Mastery Journal @monicasribeiro-blog - Tumblr Blog

Data Mining

This also looks at the number of customers in your market and predicts how many will actually buy. For example, imagine if you have a coffee shop in Seattle. Here are questions you might ask:· How many people/households/businesses within a mile of your store will buy your coffee?· How many competitors are in that mile?· How many people/households/businesses in 5 miles?· How many competitors in those 5 miles?Take away: When it comes to forecasting sales, create three cash flow projections: realistic, optimistic and pessimistic. This way you can plan to have the right amount of capital on hand to endure the worst situation possible if sales don’t go as planned.3. Database MarketingBy examining customer purchasing patterns and looking at the demographics and psychographics of customers to build profiles, you can create products that will sell themselves.Of course for a marketer to get any value out of a database, it must continue to grow and evolve. You feed database information from sales, surveys, subscriptions and questionnaires. And then you target customers based upon this intelligence.Take away: Database marketing begins with collecting information. For example, if you owned a coffee shop, your database might consist of these things:Data Mining

This month was very Important, Data Mining takes a big part today and the future. Many still have much to learn the different techniques on how to frame it and collect the right Data. Fraud is also very important because collecting the correct Data, detects fraud on time.

Data Mining History and Current Advances

The process of digging through data to discover hidden connections and predict future trends has a long history. Sometimes referred to as "knowledge discovery in databases," the term "data mining" wasn’t coined until the 1990s. But its foundation comprises three intertwined scientific disciplines: statistics (the numeric study of data relationships), artificial intelligence (human-like intelligence displayed by software and/or machines) and machine learning (algorithms that can learn from data to make predictions). What was old is new again, as data mining technology keeps evolving to keep pace with the limitless potential of big data and affordable computing power.

Over the last decade, advances in processing power and speed have enabled us to move beyond manual, tedious and time-consuming practices to quick, easy and automated data analysis. The more complex the data sets collected, the more potential there is to uncover relevant insights. Retailers, banks, manufacturers, telecommunications providers and insurers, among others, are using data mining to discover relationships among everything from pricing, promotions and demographics to how the economy, risk, competition and social media are affecting their business models, revenues, operations and customer relationships.

10 Ways Data Mining Can Help You Get a Competitive Edge

Far too many companies that I consult with sit on loads of good customer data…and do nothing with it. It’s truly amazing, because in that data is a gold mine of insight.

Insight that can:

· Increase customer loyalty

· Unlock hidden profitability

· Reduce client churn

Are you sitting on loads of data that you aren’t using? Would you like to learn how you can use it? Here are the ten most common ways, with some practical advice on how to use each.

1. Basket Analysis

Sometimes called “affinity analysis,” this looks at the items that a customer bought, which could help brick-and-motar stores improve their layouts or online companies like Amazon recommend related products. The “basket” refers to what shoppers use when they are shopping.

It’s based on the assumption that you can predict future customer behavior by past performance, including purchases and preferences. And it’s not just grocery stores that can use this data. Here are a few ways it can be applied in various industries:

· Evaluating use of credit cards. (especially important for online ecommerce). Typically, professionals mine credit card data to find patterns that might suggest fraud, but the data is also used to tailor cards around a variation of credit limits, terms and interest rates…and even collect debt.

· Evaluating patterns of telephone use. For instance, you could discover customers who adopt all of the latest services and features your phone company offers…suggesting they will need something new to stick around…and then offer them an incentive to stay another year.

· Identifying fraud insurance claims. Through the mining of historical information, insurance companies can spot claims with a high percentage of recovering money lost through fraud and develop rules to help them flag future fraudulent claims.

And all the products don’t have to be purchased at the same time. Most customer analytic tools can observe purchases over time, thus helping you spot trends or opportunities that you can test for future promotions.

Take away: Look at your purchase data with an eye for patterns. Do you see people who buy item X also buy Y? Which item did they buy first? Why? Could you encourage people to buy X,Y and Z, thus boosting point-of-purchase sales?

2. Sales Forecasting

This looks at when customers bought, and tries to predict when they will buy again. You could use this type of analysis to determine a strategy of planned obsolescence or figure out complimentary products to sell.

