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7/29/2019 Direct Marketing data analysis
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Direct Marketing Data Analysis
7/29/2019 Direct Marketing data analysis
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Our Approach
Understanding
the Data
Analysis using
Statistical Tools
DrawingInferences
MakingRecommendations
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Our Goals
Our consultation aims to help achieve the following business goals
Increase Revenue
Expand existing customer base (both acquisition and retention)
Identify problem areas ( and propose solutions for them)
Capitalize on untapped opportunities
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Data Comprehension
303
697
No of Customers
New Existing
506494
No of Customers
Male Female
498502
No of Customers
Unmarried Married
710
290
No of Customers
Close Far
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Data Analysis
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0.74
0.84
0.38
Prev Year This YearExisting New
64.3%
Observations
Overall, increase in revenue over
last year has been 64.3%
If we filter down to just the exitingconsumers, the increase in
revenue comes out to be 13.8%
The company seems to be getting
adequate revenue from new
clients. They should tap theseconsumers as a potential segment.
AUD Millions
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Observations
4%
9%
20%
26%
21%
14%
5% 1%
Revenue Segmentation based on
Salary
81% of revenue generated comes
from 65% of population
Salary between $ 40,000 and $1,20,000
As the salary/income of a family
decrease, we observe a decline in
the amount spent. Targeting this
audience with enticingpromotions is likely to change the
trend.
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Observations
13%
24%
29%
35%
Catalogues sent & Revenue
6 12 18 24
The amount spent by a consumer isdirectly proportional to the number of
catalogues he/she receives
Correlation value of 0.473 between
Amount Spent and No of catalogues
R-Square = 0.71, Coefficient = 42.71, p-
value ~ 0
More aggressive the direct marketing
campaign, higher the revenue generated.
Since this seems to be the only marketing
activity to draw reference from, the
company should increase the number of
catalogues sent to potential segments
(after considering the costs involved).
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Observations
Married population contributes 69% of
the total revenue as opposed to
singles, who contributes a 31% share.
For the married couples, the combined
income data is likely to influence the
higher salaries and further, the higher
amount spend.
31%
69%
Revenue & Marital Status
Unmarried Married
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Observations
15.1113.7
Marketing Effort across Customer
Base
Existing New
As stated before, total increase in
revenue is 64.3%
New Consumers: 50.5%
Existing Consumers: 13.8%
However, average number ofcatalogues sent per consumer is
slightly higher for existing consumers.
While the significance of client
retention cant be overstated, it could
prove hazardous to overlook thepotential of client acquisition, as a
majority of increase in revenue is
coming from latter.
Average Catalogue sent per consumer
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Observations
Out of the 697 existing consumers
the revenue from 294 consumers
decreased over last year, thus a
change in approach is required for
the segment.
Correlation value of0.535 between
Amount Spent and Previous Spent
R-Square = 0.71, p-value ~ 0
Last Year
Revenue
Decreases
Revenue
Increases
697294
403
This Year
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Opportunities
Correlation value of-0.222 betweenAmount Spent and Number of Children.
R-Square = 0.71, Coefficient = -203.47, p-value ~ 0
Revenue generated is inverselyproportional to number of kids in family.
The company can tap the segment byintroducing lucrative offers related tokids products.
The company should aim to maintain abalance between consumer acquisitionand consumer retention. It might be agood idea to approach both segments
with different marketing strategies. The existing clients could be offered
loyalty bonuses whereas, newconsumers could be brought on-board byoffering newbie discounts.
1,407
1,220
941831
0 1 2 3
No of Children
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Threats
It is observed that people living in
vicinity of similar shops tend to spend
$ 535 less per person on an average as
compared to consumers who live In
the middle of Nowhere.
It is likely that these consumers have
other options to choose from, which
results in a decrease in average
amount spent on this company
1,596
1,062
Close Far
50%
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Methodology
Correlation
Regression Analysis
Descriptive Analysis
Pivot Table Analysis
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Thank You