...E-Commerce Marketing Plan | August 21 2011 | Internet marketing strategy for Tesla Tech | At Tesla Tech they offer a variety of computer related services. Services offered include standard computer repair, upgrades, custom gaming personal computers, accessories, and much more. Tesla Tech’s Marketing niche will be fairly pinpointed, set to cater to the older generation that needs and wants to learn how to use modern day computers and do not have the means to learn. This strategy will bring new business and keep customers returning to our website to learn about different applications and functions of the new computer that they purchased from Tesla Tech. This market is fairly untapped in the online and even onsite marketplace. Tesla Tech plans to offer this online service free of charge to customers that buy custom made or brand new desktop or laptop computers from our online e-commerce website. This will allow the company to generate many new customers within the age rages of 45+ who may be timid or reluctant to buy a new pc because of their perception that they do not have the necessary tools or knowledge to complete basic computer related tasks. Sales of new computer will increase since our entire strategy will thrive on the fact that consumers will know that they will be able to log-in to our video tutorial database and educate themselves on whatever subject they need help with. Our main demographic will be single or married woman age 45 and up. This demographic was...
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...new Custom Social . This platform provides a new level of insight for how social media is impacting your business. It provides metrics beyond those available anywhere, like fans and followers, and gives decision making metrics like how many site visits your social media activities generated and how many of your social media contacts converted on your site. Combining this data with basic executive measurement philosophies will provide concrete reports on what is and what isn’t delivering in your social strategy. The following pages outline some core measurement strategies that will transform your conversation about social media measurement. Customize. Automate. Simplify. Get a better view of your social campaigns with new, more powerful analytics tools, more ways to measure, and customizable...
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...JOB DESCRIPTION JOB TITLE: CHIEF CONTENT OFFICER Reports To Chief Executive Officer/Chief Operating Officer (smaller enterprise) or Chief Marketing Officer/VP of Marketing (larger enterprise) Position Summary The Chief Content Officer (CCO) oversees all marketing content initiatives, both internal and external, across multiple platforms and formats to drive sales, engagement, retention, leads and positive customer behavior. This individual is an expert in all things related to content and channel optimization, brand consistency, segmentation and localization, analytics and meaningful measurement. The position collaborates with the departments of public relations, communications, marketing, customer service, IT and human resources to help define both the brand story and the story as interpreted by the customer. Responsibilities Ultimately, the job of the CCO is to think like a publisher/journalist, leading the development of content initiatives in all forms to drive new and current business. This includes: • Ensuring all content is on-brand, consistent in terms of style, quality and tone of voice, and optimized for search and user experience for all channels of content including online, social media, email, point of purchase, mobile, video, print and in-person. This is to be done for each buyer persona within the enterprise. • Mapping out a content strategy that supports and extends marketing initiatives, both short- and long-term, determining which methods work for...
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...10 ...so you don’t have to. by: tara ‘missrogue’ hunt things I’ve done wrong who am I and why I’m qualified to talk about this stuff: • co-founder + CEO Buyosphere.com • been raising $$ for >1yr • raised $200k F&F • believed the hype • lived in SF for 4yrs • made a crapload of mistakes already • serial entrepreneur (but first startup) 1. focused on the ‘big picture’ too much the original* pitch deck *since 2008 when I put this deck together, I’ve done 75+ versions... “The hard part is to figure out the fewest possible features that could possibly accomplish your company’s goals.” Eric Ries The advantages of Minimum Viable Product (MVP) 1.test your assumptions 2.minimal wasted time/energy 3.iterative based on real customer needs The trouble with Minimum Viable Product (MVP) 1.it has to be viable 2.it has to be viable 3.it has to be viable key: build something your customers can use. what we did wrong: kept focusing on (our idea of) the final product and building minimum components of it rather than thinking about what our customers could really use. we were wandering lost in the sea of aimless builds with no data and no reason unfortunately, it took us a year and $200k to figure this out. fortunately, we’ve figured it out. 3 ways to figure out MVP 1. Think about the problem you want to solve and ask yourself: “Could I accomplish this on an email list?” Try it. On an email list. OR think about how people solve it currently...