This also looks at the number of customers in your market and predicts how many will actually buy. For example, imagine if you have a coffee shop in Seattle. Here are questions you might ask:

· How many people/households/businesses within a mile of your store will buy your coffee?

· How many competitors are in that mile?

· How many people/households/businesses in 5 miles?

· How many competitors in those 5 miles?

Take away: When it comes to forecasting sales, create three cash flow projections: realistic, optimistic and pessimistic. This way you can plan to have the right amount of capital on hand to endure the worst situation possible if sales don’t go as planned.

3. Database Marketing

By examining customer purchasing patterns and looking at the demographics and psychographics of customers to build profiles, you can create products that will sell themselves.

Of course for a marketer to get any value out of a database, it must continue to grow and evolve. You feed database information from sales, surveys, subscriptions and questionnaires. And then you target customers based upon this intelligence.

Take away: Database marketing begins with collecting information. For example, if you owned a coffee shop, your database might consist of these things:

· Purchase records stored via a club card that you offer via incentives like 5% off purchases or accumulation of points.

· Contests you run to collect additional information about where people live.

· Email newsletter you use to update customers weekly, but also to send out surveys in which you collect additional information concerning new products and promotions.

· Twitter account that doubles as a flash promotion tool and customer service hub where you listen to the good and bad of what your followers are saying…and then respond.

As you collect this data, start to look for opportunities like best days to run a discount promotion. Ask yourself: Who are your local customers and how you can turn these customers in advocates for your store?

4. Merchandise Planning

This is helpful for offline or online companies. For the offline, a company looking to grow by adding stores can evaluate the amount of merchandise they will need by looking at the exact layout of a current store. For an online business, merchandise planning can help you determine stocking options and inventory warehousing.

The right approach will lead to answers that can help you decide what to do with:

· Inventory getting old – Merchandising planning can be as easy as updating a PDF white paper to be current or stocking up-to-date accessories for products.

· Selecting product – Mining your database will help you determine which products customers want, which should include intelligence on your competitors merchandise.

· Balancing your stock – Database mining can also help you determine the right amount of stock…not too much or too little…throughout the year and buying seasons.

· Pricing – Database mining can also help you determine the best price for your products as you uncover customer sensitivity.

Take away: Ignoring this database strategy can lead to poor performance in terms of production and customer service/experience. If you can’t handle typical runs on a product, in-store expectations aren’t met or your price doesn’t match the market, customers will jump ship and go to your competitors.

5. Card Marketing

If your business involves issuing credit cards, you can collect the information from usage, identify customer segments and then based on information on these segments build programs that improve retention, boost acquisition, target products to develop and design prices.

A great example of this occurred when the UN decided to issue a Visa credit card to people who traveled overseas frequently. The agency marketers segmented their database into wealthy travelers—30,000 people in high-income households.

The agency marketers used direct mail for their appeals and generated a 3% response. That may sound small, but it actually exceeded industry standards. Large financial institutions typically see 0.5% response rates. That’s how effective databases can be when marketing cards.

Take away: Of course there are costs built into issuing credit cards that most companies can’t absorb, but if you can…do it. Analyzing customer buying patterns based on their credit card habits will give you insights into behavior that can lead to promotions and programs that will result in higher revenues and better customer loyalty.

6. Call Detail Record Analysis

If your company depends upon telecommunications, then you can mine that incoming data to see use patterns, build customer profiles from these patterns and then construct a tiered pricing structure to maximize profit. Or you could build promotions that reflect your data.

A China mobile operator with about 600,000 customers wanted to analyze their data to create offerings to fend off competition. The first thing the project team behind collecting and analyzing the data did was create an index to describe caller behavior. That index then clustered the callers into 15 segments based on elements like this:

· Minutes Of Usage per user on the average

· Local call percentage

· Long distance call percentage

· IP call percentage

· Roam percentage

· Idle period local call percentage

· Idle period long distance call percentage

· Idle period roam call percentage

From that data the marketing department then created strategies directed at each segment, namely improving customer satisfaction, delivering quality SMS service for another group and encouraging another group to use more minutes.

