1) The document analyzes sales data for the product "Charminar Asbestos Sheet" in the Balasore and Rourkela zones over the current and previous years using descriptive statistics.
2) Key findings include sales increasing in both zones over time but Balasore experiencing higher growth, with sales 8.18% more than Rourkela in the current year.
3) There is opportunity to increase sales by converting more customers to higher sales tiers, as most customers remain in the lowest tier, and understanding customer preferences.
Understanding the brand equity,products and the customers ofvivek gandhi
Indiabulls Real Estate is one of the largest real estate companies in India with projects in Mumbai, Delhi, and Chennai. The presentation analyzes Indiabulls using SWOT, PEST, Porter's 5 Forces, market research techniques, and makes recommendations. Cluster analysis found 5 customer clusters that vary by age, income, and important factors. Factor analysis identified 4 key factors influencing sales. ANOVA showed TV ads were most effective. Regression showed a relationship between factors and past sales. Discriminant analysis found age was the dominant factor in determining customers who may default. Recommendations target specific customer clusters and emphasize quality, pricing, promotions, assistance and location options.
Most riders travel between 2-4pm and 11pm, with those aged 36-45 having the highest average ride durations. Offering discounts to casual riders aged 18-35 (male) and 18-35 and 36-45 (female) during peak times could increase loyalty. The highest proportion of riders are aged 0-17, suggesting an experience-focused demographic. Changing regional sales managers most impacts customer attrition, so reducing such changes is recommended alongside offering discounts to price-sensitive customer segments.
Data mining to improve e-mail marketing Ritu Sarkar
Tayko is a fictitious business which wants to use data mining to improve their email marketing efforts. They are trying different data-mining algorithms to get the best results.
Feasibility of plug & socket report pptRahul Raman
L&T Electrical and Automation conducted research to determine the feasibility of adding plugs and sockets to its product portfolio. The research found that the Chennai market has high annual demand for industrial plugs and sockets, especially in industries, malls, hospitals and metro projects. It was determined that L&T should target these industries and price its products competitively to gain market share from companies like Siemens, ABB and Legrand. The optimal distribution channels identified were through stockists and retailers.
This document analyzes price elasticity through charts and a data set showing the relationship between price and quantity demanded of a product. It summarizes that as price decreases, quantity demanded increases, showing consumer willingness to purchase more at lower prices. The data set adds a summation column for clarity, showing maximum revenue is generated at a quantity of 9 where demand is balanced with price. The analysis advises companies to monitor elasticity in order to maintain profits and market share without damaging demand through excessively high prices.
This document discusses metrics to measure the adoption of a new application and user satisfaction. It examines adoption time, average customer satisfaction, and most used features. Adoption time measures how long it takes users to reach normal efficiency with the new application. User satisfaction is measured through customer satisfaction surveys and ease of use. The document also provides recommendations to improve the user interface and keyboard for greater usability.
Understanding the brand equity,products and the customers ofvivek gandhi
Indiabulls Real Estate is one of the largest real estate companies in India with projects in Mumbai, Delhi, and Chennai. The presentation analyzes Indiabulls using SWOT, PEST, Porter's 5 Forces, market research techniques, and makes recommendations. Cluster analysis found 5 customer clusters that vary by age, income, and important factors. Factor analysis identified 4 key factors influencing sales. ANOVA showed TV ads were most effective. Regression showed a relationship between factors and past sales. Discriminant analysis found age was the dominant factor in determining customers who may default. Recommendations target specific customer clusters and emphasize quality, pricing, promotions, assistance and location options.
Most riders travel between 2-4pm and 11pm, with those aged 36-45 having the highest average ride durations. Offering discounts to casual riders aged 18-35 (male) and 18-35 and 36-45 (female) during peak times could increase loyalty. The highest proportion of riders are aged 0-17, suggesting an experience-focused demographic. Changing regional sales managers most impacts customer attrition, so reducing such changes is recommended alongside offering discounts to price-sensitive customer segments.
Data mining to improve e-mail marketing Ritu Sarkar
Tayko is a fictitious business which wants to use data mining to improve their email marketing efforts. They are trying different data-mining algorithms to get the best results.
