how business intelligence and mapping can improve your business: customer and competitive analysis
DESCRIPTION
How Business Intelligence and Mapping can Improve Your Business: Customer and Competitive Analysis. Monica L. Perry. “Where’s” your Most Critical Strategic Marketing Problem?. Customers Competitors. Customers Competitors. Choosing Deciding. Understanding Knowledge of. Positioning - PowerPoint PPT PresentationTRANSCRIPT
1
How Business Intelligence and Mapping can Improve Your Business:
Customer and Competitive Analysis
Monica L. Perry
2
““Where’s” your Where’s” your Most Critical Strategic Marketing Problem?Most Critical Strategic Marketing Problem?
Implementin
g
Implementin
g
Choosing
ChoosingDeciding
Deciding
Controlling
Controlling
Understanding
Understanding
Knowledge of
Knowledge ofCustomersCustomersCompetitorsCompetitors
PositioningPositioningProductProduct
PricePricePlacePlace
PromotionPromotion
CustomersCustomersCompetitorsCompetitors
CustomersCustomersCompetitorsCompetitors
CustomersCustomersCompetitorsCompetitors
3
Why Location is Critical to Customer BehaviorWhy Location is Critical to Customer Behavior
WhereWhereCustomerCustomerOperates,Operates,
Lives, Lives, Works, PlaysWorks, Plays
WhereWhereCustomerCustomerOperates,Operates,
Lives, Lives, Works, PlaysWorks, Plays
PreferencesBehaviors
AttitudesInterests
Needs
What, Where, When and How Customers BuyWhat, Where, When and How Customers BuyImpact and Availability of CompetitorsImpact and Availability of Competitors
4
Target Markets:Target Markets: The value of knowing “Where” The value of knowing “Where”
Choosing
ChoosingDeciding
DecidingUnders
tanding
Understanding
Knowledge of
Knowledge ofCustomersCustomersCompetitorsCompetitors
CustomersCustomersCompetitorsCompetitors
5
Profiling Customers’ Mean Travel Time (by Census Tract for 91711 Zip)
6
Profiling by Block GroupMen’s Apparel NYC
• http://www.mappinganalytics.com/consulting/site-selection.html
7
Marketing Mix Decisions:Marketing Mix Decisions:The value of knowing “Where”The value of knowing “Where”
Geodemographic SegmentationEstimating Potential and Sales ForecastsCustomer Cloning
Choosing
ChoosingDeciding
DecidingUnderstanding
Understanding
Knowledge of
Knowledge ofCustomersCustomersCompetitorsCompetitors
PositioningPositioningProductProduct
PricePrice
PlacePlacePromotionPromotion
CustomersCustomersCompetitorsCompetitors
8
Site Market Modeling - Known to Unknown Forecasting, Sales Potential
High Revenue
Site
Low RevenueSite
Use information about known sites to predict performance of proposed sites
ForecastHigh or LowRevenue?
9
Site Market Modeling - Known to Unknown Customer Cloning, Marketing Mix Geo-
Customization
High Revenue
Site
Low RevenueSite
Use information about known sites to predict performance of proposed sites
ForecastHigh or LowRevenue?
10
Retail Trade Area Analysis
Source: Segal (1998) Retail Trade Area Analysis: Concepts and New Approaches http://www.directionsmag.com/features.php?feature_id=5
Figure 2a. Patronage probability model - theoretical store trade area.
Blue – green – yellow – red progression represents zones of increasing patronage probability.
11
Retail Trade Area Analysis: Drive Time
Source: Segal (1998) Retail Trade Area Analysis: Concepts and New Approaches http://www.directionsmag.com/features.php?feature_id=5
Figure 3b. Drive time analysis showing the location of demographic samples. Blue dots = sample within a 10-minute drive.
Green dots = sample within 5-mile radius, but outside 10-minute drive time polygon. Red colored dots that fall within the 15-minute drive time polygon represent demographics
that would not be included using a traditional 5-mile radius approach
12
Marketing Mix Decisions:Marketing Mix Decisions:The value of knowing “Where”The value of knowing “Where”
Which Sites, Territories are Underperforming? Overperforming?Profiling Customers
Choosing
ChoosingDeciding
DecidingUnderstanding
Understanding
Knowledge of
Knowledge ofCustomersCustomersCompetitorsCompetitors
PositioningPositioningProductProduct
PricePrice
PlacePlacePromotionPromotion
CustomersCustomersCompetitorsCompetitors
13
Retail Trade Area Analysis
• Source: Segal (1998) Retail Trade Area Analysis: Concepts and New Approaches http://www.directionsmag.com/features.php?feature_id=5
Trade area map - revenue concentration by block groupsTrade area map - revenue concentration by block groupsblue – green – yellow – red = progression from low to high revenue. blue – green – yellow – red = progression from low to high revenue.
14
Marketing Mix Decisions:Marketing Mix Decisions:The value of knowing “Where”The value of knowing “Where”
Choosing
ChoosingDeciding
DecidingUnderstanding
Understanding
Knowledge of
Knowledge ofCustomersCustomersCompetitorsCompetitors
PositioningPositioningProductProduct
PricePricePlacePlace
PromotionPromotion
CustomersCustomersCompetitorsCompetitors
A few examples….• Hewlett Packard• BMW Lead Generation Direct Mail• Albertson College
15
Some Geo-Customization in Marketing Communications
• Hewlett Packard
• BMW Lead Generation Direct Mail
• Albertson College
16
HP Direct Email
17
BMW Lead Generation program
• Five levels of customization
18
The right creative: Albertson College
• The small town location offered different advantages to different students.
• What creative differences are apparent?
• What additional geographic variable(s) could be used in deciding which creative to send to prospective students?
19
““Where’s” your Where’s” your Most Critical Marketing Problem?Most Critical Marketing Problem?
Implementatio
n
Implementatio
n
Planning
Planning
Control
Control
AnalysisAnalysisCustomersCustomers
CompetitorsCompetitors
PositioningPositioningProductProduct
PricePricePlacePlace
PromotionPromotion
CustomersCustomersCompetitorsCompetitors
CustomersCustomersCompetitorsCompetitors
CustomersCustomersCompetitorsCompetitors
20
What Questions What Questions Do You Have?Do You Have?