Take away: Whether it’s based upon mobile user data or customer service calls, dive into the data available in call detail records to look for ways to improve current service, promotion opportunities or ways to shorten time on call.

7. Customer Loyalty

In a world where price wars occur, you will get customers jumping ship every time a competitor offers lower prices. You can use data mining to help minimize this churn, especially with social media.

Spigit uses different data mining techniques from your social media audience to help you acquire and retain more customers. Their programs include:

· Employee innovation – A tool used to ask employees for their ideas on how to improve customer engagement, product development and future growth. Who says data mining is always customer-centric?

· Facebook – Through a technique called “customer cluster” Spigit uses data from your audience on Facebook to generate ideas for improving your brand, satisfying more customers and increasing loyalty.

· what’s below you when you fly.” Then people are shown these ideas and vote. Naturally this allows a company to find ideas that are coming from customers…and then being voted on by people who might be interested in the final idea.

Take away: Focusing on numbers like Lifetime Customer Value when mining data can help you improve your acquisition costs, but it can also help you identify reasons why customers bail. This is where a combination of tactics may come in handy because your data will probably only tell you where they are falling off. You’ll have to pull some surveys and questionnaires to build a case on why.

8. Market Segmentation

One of the best uses of data mining is to segment your customers. And it’s pretty simple. From your data you can break down your market into meaningful segments like age, income, occupation or gender. And this works whether you are running email marketing campaigns or SEO strategies.

Segmentation can also help you understand your competition. This insight alone will help you identify that the usual suspects are not the only ones targeting the same customer money as you are.

This is especially important, because when I ask most clients who their competitors are they give me a list of people. I then hand them back a bigger list. Most businesses need to expand their circle of competitors out two or three times if they plan on competing effectively. Data mining will help you do that.

Take away: Segmenting your database can improve your conversion rates as you focus your promotions on a tight, highly-interested market. And it can also help you understand who your competitors are in each of those segments, allowing you to customize products and promotions that satisfy the needs of that audience in a way a generic, broad promotion never will.

9. Product Production

Data mining is also perfect for creating custom products designed for market segments. In fact, you can predict which features users may want…although truly innovative products are not created from giving customers what they want.

Rather truly innovative products are created when you look at the data from your customers and spot holes customers are demanding be filled. When it comes to creating that product, these are the elements that must be baked into the product.

· Fulfill an obvious need

· Offer something utterly unique

· Set to enter the market with a unique name

· Attractive design

· Serves a broad market

· Can be sold in generations

· Create an impulse-purchase price

· Cost to make is low enough to make a profit

Take away: The most innovative companies never start with a product. They start with a pain point they’ve uncovered from mining data…and then build a minimum viable product that will solve that problem in a way the customer never imagined. Do this and you will easily be ahead of 90% of your competitors.

10. Warranties

Finally, database mining will allow you to predict how many people will actually cash in on the warranty you’ve set up. This is also true for guarantees.

For example, I tested the pulling power that a guarantee has for improving sales on a test I ran on QuickSprout. But before I ran the test I had to analyze data to see how many people would actually return the product I was selling. I looked at previous data on these two sets:

· Net sales

· Settlements made within the defined guarantee

I gathered those two numbers over several different sales sets to predict how many people would cash in on the guarantee…and then adjusted the guarantee amount so as not to lose money when people returned product.

These calculations are typically more robust for large corporations, but for smaller shops you don’t need anything more complicated than that.

Takeaway: One of best ways to creating a successful guarantee is to look at the data of past guarantees, sales and profits. Doing so may lead you to offer a 110% money-back guarantee to get an edge over competition.

Conclusion

The more data you collect from customers…the more value you can deliver to them. And the more value you can deliver to them…the more revenue you can generate.

Data mining is what will help you do that. So, if you are sitting on loads of customer data and not doing anything with it…I want to encourage you to make a plan to start diving into it this week. Do it yourself or hire someone else…whatever it takes. Your bottom line will thank you.

Also, would like to thank Instructor Michael Taylor for his time and help.

Great month of class!