Feasibility of plug & socket report pptRahul Raman
L&T Electrical and Automation conducted research to determine the feasibility of adding plugs and sockets to its product portfolio. The research found that the Chennai market has high annual demand for industrial plugs and sockets, especially in industries, malls, hospitals and metro projects. It was determined that L&T should target these industries and price its products competitively to gain market share from companies like Siemens, ABB and Legrand. The optimal distribution channels identified were through stockists and retailers.
This document analyzes price elasticity through charts and a data set showing the relationship between price and quantity demanded of a product. It summarizes that as price decreases, quantity demanded increases, showing consumer willingness to purchase more at lower prices. The data set adds a summation column for clarity, showing maximum revenue is generated at a quantity of 9 where demand is balanced with price. The analysis advises companies to monitor elasticity in order to maintain profits and market share without damaging demand through excessively high prices.
This document discusses metrics to measure the adoption of a new application and user satisfaction. It examines adoption time, average customer satisfaction, and most used features. Adoption time measures how long it takes users to reach normal efficiency with the new application. User satisfaction is measured through customer satisfaction surveys and ease of use. The document also provides recommendations to improve the user interface and keyboard for greater usability.
An AI project : The AIM of the project is to come out with Business Insights on the data provided and Train a Machine Learning model which can predict the success of campaign with highest accuracy percentage.
This document provides an overview of key performance indicators (KPIs) and profitability analysis for software-as-a-service (SaaS) companies. It discusses metrics like monthly recurring revenue, churn, customer lifetime value, customer acquisition cost, and time to profit. Sample data is also presented to illustrate how these KPIs can be calculated and analyzed over time to evaluate the financial health and growth trajectory of a SaaS business.
Improving profitability of campaigns through data scienceswebi
Analyze the campaign results and provide insights and recommendations on :
Which type of customers responded positively to the campaign ?
What can the customer be doing for better future campaign performance ?
How much can be the financial gains of the improved campaign strategies ?
This was part of the solution that we suggested towards SCM & Operations case study competition Marico - Over the wall. However, the idea was not accepted we believe that this will make an impact.
Transactional customers currently make up 25% of A/S's sales. Express could impact A/S in two scenarios: optimistic where all 25% of transactional customers switch to Express, and pessimistic where all transactional (25%) and some relationship (40%) customers switch. This would lead to declines in total sales of 42.1% in the optimistic scenario and 82% in the pessimistic scenario. A/S's suppliers may try to undercut A/S's margins by lowering prices for products on Express. However, suppliers would lose control over demand generation without A/S's sales team. Overall, Express poses more threats as a competitor than opportunities for A/S due to potential loss of customers
A proposed machine learning solution for a Problem statement of a Mall which needs to predict the success of a scheme with all the insights for the business
Tapping into the benefits of next generation store analyticsG3 Communications
The document discusses next generation in-store analytics and how retailers can use data from these systems. It provides examples of key metrics retailers can measure like traffic, conversion rates, dwell time, transaction size, etc. The document also gives examples of how retailers can take action on the data to improve performance in areas like merchandising, marketing and operations. Overall it promotes how next generation store analytics can help retailers optimize performance.
The document discusses how retail energy providers can apply decision science techniques like forecasting, predictive modeling, segmentation, and optimization to improve operations in areas such as demand planning, customer acquisition, loyalty analytics, campaign management, product design, and driving profitability. It provides examples of how these techniques are used to more accurately predict demand, target high value customers, increase customer lifetime value, optimize marketing spend, and reduce costs like bad debt. The goal is to help energy providers better manage risks, increase revenues and margins, and make more informed business decisions.
Marketing Mix Models In a Changing EnvironmentAquent
Marketing Mix Models have been used successfully for years at consumer package goods (CPG) companies to increase their marketing effectiveness and efficiency. The four Ps (Product, Placement, Price, and Promotion) were as far as the models needed to go. Broad–based media was and is very expensive, which kept competition to a minimum. However, the marketing environment has changed in many ways and must be considered when looking to these models to improve marketing performance.