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...(include all group members for group work): Deniz Ozalp Degree Programme: MSc in Technology Entrepreneurship Module code and name: MSING030: New Venture Analytics Assignment number/title: Coursework 1 / Geckoboard Course Lecturer: Dr. Dave Chapman Year of Study: 2 (part-time) 2013 Student Declaration I/we have read and understood the College and Departmental statements and guidelines concerning plagiarism. I/we declare that this submission is entirely my/our own unaided work. Wherever published, unpublished, printed, electronic or other information sources have been used as a contribution or component of this work, these are explicitly, clearly and individually acknowledged by appropriate use of quotation marks, citations, references and statements in the text: I/we agree that work submitted electronically may be checked using the JISC detection service Turnitin®. Where work is submitted electronically, the work cannot be assessed unless both a hard copy and identical electronic versions have been submitted. Signature: Deniz Ozalp Date: 5 February 2013 Marker Comments Date Received: Provisional Mark: Note of deductions: First Marker Initials: Internal Examiner Initials: NOTE: ALL MARKS ARE PROVISIONAL UNTIL CONFIRMED BY THE MS&I EXAM BOARD AND REGISTRARS MSI 2009/10 MSING030: New Venture Analytics Coursework 1 Key Metrics for Businesses Introduction: What is ? Geckoboard offers businesses a real time dashboard for monitoring their KPIs...
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...mărit numărul de comenzi cu 7% datorită statisticilor din serviciile Google Analytics şi Viget Despre PUMA ● www.puma.com ● Încălţăminte, îmbrăcăminte şi accesorii sport ● De peste 60 de ani, PUMA este printre cele mai importante companii internaţionale din domeniul sportului Obiectivele ● Să obţină detalii despre popularitatea conţinutului şi a produselor pentru a elabora strategii ● Să afle ce tip de conţinut atrage clienţii şi contribuie la efectuarea de vânzări în fiecare regiune ● Să mărească numărul de conversii şi să îmbunătăţească experienţa online a clienţilor prin optimizarea siteului Abordarea ● Utilizarea segmentării traficului prin filtre pentru a analiza fiecare produs ● Culegerea de date personalizate pentru a analiza efectul pe care îl au modificările site-ului asupra obiectivelor şi microconversiilor ● Utilizarea segmentării avansate pentru cuantificarea conţinutului şi interacţiunilor esenţiale din fiecare regiune Rezultatul ● Numărul de comenzi a crescut cu 7,1% ● Vizitatorii au petrecut de două ori mai mult timp pe site, interacţionând cu materialele mărcii PUMA ● În regiuni cheie s-a înregistrat o creştere de aproape 50% a implicării şi a numărului de vizite Studiu de caz În căutarea unui avantaj concurenţial Milioane de oameni din întreaga lume apreciază încălţămintea PUMA deoarece este uşoară, eficientă, flexibilă şi oferă rapiditate. PUMA şi-a dorit ca platforma sa de analiză web să aibă aceleaşi caracteristici. Prezenţa online a mărcii PUMA are rol de...
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...O C T O B E R 2 0 11 m c k i n s e y g l o b a l i n s t i t u t e Are you ready for the era of ‘big data’? Brad Brown, Michael Chui, and James Manyika Radical customization, constant experimentation, and novel business models will be new hallmarks of competition as companies capture and analyze huge volumes of data. Here’s what you should know. The top marketing executive at a sizable US retailer recently found herself perplexed by the sales reports she was getting. A major competitor was steadily gaining market share across a range of profitable segments. Despite a counterpunch that combined online promotions with merchandizing improvements, her company kept losing ground. When the executive convened a group of senior leaders to dig into the competitor’s practices, they found that the challenge ran deeper than they had imagined. The competitor had made massive investments in its ability to collect, integrate, and analyze data from each store and every sales unit and had used this ability to run myriad real-world experiments. At the same time, it had linked this information to suppliers’ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. By constantly testing, bundling, synthesizing, and making information instantly available across the organization— from the store floor to the CFO’s office—the rival company had become a different, far nimbler type of business...