Monica Ribeiro

Reference

www.sas.com. (n.d.). What is data mining? Retrieved October 21, 2018, from https://www.sas.com/en_us/insights/analytics/data-mining.html

Neilpatel.com. (2018, July 10). 10 Ways Data Mining Can Help You Get a Competitive Edge. Retrieved October 21, 2018, from https://neilpatel.com/blog/data-mining/

Business Intelligence Analytics

Business Analytics relates to the exploration of historical data from many source systems through statistical analysis, quantitative analysis, data mining, predictive modelling and other technologies and techniques to identify trends and understand the information that can drive business change and support sustained successful business practices.

For this past Month the discussion was Maruti Suzuki and collecting data for more improvement. I think is important to know the background and the up and downs of the company you trying to help succeed. Math is no my major, but it can help come up with some good information that can change any company. Only the future can tell what hold Maruti Suzuki, but I can tell will be successful. Also want to thank my Instructor Philip Arlen for his help during this month of class.

Thanks for reading!

Monica Ribeiro

Reference

www.betterbuys.com. (2017, July 24). Business Intelligence vs. Business Analytics: What's The Difference? Retrieved September 23, 2018, from https://www.betterbuys.com/bi/business-intelligence-vs-business-analytics/

Forecast and Prediction/Capstone Update Maruti Suzuki in India By:Monica Ribeiro

Forecast Analysis – At Maruti Suzuki in India, the rural areas are a concern. Because it hard for customer to get to our dealership that are located major cities we have implemented an idea that will help the customers get to us. We have provided dealerships around the rural areas that will bring the company more capital over time and have implemented mechanic assistance is they can’t get to us. This idea will bring more capital.

3,000 local villagers were nominated as resident dealer sales executives of Maruti Suzuki to promote the products. They were supported by over 186 extension counters.

Maruti Suzuki even tried to influence the opinion leaders of the village (like Sarpanch) by taking them for factory visits, conducting detailed profiling, their consumption patterns and their choices

The automaker aggressively marketed the brand at rural sporting events to sales fairs (Grameen Mahotsavs) to SMS campaigns for Gram Panchayat Members

Recently, Maruti Suzuki has started Video on Wheels campaign in which the villagers get to see the screening of Maruti Suzuki ads while sitting in an air-conditioned environment created in the back of a truck.

Smartly, the automaker is not just spending marketing rupees on rural people with low per capital income. Here’s an interesting snapshot of the kind of people that Maruti Suzuki is selling to

1. Orange farmers in Nagpur

2. Turmeric growers in Tiruchengode, Tamil Nadu

3. Granite polishers in Hyderabad

4. Blue pottery makers in Jaipur

5. Madhubani painters in Madhubani, Bihar

6. Potato growers in West Bengal

7. Apple and fruit growers in Himachal Pradesh

8. Fishermen in Howrah

9. Alphonso mango growers in Ratnagiri

As you can see these are not farmers struggling to make a livelihood. These are well settled villagers who have the purchasing power to buy a car for their daily needs.

And in the future…

The rural market is a relatively untapped area for automakers. Maruti Suzuki plans to double the number of its outlets in rural India from the present 231 to around 450 in the next two years. Rural outlets will account for nearly 50 per cent of Maruti’s network (550 will be located in urban centers) compared with just around 35 per cent now. It plans sale centers in all towns with a population of over 50,000 people by 2015.

2.Risk Avoidance – The rural areas give much growth, if Maruti doesn’t work more to help the rural areas it can hurt the company in the long run. The rural areas give the company 35% to 50% of sales.

Car market leader Maruti Suzuki India Ltd, two-wheeler maker Hero Moto Corp Ltd and tractor maker Mahindra and Mahindra Ltd generate about 35 of their sales from rural areas. That means we can lose up to 35% of revenue.

Example: in a month basis if the dealership sold 1500 units .

525/1500 x 100=35%

975/1500 x 100=65%

If Maruti loses the rural areas it will loose 35% its business and that damage the company.

3.Total Quality Control (TQC) – Deming's 14 points give us much to think about. To improve TQC we must have no fear, drive out fear, continue to improve, training on the job to continue to give customer satisfaction, be the leader not a fallower in our industry, create a purpose for improvement and we must involve all workers for transformation of the much more excellence to our value customer this will lead to success.