The document summarizes survey findings about small online sellers' perspectives on the upcoming festive season sales in India. It finds that despite recent challenges, small sellers are optimistic about growth during the festive season and expect revenues to increase by at least 15% compared to last year's festive period. Sellers also intend to increase their marketing spending to boost sales. The document also notes that e-commerce platforms are providing more support to sellers for festive season planning and sales are becoming an increasingly important sales channel for small businesses.
This document summarizes the business and growth of DMart, a value retailer in India. It operates predominantly through an ownership model of stores located in densely populated residential areas. Between 2012-2016, DMart's revenues and profits grew at CAGRs of 40% and 54% respectively, with like-for-like growth above 20% each year. This growth has come from increasing its store count and growing sales volumes, not from price inflation. DMart focuses on the essential product categories of food, FMCG, and general merchandise. It aims to sustain its low-price strategy through high operational efficiency from inventory management, a clustered store network, and regional distribution centers. DMart filed plans to use its upcoming IPO
The document discusses strategies for targeting valuable customers based on an analysis of customer data. It finds that high net worth and affluent customers in New South Wales and Victoria have higher property values and spending. It recommends focusing on acquiring these customers to increase revenue. The analysis also shows that customers in Queensland have made the highest average bike purchases over the past 3 years. It suggests targeting high frequency buyers with personalized offers to boost engagement and loyalty. A framework is proposed to retain high value customers and convert potential high value customers through discounts and bundles.
This document provides vocabulary definitions and analysis of promotional data for back-to-school categories in non-food and food/drinks retailers in Romania from July-September 2014 versus the same period in 2013. In non-food, Kaufland and Lidl had the highest promotional pressure while "Desk accessories" saw the largest increase. In food/drinks, private label had the largest share of voice while confectionery/sweets saw a small decline. The document analyzes categories, retailers, and producers in terms of promotional pressure, share of voice, and other key performance indicators.
The document discusses various analytics techniques used in retail decision making including store layout planning, merchandising, assortment optimization, sales forecasting, inventory management, vendor management, loyalty analytics, pricing analysis, promotion optimization, and market basket analysis. The key goal of applying these decision science techniques is to maximize revenue, sales, footfalls, and profitability through optimal allocation of space, inventory, pricing, promotions and understanding of consumer purchasing behavior.
Report_Imports of goods and services Canada(2023).docxmigneshbirdi
Comprehensive Analysis of Imported Goods into Canada in 2023 - Data Acquisition, Analysis, and Visualization
In the project focused on Data Acquisition, Analysis, and Visualization, I undertook an in-depth examination of the goods imported into Canada in the year 2023. The primary objective was to derive valuable insights from the dataset through various statistical and analytical methods.
1. The document summarizes sales performance and targets for various brands and products in 2017 and objectives for 2018. It reports 2017 sales, growth percentages, and highest ever sales for brands like Chaka, Supermom, Senora, etc.
2. Key sales objectives for 2018 include achieving 22% growth, less than 10% LPC, 60% productivity and 75% return on units. The document outlines strategies to achieve these like focusing on high potential brands and products, improving channel coverage, and identifying outlet capacity.
3. A large incentive structure is outlined to motivate sales teams for 2018 with monthly, quarterly and annual incentives for individuals and teams based on sales targets.
Wu-mart's market share and sales of hair products, especially conditioner, have been declining significantly compared to the overall market. Conditioner sales at Wu-mart are being driven by high-end and mid-high products, while sales are decreasing dramatically at the low end where consumers are being lost. Key brands like Pantene and Syoss are underperforming at Wu-mart due to lack of leading SKUs, higher prices, and ineffective promotions compared to the overall market.
Demand planning and inventories strategyLuis Cabrera
Simple technique to do your Demand Forecast and manage your inventories
It involves actual historical sales, Sales personnel, Marketing events planning, and provide you with a number within a range, to be used in you production planning, or your procurement planning. Good Luck. Luis Cabrera
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"sameer shah
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
An AI project : The AIM of the project is to come out with Business Insights on the data provided and Train a Machine Learning model which can predict the success of campaign with highest accuracy percentage.