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...Disruptive Innovation: A new era of Crowdsourced Data Analytics! Abstract: The existing business paradigm of data analytics is set for a transformation. Today, companies are experimenting to replicate the “Outsourced data analytics” model to “Crowdsourced data analytics”. Companies like Kaggle, Crowdanalytix and others are hitting the headlines of top analytics blogs across the globe. The reason is that the new business model promises a drastic decrease in the cost of analytics for companies long with the flexibility to get the problem solved anytime with much less effort. In short, it’s not just crowdsourcing that is the novelty of the concept, but the manner in which it is put to use that steals the show. Abstract: The existing business paradigm of data analytics is set for a transformation. Today, companies are experimenting to replicate the “Outsourced data analytics” model to “Crowdsourced data analytics”. Companies like Kaggle, Crowdanalytix and others are hitting the headlines of top analytics blogs across the globe. The reason is that the new business model promises a drastic decrease in the cost of analytics for companies long with the flexibility to get the problem solved anytime with much less effort. In short, it’s not just crowdsourcing that is the novelty of the concept, but the manner in which it is put to use that steals the show. General Management General Management MBA Core, 2nd Year MBA Core, 2nd Year Ayush Malhotra NMIMS,Mumbai Ayush Malhotra ...
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...of my company, I am not familiar with the names or metrics used to evaluate important data, but I do know from experience and part of my job function, reports and data gathered are used to make judgments and decisions about new products and constant improvements for existing services we currently provide. Surveys are completed by our travel partners and guests, and even employees. We compile reports and present them to management electronically. Our research, experience, and use of different applications, along with our IT departments, helps management and executives determine which direction to move forward. Feedback from our travel partners and guests are both direct and indirect. Upon learning about programs such as Google Analytics, the importance of webpage layout, the amount of time spent on our site, as well, as how often individuals contact our chat system and sales automation for assistance with our product gives insight to “how we are doing” as a company. Constant looping and revisiting certain pages...
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...volume, which is the quantity of data. The second is Variety, which the type of Data. The third is velocity, which is the speed of the data is gathered. The fourth one Variability, which is inconsistency of data can hamper processes to manage it. The final one is Veracity, which is the quality of data captured can vary. These data sets are growing rapidly mainly because they are gathered at a fairly cheap. The world's technological per-capita are doubling every 40 months. Business intelligence with data with high information density to look for trends. Big Data also increased information management specialist. Some of the largest companies like IBM and Microsoft spent over 15 billion dollars on software firms which specialize in data analytics. Governments use big data because it's efficient in terms of productivity and innovation. While gathering big data is a big benefit there are also some issues that need to brought up. Some policies involving privacy, security, and liability. Companies would need to put the right people to manage and use this data efficiently. Accessibility is also crucial because most likely there will need to be third parties included and incentives put in place to enable...
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...Date: 04-19-2015 The New Frontier: Data Analytics (Course title: Info System Decision Making) Professor: Clifton Howell Student: Deep Ajabani Data analysis is the process of finding the right data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have the biggest possible impact. Analytics have been used in business since the management exercises were put into place by Frederick Winslow Taylor in the late 19th century. Henry Ford measured the time of each component in his newly established assembly line. But analytics began to command more attention in the late 1960s when computers were used in decision support systems. Since then, analytics have changed and formed with the development of enterprise resource planning (ERP) systems, data warehouses, and a large number of other software tools and processes. In later years the business analytics have exploded with the introduction to computers. This change has brought analytics to a whole new level and has made the possibilities endless. As far as analytics has come in history, and what the current field of analytics is today many people would never think that analytics started in the early 1900s with Mr. Ford. We are going to have a look on Big Data Analytics. Let’s have a look on advantages of big data analytics. It helps marketing companies build models based on historical data to predict...