4.Six Sigma – Quality is job 1,” today they have demonstrated that making product quality a high priority is more than just a slogan, it is critical to the organization’s operations and long-term growth. Maruti Suzuki India Ltd created a quality equals profitability equation stating that improving quality increases customer satisfaction which leads to an increase in customer loyalty. An increase in customer loyalty increases Maruti Suzuki India Ltd, sales revenues by the billions and profits by hundreds of millions.

Six Sigma

5.Process Analysis

6. Conclusion

All this Month we have studied Maruti Suzuki and yet many things can change in the future. After much research its proven that overseas will bring much more capital. Also, that a rural area was a major target since it brings almost 35% to 50% customers, included there is now a program that will reach much of the rural areas with the help of a mobile mechanics that can help those areas. Helping that area can only benefit the dealership. Maruti has 50% of the market and growing. Keeping the prices affordable from the rest of the competition is the goal. The future hold much more to Maruti and we will make history.

References

www.americannursetoday.com. (2017, June 13). The power of Lean Six Sigma. Retrieved September 23, 2018, from https://www.americannursetoday.com/power-lean-six-sigma/

Asq.org. (n.d.). W. Edwards Deming's 14 Points for Total Quality Management. Retrieved September 23, 2018, from http://asq.org/learn-about-quality/total-quality-management/overview/deming-points.html

Kotecha, A., & Ghosh, M. (2018, April 10). India's automobile industry sees rural India driving sales in 2018-19. Retrieved September 23, 2018, from https://www.livemint.com/Industry/6DWdmeUSV4s28eYSZs50rJ/Indias-automobile-industry-sees-rural-India-driving-sales-i.html

Smartsheet.com. (2018, July 26). Supply Chain Management: Principles, Examples & Templates. Retrieved September 23, 2018, from https://www.smartsheet.com/supply-chain-management

Decision Making at CEO Level For Maruti Suzuki By:Monica Ribeiro

1.Growth Analysis – At Maruti Suzuki there are several locations all over the country. Also lease and the dealership is trying to expand overseas. By consumer demand our vehicles are in high demand. There are many competitors in this market, but the price is just right. We also have a new program called Mobile Mechanics on duty, this separates us from the rest. The demand will continue because our prices are the lowest in the market. To say how long the prices, change, it depends on the market. If there is failure the dealership will have to adjust and in valuate the situation. As you can see Maruti Suzuki stand out by 49% of the market share. This chart concludes that the vehicles prices and sales from competitors Maruti wins the competition.

2. Personnel Analysis – The long-term strategy in to give training to our personal and provide bonus to motivate the personal. In case of layoffs we are ready because there is a budget in place in case the economy crashes. There is no need to hire because the confidence of the staffed personal is very high and been here for years. The managers are given bonus at the end of the year to compensate for their hard work. The production line is strong and if there is need for more we have many locations that can provide the product.

3. Operation Analysis – Maruti Suzuki has a well-organized plan that provides us much information that helps making smart decisions. The customer is our priority, for finance making the price just right not just for them but analyzing the competition to give the customer the best.

4. Cash Flow Analysis – The cash flow problems are handled by many stock holders and existing credit line. If there is to be a problem the credit line and shareholders will help with that problem, that’s how the company obtains financial backing.

5. Sales Analysis -At Maruti Suzuki pricing, distribution, purchasing, and suppliers are the main areas. The main goal is to try to beat the market by pricing our vehicles affordably. Have the vehicles distributed on time for our valuable customers. The company has sold many vehicles over the world and yes, we should expand overseas.

6. Risk Analysis – Risk Analysis of Maruti Suzuki India Limited

"The Risk Score is a relevant measure for the assessment of a stock attractiveness. Maruti Suzuki India Limited shows a Risk Score of 9.00. 0 corresponds to a very high risk and 10 corresponds to a very low risk." The Risk Score for Maruti Suzuki India Limited is significantly higher than its peer group's. This means that Maruti Suzuki India Limited is significantly less risky than its peer group.