This document provides an overview of key performance indicators (KPIs) and profitability analysis for software-as-a-service (SaaS) companies. It discusses metrics like monthly recurring revenue, churn, customer lifetime value, customer acquisition cost, and time to profit. Sample data is also presented to illustrate how these KPIs can be calculated and analyzed over time to evaluate the financial health and growth trajectory of a SaaS business.
Improving profitability of campaigns through data scienceswebi
Analyze the campaign results and provide insights and recommendations on :
Which type of customers responded positively to the campaign ?
What can the customer be doing for better future campaign performance ?
How much can be the financial gains of the improved campaign strategies ?
This was part of the solution that we suggested towards SCM & Operations case study competition Marico - Over the wall. However, the idea was not accepted we believe that this will make an impact.
Transactional customers currently make up 25% of A/S's sales. Express could impact A/S in two scenarios: optimistic where all 25% of transactional customers switch to Express, and pessimistic where all transactional (25%) and some relationship (40%) customers switch. This would lead to declines in total sales of 42.1% in the optimistic scenario and 82% in the pessimistic scenario. A/S's suppliers may try to undercut A/S's margins by lowering prices for products on Express. However, suppliers would lose control over demand generation without A/S's sales team. Overall, Express poses more threats as a competitor than opportunities for A/S due to potential loss of customers
A proposed machine learning solution for a Problem statement of a Mall which needs to predict the success of a scheme with all the insights for the business
Tapping into the benefits of next generation store analyticsG3 Communications
The document discusses next generation in-store analytics and how retailers can use data from these systems. It provides examples of key metrics retailers can measure like traffic, conversion rates, dwell time, transaction size, etc. The document also gives examples of how retailers can take action on the data to improve performance in areas like merchandising, marketing and operations. Overall it promotes how next generation store analytics can help retailers optimize performance.
The document discusses how retail energy providers can apply decision science techniques like forecasting, predictive modeling, segmentation, and optimization to improve operations in areas such as demand planning, customer acquisition, loyalty analytics, campaign management, product design, and driving profitability. It provides examples of how these techniques are used to more accurately predict demand, target high value customers, increase customer lifetime value, optimize marketing spend, and reduce costs like bad debt. The goal is to help energy providers better manage risks, increase revenues and margins, and make more informed business decisions.
Marketing Mix Models In a Changing EnvironmentAquent
Marketing Mix Models have been used successfully for years at consumer package goods (CPG) companies to increase their marketing effectiveness and efficiency. The four Ps (Product, Placement, Price, and Promotion) were as far as the models needed to go. Broad–based media was and is very expensive, which kept competition to a minimum. However, the marketing environment has changed in many ways and must be considered when looking to these models to improve marketing performance.
The document summarizes survey findings about small online sellers' perspectives on the upcoming festive season sales in India. It finds that despite recent challenges, small sellers are optimistic about growth during the festive season and expect revenues to increase by at least 15% compared to last year's festive period. Sellers also intend to increase their marketing spending to boost sales. The document also notes that e-commerce platforms are providing more support to sellers for festive season planning and sales are becoming an increasingly important sales channel for small businesses.
This document summarizes the business and growth of DMart, a value retailer in India. It operates predominantly through an ownership model of stores located in densely populated residential areas. Between 2012-2016, DMart's revenues and profits grew at CAGRs of 40% and 54% respectively, with like-for-like growth above 20% each year. This growth has come from increasing its store count and growing sales volumes, not from price inflation. DMart focuses on the essential product categories of food, FMCG, and general merchandise. It aims to sustain its low-price strategy through high operational efficiency from inventory management, a clustered store network, and regional distribution centers. DMart filed plans to use its upcoming IPO
The document discusses strategies for targeting valuable customers based on an analysis of customer data. It finds that high net worth and affluent customers in New South Wales and Victoria have higher property values and spending. It recommends focusing on acquiring these customers to increase revenue. The analysis also shows that customers in Queensland have made the highest average bike purchases over the past 3 years. It suggests targeting high frequency buyers with personalized offers to boost engagement and loyalty. A framework is proposed to retain high value customers and convert potential high value customers through discounts and bundles.
