stratagy management

1. STRATEGY
M A N A G E M E N T
m e e t o u r t ea m
Submitted by:- Tanya agarwal-P221A064. Abhinav Shankar-P221A002. Payal Dagar-P221A039.

2. DATA ISSUEREPORT
Framework for dataquality
Missing Values
Accuracy
Validation
Data Gaps
Duplicates
Referential integrity
Baseline
Data Definition
More detailed descriptions of data quality issues discovered, and mitigation methods used are
provided further. To avoid future data quality issues, recommendations and explanations are
provided. By analyzing and reporting on data quality, we can identify areas for improvement,
prioritize data cleansing and enrichment activities, and ensure that data is fit for solving problem.

3. Accuracy
Referential
Integrity
Completeness
Issues
Consistency Issues
Currency
Relevancy
Validity
Missing a profit column in “Transactions”; DOB is inaccurate in “Customer Demographic” and
missing Age column.
As customer id 5034 does not exist in the customer demographics sheet its an referential integrity
issue and therefore will be omitted.
Additional customer ids were inconsistent in “Transaction”, “Customer Address” and “Customer
Demographic”.
Inconsistency in gender for “Customer Address” and “Customer Demographic” respectively
People that are ‘Y’ in deceased_indicator for “Customer Demographic” are not current customers
Lack of relevancy in default column for “Customer Demographic” and order status for “Transactions”
Format of list_price; product_sold_date for “Transaction”
The suggestions below will help to improve the quality of data used to influence business
decisions.

4. BUSINESS
ANALYSIS

5. Revenue Growth
Based on
revenue growth, it can
the analysis of the
be
concluded that Company is a
moderately
Although
experienced
good business.
the company
some negative
growth, it managed to recover
with impressive growth in some
months. Therefore, the company
needs to focus on its growth
strategies to ensure consistent
growth and profitability in the
future.

6. Sources of Revenue
From the data we have 3 type of customers -
mass customers, affluent customers, high net
worth customers with 50%
, 24% and
26% the revenue
generation
contribution in
respectively
Recommendation- it may focus on attracting
more high net worth customers or increasing
the spending of its affluent customers.
Alternatively, it may try to increase its
customer base by targeting the mass customer
segment.

7. Revenue and Profit analysis
We have highest amount of revenue and profit generated from mass customer. Total profit
generated by affluent and high net worth are almost equal.
Customer id Average profit Average Revenue
Affluent
556.0960982 1111.216269
Customer
High Net
548.6933773 1101.876753
Worth
C
Mass
er
551.3195495 1108.5981
ustom
(blank) 784.5475 1502.138125
Grand Total 551.9944221 1107.836886

8. Analysis by gender
FEMALE
MALE AND
CUSTOMERS
CONTRIBUTE TO EQUAL
AMOUNT OF REVENUE
Gender Revenue %
F 50%
M 48%
U 2%
(blank) 0%
Grand Total 100%

9. Customer demographics
As we can infer from
customers
the graph majority
i.e. 50% of our
come
from the age group
of 34-52.

10. Customer category and RFM score Analysis
So, on the basis of RFM score that we
calculated, the TOP 1
0 PERCENTILE
customers have been classified as
premium customers with RFM Score in
range 78-99.
2nd category of customers is gold. We
have 649 gold customers.(RFM:58-67)
We have 1715 customers under the 3rd
category, that is silver customers.(RFM:
41-57)
we have lowest category of bronze
customer, under which we have 780
customers.

11. DataAnalysis
The table shows that there are 1,715SILVER
customers, out of which 980 are Not Loyal
and 735 are Loyal. There are 780 BRONZE
customers, out of which 767 are Not Loyal
and 1
3 are Loyal. There are 649 GOLD
customers, who are all Not Loyal. There are
348 Platinum customers, who are all Loyal.
it appears that the majority of customers
are SILVER customers, and there are more
Not Loyal customers than Loyal customers.
We can conclude that as there are only a
small number of Loyal
comparison to the total
customers in
number of
customers so the company needs to take
measured steps to retain their existing, new
customers and lapsers