References

hypestat.com. (n.d.). Mymotorwheels.Wordpress. Com - Info. Retrieved September 16, 2018, from https://hypestat.com/info/mymotorwheels.wordpress.com

Ali, M. (n.d.). BP.BLOGSPOT.COM. Retrieved September 16, 2018, from https://2.bp.blogspot.com/-ydbQRe11HWo/UTceiUVSsaI/AAAAAAAAAJI/ofgaXPZgdZw/s1600/Personnel_management.jpg

Analytics, I. (n.d.). Maruti Suzuki India Limited (Formerly Maruti Udyog Limited). Retrieved September 16, 2018, from https://www.infrontanalytics.com/fe-EN/30835FI/Maruti-Suzuki-India-Limited/gprv-risk

Www.seair.co.in. (n.d.). ViewBag.Productnames. Retrieved September 16, 2018, from https://www.seair.co.in/product-export-data/maruti-suzuki-export-data.aspx#

Qstreetcs.com. (n.d.). Operations Analysis. Retrieved September 16, 2018, from https://qstreetcs.com/our-services/operations-analysis/

Www.ndtv.com. (n.d.). Maruti Suzuki India Ltd. Retrieved September 16, 2018, from https://www.ndtv.com/business/stock/maruti-suzuki-india-ltd_maruti/financials-cash-flow

Bayesian Analysis

Maruti Suzuki India

By:Monica Ribeiro

1. Promotional Event

At Maruti Suzuki India the dealership we are thinking of studding a marketing analysis on a promotional event which will indicate how many males and females are satisfied with our customer satisfaction rate. For that reason, we will study which customer type are buying by gender, and who wins men or woman in satisfaction of the buying process. Why we are doing this is because that way we can satisfy customer needs by having the right vehicle is stock.

2.Target Customers

My target pool is toward the gender female or male and how happy are they with buying a vehicle in this case who wins are the male by potential customer. We plan to contact them directly and mail them offers to bring them back and finalize a sale. The cost can vary between $2000 to $4000 dollars. The cost will be justified when we sale them the vehicle.

3. Selected Sampling

A) The probability that the customers is a woman or male

P=60/124=0.483

B) The probably that the potential customer is a woman

P=23/124=0.185

4. Lottery Analysis

A) Loyal Customers

P=15/124=0.129

B) Potential Customers

P=58/124=0.467

C) New Consumers

P=30/124=0.241

D) Dissatisfied customer

P=15/124=0.120

In this analysis the Potential Customers have a better chance to win with a .467%.

5. Bayesian Analysis

Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability.

6. Expansion Recommendation

Based on our analyses in Maruti Suzuki India the data above and given the test data, in our dealership, we should expand to India. Our focus should be on the client satisfaction and needs. Especially the ones in rural areas. We do have potential here in India since is a strong market. We must do what’s necessary to bring in more customers and have them also communicate to friends and family their success story here.

References:

Bayesian inference. (2018, September 06). Retrieved September 9, 2018, from https://en.wikipedia.org/wiki/Bayesian_inference#Bayesian_inference

#Bayesian Analysis

Market Analysis Company: Maruti Suzuki India By: Monica Ribeiro

INTRODUCTION

The automotive industry in India is one of the largest in the world with an annual production of 23.96 million vehicles in FY (fiscal year) 2015–16, following a growth of 2.57 per cent over the last year. The automobile industry accounts for 7.1 per cent of the country's gross domestic product (GDP). The Two Wheelers segment, with 81 per cent market share, is the leader of the Indian Automobile market, owing to a growing middle class and a young population. Moreover, the growing interest of companies in exploring the rural markets further aided the growth of the sector. The overall Passenger Vehicle (PV) segment has 13 per cent market share.