This document provides vocabulary definitions and analysis of promotional data for back-to-school categories in non-food and food/drinks retailers in Romania from July-September 2014 versus the same period in 2013. In non-food, Kaufland and Lidl had the highest promotional pressure while "Desk accessories" saw the largest increase. In food/drinks, private label had the largest share of voice while confectionery/sweets saw a small decline. The document analyzes categories, retailers, and producers in terms of promotional pressure, share of voice, and other key performance indicators.
The document discusses various analytics techniques used in retail decision making including store layout planning, merchandising, assortment optimization, sales forecasting, inventory management, vendor management, loyalty analytics, pricing analysis, promotion optimization, and market basket analysis. The key goal of applying these decision science techniques is to maximize revenue, sales, footfalls, and profitability through optimal allocation of space, inventory, pricing, promotions and understanding of consumer purchasing behavior.
Report_Imports of goods and services Canada(2023).docxmigneshbirdi
Comprehensive Analysis of Imported Goods into Canada in 2023 - Data Acquisition, Analysis, and Visualization
In the project focused on Data Acquisition, Analysis, and Visualization, I undertook an in-depth examination of the goods imported into Canada in the year 2023. The primary objective was to derive valuable insights from the dataset through various statistical and analytical methods.
1. The document summarizes sales performance and targets for various brands and products in 2017 and objectives for 2018. It reports 2017 sales, growth percentages, and highest ever sales for brands like Chaka, Supermom, Senora, etc.
2. Key sales objectives for 2018 include achieving 22% growth, less than 10% LPC, 60% productivity and 75% return on units. The document outlines strategies to achieve these like focusing on high potential brands and products, improving channel coverage, and identifying outlet capacity.
3. A large incentive structure is outlined to motivate sales teams for 2018 with monthly, quarterly and annual incentives for individuals and teams based on sales targets.
Wu-mart's market share and sales of hair products, especially conditioner, have been declining significantly compared to the overall market. Conditioner sales at Wu-mart are being driven by high-end and mid-high products, while sales are decreasing dramatically at the low end where consumers are being lost. Key brands like Pantene and Syoss are underperforming at Wu-mart due to lack of leading SKUs, higher prices, and ineffective promotions compared to the overall market.
Demand planning and inventories strategyLuis Cabrera
Simple technique to do your Demand Forecast and manage your inventories
It involves actual historical sales, Sales personnel, Marketing events planning, and provide you with a number within a range, to be used in you production planning, or your procurement planning. Good Luck. Luis Cabrera
Similar to Assignment on DVADM- Popun Patro.docx (20)
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"sameer shah
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Assignment on DVADM- Popun Patro.docx
1. Name: - Popun Patro
Roll No: - TB21015
Program: - PGCBM-40
Assignment on DVADM
I would like to present my topic on sales analysis of two zones named Balasore and Rourkela and the
company offers product named “Charminar Asbestos Sheet” given below I have placed the
interpretation of result.
Descriptive Statistics is used to provide the large amount of data into manageable form. It helps to
analyses the data, organizes and simplified in the effective way.
I wouldlike to presentbelowthe descriptivestatistcs analysis of Balasore and Rourkela zone for better
understanding of sales trend and will identify the problems and opportunities.
SALES ZONE 1
SALES ANALYSIS OF BALASORE ZONE
Current Year Previous year SHIFT
Mean 143.9244474 116.9262456 26.99820175
Standard Error 31.26652137 31.70738021 -0.440858843
Median 64.7445 28.518 36.2265
Mode 0 0 0
Standard Deviation 333.8350954 338.5421797 -4.707084362
Sample Variance 111445.8709 114610.8074 -3164.94
Kurtosis 76.32363263 77.34843712 -1.024804488
Skewness 8.075631369 8.194791322 -0.119159952
Range 3347.665 3374.788 -27.123
Minimum 0.603 0 0.603
Maximum 3348.268 3374.788 -26.52
Sum 16407.387 13329.592 3077.795
Count 114 114 0
CV 231.95 289.53 57.58
3. Current Year
Bin Frequency Cumulative Frequency
Cumulative
%
99 74 74 64.91%
199 19 93 81.58%
299 8 101 88.60%
399 6 107 93.86%
499 1 108 94.74%
599 3 111 97.37%
699 2 113 99.12%
3348.268 1 114 100.00%
Current Year Histogram
74
19
8
6
1
3 2 1
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
0
10
20
30
40
50
60
70
80
frequency
Bin
Histogram
Frequency
Cumulative %
4. I wouldlike togive the interpretationof resultof salesof “CharminarAsbestossheet”for Balasore Zone.
I wouldlike todescribe the firstmeanisthe centerof the data and average value in data. Median is the
middle value in data and standard deviation is the average observation from the mean.
