of the
destination categories with
over 60% share on basket
• Beer was identified as key
element in number of other
baskets
• Associations – items
purchased together were
identified as inputs to leaflet
optimisation
Pivní koš
8,40%
7,28%
19,40%
14,07%
8,30%
9,92%
9,96%
12,31%
10,35%
8,40%
7,28%
19,40%
14,07%
8,30%
9,92%
9,96%
12,31%
10,35%

Possible outputs from retailers‘ own data
• Purchase profile
– Category profile – category roles – destination
categories, secondary categories
– RFM data – recency, frequency, monetary
information
– Brand profile – brand mix, complementary
brands, substitute brands
– SKU profile – SKU mix, complementary and
substitute SKUs
– Other 100s of analyses over basket data –
associations (regular mix with other
categories and SKUs – cobrand promo ideas),
seasonality, price sensitivity etc.
• Social-demographic profile – only available
at retailers running loyalty program
– Gender, geographic, income, education
Nedělní blesk
Kaiserka
cereální rozpek 50g
Vodka 37,5%
0,5l
Mléko kefírové Milkin
500ml
Zlatopramen 11 0,5l
Zlatopramen 11 Maxi 1,5l
Raženka 43g
Bonaqua
jemně perlivá 1,5l
Hořčice
plnotučná alba 200g
Sýr tvarůžky
malé 100g

Promotion management and assessment model
Consumer
proof of purchase
promotion
(SMS)
Consumer
leaflet
promotion
(lower sales out)
Nielsen data
Retail
delivery
(higher sales in)
ERP data
TIME
Consumer
statistics
Retail
statistics
Final
statistics

Project streams
Understanding and setting up
brand portfolio
category
key account
vision, goals
Defining data model
for promotion analyses
&
brand performance
Promotion,
brand performance
data model
proofing and testing
data mining procedures
Redefining category
and promotion management
principles with selected
retail chains
Identify and ensure
data sources
Provide data
Building target solution
Strategy
IT
Organisation
Piloting & testing
Continuous
improvement

Value chain coverage model
value chain
retail
media
on-trade
off-trade
production
wholesale

Model detail – ERP
• ERP is a critical data source for overall promo
model and solution – target promo DB would
need to connect to ERP (SAP) and import
entities such as EAN, customer ID, value,
volume, packaging, price/discount etc.
• Invite CRM has implemented number of
interfaces to common ERP systems such as
SAP, Navision, Karat and number of
proprietary ERP systems
• Invite CRM team contains experienced SAP
specialists who will lead the subproject
• Data transfers run on-line or in batches with
incremental and overwrite data controls
• Invite CRM is using most common interface
technologies such as webservices,
integration services, files import (XML, XLS,
TXT)
value chain
retail
media
on-trade
off-trade
production
wholesale

Model detail – media
• Invite CRM can provide complete media mix
either directly integrated into solution (email,
mobile, lettershop, internet, call centre) or
indirectly via media partners
• Integrated media campaigns can be planned,
executed and analysed directly in application
including real time feedback on its
performance
• Whole campaign process (funnel) can be
tracked with impact to consumer decision
process making link between campaign,
media and purchase
• Campaign response is recorded in consumer
profile and used for further campaign
planning and optimisation
value chain
retail
media
on-trade
off-trade
production
wholesale

Extended
campaign
a) segmentation
b) targeting
Extended campaign
a) complex customer relationship
b) proof of purchase as result of campaign
Traditional campaign elements
Purchasing behavioral tracking
example
behavioral
targeting
advert
exposure
registration
reaction to
advert
purchase
value chain
retail
media
on-trade
off-trade
production
wholesale

Model detail – consumer
• Invite CRM can create complete consumer
behaviour picture combining data from GfK
consumer panel, Mindec online research tool
and internet behavioural profiling tool by
BBelements/nugg.ad
• Collected data provide not only basic socio-
demographic data but also life style and
interest profiles which allow for much more
indepth understanding of consumer decision
process
• Part of profile may be competitive
assessment ie themes, brands and
promotions attracting the consumer
• As a result Invite CRM provides rich
consumer profile used to more precise
promotion value proposition, targeting and
precise assessment
value chain
retail
media
on-trade
off-trade
production
wholesale

Model detail – off-trade
• Invite CRM connects to standard market
reports such as Nielsen market audit, Incoma
Leaflet monitor, GfK Consumer panel, price
monitoring etc. and creates combined view of
reaction to campaign
• Invite CRM can also provide direct access to
transaction data via our retail ERP partners
using existing data interface – thanks to such
ability, Invite is able to run detailed basket
analyses and provided added value to basic
sales data such as supplementary and
complementary product and brands,
associations
value chain
retail
media
on-trade
off-trade
production
wholesale

Model detail – off-trade
• Invite CRM connects to Global System and
other POS system providers
• Detailed basket structure analyses are now
available at the listed retail chains and in
some cases even extended to customer
profile
• Invite CRM is involved in current retail
projects with other chain to implement similar
solutions which would allow for in-depth data
exchange between supplier and retailer
• Complete set of various retail outlets in such
network would cover majority of retail
segments and consumer target groups
value chain
retail
media
on-trade
off-trade
production
wholesale
Chain A
Chain B

Model detail – on-trade
• Due to its interactive consumer touchpoints
Invite CRM can be highly effective in running
on-trade promotions
• In combination with on-trade market data (for
example Data Servis or Incoma GfK) Invite
can provide comprehensive insights into on-
trade behaviour and cause-effect
relationships
value chain
retail
media
on-trade
off-trade
production
wholesale

Model detail – knowledge DB
• Invite CRM gathers all relevant consumer
behavioural data in one single DB creating
full picture providing most comprehensive
platform for planning, executing and
evaluating FMCG and retail promotions
value chain
retail
media
on-trade
off-trade
production
wholesale
on-trade
off-trade

PromotionMntSolutionExt_110428

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (15)

Similar to PromotionMntSolutionExt_110428

Similar to PromotionMntSolutionExt_110428 (20)

More from Jan Bízik

More from Jan Bízik (19)

PromotionMntSolutionExt_110428