India is also a prominent auto exporter and has strong export growth expectations for the near future. In FY 2014–15, automobile exports grew by 15 per cent over the last year. In addition, several initiatives by the Government of India and the major automobile players in the Indian market are expected to make India a leader in the Two Wheeler (2W) and Four Wheeler (4W) market in the world by 2020.[1]

1.Company Profile

Maruti Suzuki India Limited (MSIL), formerly known as Maruti Udyog Limited, a subsidiary of Suzuki Motor Corporation of Japan, is India's largest passenger car company, accounting for over 50 per cent of the domestic car market. Maruti Udyog Limited was incorporated in 1981 under the provisions of Indian Companies Act 1956 and the government of India selected Suzuki Motor Corporation as the joint venture partner for the company. In 1982 a JV was signed between Government of India and Suzuki Motor Corporation

More than half the number of cars sold in India wear a Maruti Suzuki badge. They are a subsidiary of Suzuki Motor Corporation Japan. The company offer full range of cars– from entry level Maruti 800 & Alto to stylish hatchback Ritz, A star, Swift, Wagon R, Estillo and sedans DZire, SX4 and Sports Utility Vehicle Grand Vitara.

MSIL’s parent company, Suzuki Motor Corporation, has been a global leader in mini and compact cars for three decades. Suzuki's technical superiority lies in its ability to pack power and performance into a compact, lightweight engine that is clean and fuel efficient. The same characteristics make their cars extremely relevant to Indian customers and Indian conditions. Product quality, safety and cost consciousness are embedded into their manufacturing process, which they have inherited from their parent company.

This product market is high within India. but company originated from japan.

2.Expansion Analysis

India is a very big country, but the rural areas like Raigad where less than 10,000 people live, trying to buy a car becomes hard for them. The city Mumbai is 100 miles away and becomes hard for them to travel. The problem is not the buying process is when the vehicle is purchased it needs service and traveling is a time consuming and hard for the buyer. The best way is to come up with an area close by that twill offer mobile mechanics. These mechanics or specialist will come to the buyer in case they need help with the vehicle. By adding this feature to the dealership, we can attract more buyers.

3.Product/Service Analysis

The best way is to come up with an area to help rural areas close by capital that will offer mobile mechanics. At least half way between the dealership and area to target, in this case the rural areas. These mechanics or specialist will come to the buyer in case they need help with the vehicle. By adding this feature and service to the dealership, we can attract more buyers and have better chance against the other competitors.

4. Marketing Data Flow Diagram

5. Quantitative Analysis

The graph below will explain what will happen by implementing Mobile mechanic service by 2020. As 2018 our sales are taking the market by 50% of our competitors, our goal is to increase our sales by 25% by 2020. Implementing a service that no one has as of yet to serve the rural areas will give us many more new clients. With this new service in our dealership we can make it happen.

6. Target Area

Maruti Suzuki will target the Mumbai urban area with Mobile Mechanic assistance as a test to the Maruti Suzuki dealership. And we will collect the data to see how customers like the new service we have to offer. This service can only help these areas. This good example will be different front the rest of the auto industry in the area. Below is a map of the areas we will help locate the area.

Mumbai urban areas

References

Www.quora.com. (n.d.). Is Maruti Suzuki now an Indian company if Suzuki has 56% share in the company? Retrieved September 2, 2018, from https://www.quora.com/Is-Maruti-Suzuki-now-an-Indian-company-if-Suzuki-has-56-share-in-the-company

En.wikipedia.org. (2018, August 30). Automotive industry in India. Retrieved September 2, 2018, from https://en.wikipedia.org/wiki/Automotive_industry_in_IndiaEn.wikipedia.org. (2018, August 30). Automotive industry in India. Retrieved September 2, 2018, from https://en.wikipedia.org/wiki/Automotive_industry_in_India

Map- www.newgeography.com. (n.d.). World Urban Areas: 1,064 Largest Cities: 2018 Update. Retrieved September 2, 2018, from http://www.newgeography.com/content/005933-world-urban-areas-1064-largest-cities-2018-update

#school assignment #market analysis

monicasribeiro-blog

Business Intelligence Technology

Business Intelligence Technology this month wasn’t easy. Understanding data is not easy, but knowing your organization is key to include the right data. Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help executives, managers and other corporate end users make informed business decisions. BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources; prepare it for analysis; develop and run queries against that data; and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers. I would like to thank Instructor Michael Taylor for taking the time to help me through this month of class. There many things to learn and I’m pressing forward.