In the above findings,inthe sale of “CharminarAsbestossheet” on Balasore zone the mean in previous
year is 116.926 and in the current year are 143.924. So the increase in the mean is 26.998. The increase
in the mean leads to increase in standard deviation in previous year is 338.542 and the current year is
333.835. It means a high standard deviation indicates that the data are spread over the large values in
the data. The Median in the previous year is 28.518 and the current value is 64.744. The Median value
has increased and the mode does not appear in this data. Due to the different value in the mean and
medianthenthe distribution indataisnot symmetrical anditisthe skewedtothe left,hence the data is
skewed. Co-efficient of variation always represent the ratio to standard deviation of the mean in the
previousyearco-efficientof variation is 289.534 and in the current year is 231.951. It indicates increase
in co-efficient of variation. Histogram is a graph that indicates the skewness and kurtosis. It is always
used to present the skewness and Kurtosis.
In the salesof Balasore Zone,the skewnessisinthe previousyearis 8.19 andthe currentyearis 8.07 the
difference value is -0.119.It indicatesthatthe data ishighlyskewed.Itshowsthatthe data it is negative
skewed and the distribution the tail is on the left side of the distribution of product and the negative
skewnessindicatesthe salesof Balasore zone were soldmore thanthe average quantity of the product.
The kurtosis is a measure that is used to describe distribution of a product. In the Balasore zone the
kurtosis value in previous year is 77.348 and in the current year 76.323 respectively. The difference
value is-1.024; it indicatesthatthe kurtosishasnegative value.Itindicatesthat the distribution has flat
and thin tails and it is always referred to play kurtosis distribution in the Balasore zone. Hence the
distribution of a product is flat and it has negative value therefore the distribution is flat.
From the above sales analysis of “Charminar Asbestos sheet” on Balasore zone, there is an increase in
23.09% sales of product as compared to the previous year. As the product targeted on rural areas and
companyconverteditssmall customers whosale below99MT in previousyearnow in current year they
startedsellingmore than99MT ina year. Whichevidencesthe frequency distribution of below 99MT in
previousyearis 81 whereasincurrentyearis 78. The frequencydistributionof below 199MT inprevious
year 16 whereas in current year 19. Respectively all bin frequencies shows an increasing trend as
compare to previous year. But still there is a scope of converting customer from 99MT slab to 199MT
slabas out of 114 customers74 numberof customers having sales of below 99MT. It consists of 64.91%
of total customers of Balasore zone. In this case company has to educate the customers about the
productat balasore zone forthe long term and customers to distribute the product in the right area. In
order to increase the sale of the Balasore zone company should understand the preferences of the
customersandaccordinglyshouldbringthe changesinthe product to meet the demands of the people
at the large. The Customers will be able to increase the sale of product and will get return on the
investment in the product.