12. Recency
The business has done
extremely well in terms of
recency scoring on an
average
of 85
Frequency
On average The
consumers are not very
frequent scoring on
average only 35 therefore
we need to Target
consumers who
frequently make bike
Monetary
On average The consumers
are not very Spending alot
scoring on average only 35
therefore we need to Target
consumers who have high
disposable income
RS
RFM Analysis

13. CUSTOMER TARGETING
STRATEGY
LaranaInc.

14. Dataanalysis
Analysis shows high net worth and affluent customers are concentrated in NSW and VIC, with property valuation being a
proxy for high disposable income. It is essential to target these customers to increase revenue and profitability and solve the
problem of low monetary customers the business currently faces. Company should Focus on acquiring these customers as
they can potentially provide a very High Customer Life time value .

15. Dataanalysis
Analysis shows that, on average, NSW has the
highest property values in all three customer
segments. The overall average property valuation is
7, indicating that customers in all three segments
and regions own properties with similar values.
However, we observe a higher average property
valuation of 8 for Affluent and Mass Customers in
NSW, and a slightly higher average property
valuation of 8.33 for High Net Worth customers in
NSW. These customers are likely to be Platinum and
Gold customers, with high disposable incomes and
purchasing power.
Therefore, it is recommended that company should
target these customers by offering customized
products and services that cater to their needs and
preferences. By focusing on these high-value
customers, company can increase revenue and
profitability and strengthen its market position.

16. Dataanalysis
By considering the frequency of
customers' bike purchases, we have
plotted a graph where the lower
frequency customers are on the left,
and the high frequency consumers,
who are potential target customers,
are on the right. This provides more
value to our business and solves the
problem of low frequency by
enabling us to focus on these high
frequent buyers. Therefore, we can
target these customers with
personalized products and services,
to increase their engagement and
loyalty, ultimately leading to higher
revenue and profitability.

17. Dataanalysis
From the graph we can see that the average past
3 years bike related purchases for Affluent
Customers, High Net Worth Customers, and Mass
Customers are 50, 51, and 49 respectively. This
suggests that High Net Worth Customers have
made the highest average bike related purchases
in the past 3 years among the three customer
segments.
When considering regions, the table shows that
customers in QLD have made the highest average
past 3 years bike related purchases . From the
property valuation graph we could see that QLD
was giving very insignificant impact in terms of
monetary but in terms
contributing highest i.e.
of frequency
they are one
it is
of the
potential customers for our business.

18. Loyalandvaluablecustomer framework
HIGH MONETARY LOW MONETARY
HIGH
FREQUENCY
LOW
FREQUENCY
MOST
VALUABLE
CUSTOMERS
POTENTIAL
HIGH VALUE
CUSTOMERS
DISCOUN
T
SEEKERS
LOW
VALUE
CUSTOMERS

19. Strategiesfor Loyalandvaluablecustomer framework
To retain our most valuable customers, the high
frequency and high monetary value Titanium
customers, we should provide them with continuous
value by offering personalized selling and high-end
products or services that fulfill their "jobs to be done."
By building strong relationships and gathering
feedback, we can increase their loyalty and ultimately
achieve higher revenue and profitability.
To target potential customers who are high frequency
and low monetary customers, we can offer them
coupons and bundle different products as a package
deal. We can also leverage the network effect in the
bike business to personalize recommendations and
increase their loyalty. By using these strategies, we can
increase revenue and profitability and build strong
relationships with our potential high value customers.
strategy for low frequency and high monetary
customers is a reactivation campaign. This involves
sending personalized messages with exclusive offers
to encourage purchases. For example, offering special
discounts on new products that appeal to their
interests. We could also use targeted advertising to
remind them of our brand and offerings. By focusing
on reactivating these customers, we can increase
engagement and drive revenue for our business.
To understand the reasons behind low
frequency and low monetary customers, it is
important to identify the gaps in the business
that may be preventing them from
purchasing. These customers can provide
valuable insights into areas of improvement
and help address any issues in the business
model.

20. THANK
Y O U
m e e t o u r t ea m
Submitted by:- Tanya agarwal-P221A064. Abhinav Shankar-P221A002. Payal Dagar-P221A039.