Reference

Searchbusinessanalytics. (n.d.). What is business intelligence (BI)? - Definition from WhatIs.com. Retrieved August 26, 2018, from https://searchbusinessanalytics.techtarget.com/definition/business-intelligence-BI

Business Intelligence Technology

Reference

#Business Intelligence Technology

Enterprise Data Management

This Month of class was not easy, there much to say and learn about data. Data is a word that is used in many times. For any to run a successful business we must know about Data management, what it does and what is needed.

Data management is the practice of organizing and maintaining data processes to meet ongoing information lifecycle needs. Emphasis on data management began with the electronics era of data processing, but data management methods have roots in accounting, statistics, logistical planning and other disciplines that predate the emergence of corporate computing in the mid-20th century.

As data technologies have expanded, the purview of data management has expanded in turn. Increasing volumes of data and real-time processing of data have ushered in such data frameworks as Hadoop and Spark. The variety of data has grown as well. Unstructured data types have complicated data modeling procedures and ushered in an assortment of databases that do not use SQL, the structured query language closely associated with the use of relational databases. Collectively, the new technologies have come under the banner of big data. Analyst group Gartner has listed in-database analytics, event stream processing, graph databases, key-value stores and distributed ledgers as just some of the data management technologies to watch going forward.

Reference:

Searchdatamanagement.techtarget.com. (n.d.). What is data management? - Definition from WhatIs.com. Retrieved May 27, 2018, from https://searchdatamanagement.techtarget.com/definition/data-management

Thanks for reading!

Foundations of Business Intelligence

BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources; prepare it for analysis; develop and run queries against that data; and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers.

Foundations of Business Intelligence course helped me understand that in today’s world this tool is very important. Knowing that there is a way to manage your business without going bankrupt and lost. Business intelligence is there to help us understand that there is a way to run your business on the right path. What I learned during this month of class is that we shouldn’t be so scared about DATA, data is everywhere, and we can’t digest it all, but BI can help us. BI can guide us to be successful, but we must understand how it works and what it does.

The potential benefits of business intelligence tools include accelerating and improving decision-making, optimizing internal business processes, increasing operational efficiency, driving new revenues and gaining competitive advantage over business rivals. BI systems can also help companies identify market trends and spot business problems that need to be addressed.

Before I finish, I would like to thank my professor Ramos at Full Sail University for this month of class and the time and help he dedicated to all of us.

Reference:

Craig Stedman and Ed Burns. (n.d.). What is business intelligence (BI)? - Definition from WhatIs.com. Retrieved April 29, 2018, fromhttps://searchbusinessanalytics.techtarget.com/definition/business-intelligence-BI

Week 4_Mastery Timeline_Assignment

#Business

Mastery Journal Logo

#Inspiration

Feedly

https://papaly.com/6/5BKV

My Linkedin Profile

Linkedin.com

Mastery Journey

In the next 12 months of class in my Mastery Journey my goal will be to learn as much as possible. Stay focused, positive and don’t let the pitfalls take the best out of me. Being a master of anything will take time and practice. I will need to stay positive and remember that the way to success also includes setbacks, but learn from it and get back on track. Mastery requires patience and understanding about your subject why you are here and how can I enforce it to go forward not backwards. Life has thought me a big deal of things, I have fallen behind and have learned to get back on track. I think that having a better understanding what a Master is will help me along my journey here at Full Sail and apply it when I open my own business in the near future. My inspiration for all this will be my mom and husband, they all are hard workers, and nothing happens or comes easy. My mother is one of them, she started a business with my help out of nothing years ago and now she’s feels content and her life is stabled. All this came with hard work, up and downs, setbacks but she didn’t get discouraged and this all helps us do better. We never stop learning we live in a very fast paced world with many changes, but as time passes we learn and adapt to new things. We must believe, love and trust in our abilities, if we believe in those words nothing can stop us. I know for me to be a master I have a big deal of information to consume and put it to practice, once we get the practice and succeed, then we can say that we have mastered it.

Trending Blogs

Recently Viewed Blogs

Mastery Journal