5. ZONE NO-2
SALES ANALYSIS OF ROURKELA ZONE
Current Year Previous year SHIFT
Mean 133.0401053 112.7739912 20.26611404
Standard Error 31.97621754 25.62903967 6.347177867
Median 59.7415 59.596 0.1455
Mode 0 0 0
Standard Deviation 341.4125769 273.6432621 67.76931477
Sample Variance 116562.5477 74880.63491 41681.91
Kurtosis 87.02785988 78.76586904 8.261990836
Skewness 8.834759579 8.236190536 0.598569043
Range 3515.513 2759.782 755.731
Minimum 0.73 0 0.73
Maximum 3516.243 2759.782 756.461
Sum 15166.572 12856.235 2310.337
Count 114 114 0
CV 256.62 242.65 13.98
Previous Year Sales
Previous Year
Bin Frequency Cumulative Frequency
Cumulative
%
99 81 81 71.05%
199 17 98 85.96%
299 6 104 91.23%
399 6 110 96.49%
499 2 112 98.25%
599 1 113 99.12%
699 0 113 99.12%
2759.782 1 114 100.00%
6. Histogram Previous Year Sales
Current Year Sales
Current Year
Bin Frequency Cumulative Frequency
Cumulative
%
99 73 73 64.04%
199 24 97 85.09%
299 6 103 90.35%
399 7 110 96.49%
499 1 111 97.37%
599 0 111 97.37%
699 2 113 99.12%
3516.243 1 114 100.00%
81
17
6 6
2 1 0 1
71.05%
85.96%
91.23%
96.49% 98.25% 99.12% 99.12% 100.00%
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
0
10
20
30
40
50
60
70
80
90
Frequency
Bin
Histogram
Frequency
Cumulative
%
7. Histogram Current Year
I wouldlike togive the interpretationof resultof salesof “CharminarAsbestossheet” on Rourkela zone
and the problemoccurredforthe limitedsalesvolume formostof the customer.Iwouldlike todescribe
the first mean is the center of the data and in the previous year mean is 112.77 and the current year is
133.04. In this case the mean has increased by 20.266 and the median in previous year is 59.596 and in
the current year is 59.7415. Hence the median value has increased little more. The mode does not
appear in the data it indicates the values does not occur most frequently in the data of Rourkela zone
sales and the standard deviation in the previous year is 273.643 and the current year is 341.412. The
increase instandarddeviationitindicatesthe average distance fromthe mean it is getting increase and
the values are more spread and the co-efficient of variation in the previous year is 242.647 and the
current year is 256.623. An increase in co-efficient of variation means co-efficient of variance is to be
high variance and it is always dispersion of data around the mean and the skewness in the data in
Rourkeal zone sales the previous year is 8.236 and in the current year is 8.834. Hence the difference
value ispositive value0.59.A large positive value forkurtosis indicates that the tails of the distribution
are longer than those of a normal distribution. In the previous year the kurtosis value is 78.76 and the
current value is 87.02. The difference in kurtosis value is positive 8.261.
73
24
6 7
1 0 2 1
64.04%
85.09%
90.35%
96.49% 97.37% 97.37% 99.12% 100.00%
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
0
10
20
30
40
50
60
70
80
Frequency
Bin
Histogram
Frequency
Cumulative
%
8. From the above sales analysis of Rourkela zone, there is a 17.97% sales growth shown as compared to
the previousyear.Asthe governmentinRourkelazone givenapprovalfornew poultry projects so there
is an increase in demand shown for “Charminar Asbestos sheet” with sales growth. As the product is
verymuch targetingrural customerssothe frequencyof distributionbelow 99MT ismore as compare to
othersalestarget. The biggestchallenge for company is to find out a customer who can sale more than
99MT in a year for the Rourkela zone. Hear out of 114 customers only 41 customer able to sale more
than 99MT. In orderto increase the sale of the Rourkela zone product which is very much good for the
rural customers and poultry farm, so company should maintain the proper demand analysis at the
factory site for the production of the product which will enable the customer to make the product
available to the large audience. This will result good increase in the percentage of the sales of the
Rourkeal zone and also increase the sales volume frequency with profitability. This sample data has
helpedthe company to understand the market situation and how to deal with customers in upcoming
year.
Balasore Zone Total
Sales
Rourkela zone Total
Sales
Current Year Current Year % Change
16407.387 15166.572 8.18%
Balasore Zone Total Sales Rourkela zone Total Sales
Previous Year Previous Year % Change
13329.592 12856.235 3.68%
When we compare two sales zone Balasore & Rourkela both zones have increasing sales trend but
balasore zone ismore successful as compare to Rourkela zone. Balasore zone having 3.68% more sales
in previous year as compare to Rourkela zone whereas in current year 8.18% more sales in Balasore
zone as compare to Rourkelazone.Sothere is a serious concern for company for Rourkela zone. So the
salesanalysisdataat Balasore zone alsohelpfulforRourkelazone forbetterimprovementof the salesin
future for company to sustain in market.