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...Definition IoT is one of the fastest growing technologies in computing. It is an environment where people, animals, or objects are presented with unique identifiers and the ability to transfer data over a network (Rouse, 2014). It has emerged from combining wireless technologies, micro-electromechanical systems, and the internet (Rouse, 2014). See Figure 1. These wireless technologies are equipped with, or connected to a smart device allowing data collection and communication through the internet (Caron, Bosua, Maynard, & Ahmad, 2016). Figure 1. IoT Ecosystem (Medici, 2015) Benefits * Tracking behavior for real-time marketing (Borne, 2014). * Enhanced situational awareness (Borne, 2014). * Sensor-driven decision analytics (Borne, 2014). * Process optimization (Borne, 2014). * Optimized resource consumption (Borne, 2014). * Instantaneous control and response in complex autonomous systems (Borne, 2014). * Increase operational efficiency, power new business models, and improve quality of life (Harrell, 2015). * Provide an accurate analysis of customer data (Medici, 2015). Some Applications of IoF Business intelligence (BI). “The BI application ensures the analysis and measurement of the consumer’s thoughts, behaviors, relationships, buying attitudes, choices, and many more parameters that form the backbone of effective strategy building, business operations management, customer relationship management, and other business operations” ...
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...companies in every industry are using analytics to replace intuition and guesswork in their decision-making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insights and running controlled experiments to test hypotheses. This course prepares students to understand structured data and business analytics and become leaders in these areas in business organizations. This course teaches the scientific process of transforming data into insights for making better business decisions. It covers the methodologies, algorithms, issues, and challenges related to analyzing business data. It will illustrate the processes of analytics by allowing students to apply business analytics algorithms and methodologies to real-world business datasets from finance, marketing, and operations. The use of real-world examples and cases places business analytics techniques in context and teaches students how to avoid the common pitfalls, emphasizing the importance of applying proper business analytics techniques. In addition to cases, this course features hands-on experiences with data collection using Python programs and analytics software such as SAS Enterprise Guide. Throughout the semester, each team works to frame a variety of business issues as an analytics problem, analyze data provided by the company, and generate applicable business insights as a secondary objective, while also learning essential business analytics techniques. Students benefit...
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...Spring 2016 | Elective | FIN | FIN7503 | EQUITIES | Spring 2016 | Elective | FIN | FIN7504 | RISK MANAGEMENT | Spring 2016 | Elective | FIN | FIN7511 | CORP FIN I:RASNG CAP | Spring 2016 | Elective | FIN | FIN7513 | FIXED INCOME | Spring 2016 | Elective | FIN | FIN7516 | CORP FIN II:EVAL OPP | Spring 2016 | Elective | FIN | FIN7517 | FIN & VAL SUSTNBLTY | Spring 2016 | Elective | FIN | FIN7518 | Managing Portfolios | Spring 2016 | Elective | FIN | FIN7565 | RE INV FUNDAMENTALS | Spring 2016 | Elective | FIN | FIN7572 | BABSON COLLEGE FUND | Spring 2016 | Elective | FIN | FIN7573 | INVESTMENT BANKING | Spring 2016 | Elective | FIN | FIN7578 | RE DEVELOPMENT | Spring 2016 | Elective | MATH | QTM7571 | Bus Intel, Analytics, Visualization | Spring 2016 | Elective | MATH | QTM9515...
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...become an analytic competitor. Questions as to what are the sources of Decision Making to an analytic competitor will also be discussed. A discussion on how influential quantitative modeling is and its utility in business decision making will be summarized. Finally, a Christian view that presents an ethical perspective on quantitative modeling and decision making will be presented. In an ever increasing global environment, maintaining a competitive advantage can be sustained through quantitative modeling, which can make a company a viable analytic competitor. How Can a Company Become and Be an Analytics Competitor Competitors make it increasingly more difficult to maintain a strategic competitive advantage when exclusive technologies, products and services can be duplicated (Davenport, Cohen & Jacobson, 2005). Organizations are now framing their strategies to accomplish optimization of “key business processes”: serving optimal customers, optimize supply chains, and understand and create optimal financial performance (Davenport, et al., 2005, p. 1). Optimization strategies demand that organizations now gather extensive data and perform extensive analysis that will guide executives in the decision-making process. The data and the analysis must be specific to the issues. In other words, they must relate in order to be useful in decision-making for the firm. In order to benefit from this competitive advantage companies also have to possess the analytic capabilities...
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