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Data import and export in R

R is a versatile tool that can handle a wide range of data sources, making it a go-to language for data analysis and statistical computing. Whether you’re working with CSV files, Excel spreadsheets, or databases, R provides powerful functions and packages to import and export data efficiently. In this section, we’ll explore how to import data from various sources and export your results back into different formats.

Importing Data from CSV Files

CSV (Comma-Separated Values) is one of the most common formats for storing and exchanging data. R has built-in functions to read and write CSV files, making it easy to import data for analysis.

Using read.csv():

The read.csv() function is used to read data from a CSV file into a data frame.# Importing a CSV file data <- read.csv("path/to/your/file.csv") # Display the first few rows of the data head(data)

Customizing the Import:

You can customize how the data is imported by using additional arguments such as header, sep, and stringsAsFactors.# Importing a CSV file with custom settings data <- read.csv("path/to/your/file.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE)

header = TRUE: Indicates that the first row contains column names.

sep = ",": Specifies the separator used in the CSV file.

stringsAsFactors = FALSE: Prevents character strings from being converted into factors.

Importing Data from Excel Files

Excel is another widely used format for storing data, especially in business environments. R provides several packages to read and write Excel files, with readxl and openxlsx being two popular options.

Using readxl Package:

The readxl package allows you to read Excel files without needing to install external dependencies.# Install and load the readxl package install.packages("readxl") library(readxl) # Importing an Excel file data <- read_excel("path/to/your/file.xlsx", sheet = 1) # Display the first few rows of the data head(data)

sheet = 1: Specifies which sheet to read from the Excel file.

Using openxlsx Package:

The openxlsx package offers more flexibility, including writing data back to Excel files.# Install and load the openxlsx package install.packages("openxlsx") library(openxlsx) # Importing an Excel file data <- read.xlsx("path/to/your/file.xlsx", sheet = 1) # Display the first few rows of the data head(data)

Importing Data from Databases

R can also connect to various databases, allowing you to import large datasets directly into R. The DBI package is a standard interface for communication between R and databases, and it works with several backend packages like RMySQL, RPostgreSQL, and RSQLite.

Using DBI and RSQLite:

Here’s an example of how to connect to a SQLite database and import data.# Install and load the DBI and RSQLite packages install.packages("DBI") install.packages("RSQLite") library(DBI) library(RSQLite) # Connect to a SQLite database con <- dbConnect(RSQLite::SQLite(), dbname = "path/to/your/database.sqlite") # Importing a table from the database data <- dbGetQuery(con, "SELECT * FROM your_table_name") # Display the first few rows of the data head(data) # Disconnect from the database dbDisconnect(con)

Connecting to Other Databases:

Similar procedures apply when connecting to MySQL, PostgreSQL, or other databases, with the appropriate backend package (RMySQL, RPostgreSQL, etc.).

Importing Data from Other Sources

R supports data import from various other sources such as: JSON: Using the jsonlite package.

XML: Using the XML or xml2 packages.

Web Data: Using the httr or rvest packages to scrape data from websites.

SPSS, SAS, Stata: Using the haven package to import data from statistical software.

Here’s an example of importing JSON data:# Install and load the jsonlite package install.packages("jsonlite") library(jsonlite) # Importing a JSON file data <- fromJSON("path/to/your/file.json") # Display the first few rows of the data head(data)

Exporting Data from R

Once you’ve processed or analyzed your data in R, you may want to export it for reporting, sharing, or further use.

Exporting to CSV:

The write.csv() function allows you to export data frames to a CSV file.# Exporting data to a CSV file write.csv(data, "path/to/save/your/file.csv", row.names = FALSE)

row.names = FALSE: Prevents row names from being written to the file.

Exporting to Excel:

If you used the openxlsx package, you can also write data frames to Excel files.# Exporting data to an Excel file write.xlsx(data, "path/to/save/your/file.xlsx")

Exporting to Databases:

You can use the dbWriteTable() function from the DBI package to export data back into a database.# Connecting to the database con <- dbConnect(RSQLite::SQLite(), dbname = "path/to/your/database.sqlite") # Writing data to a new table in the database dbWriteTable(con, "new_table_name", data) # Disconnecting from the database dbDisconnect(con)

Best Practices for Data Import and Export

Data Validation: Always inspect the first few rows of your imported data using head() to ensure it has been read correctly.

Customizing Imports: Use the various arguments available in the import functions to handle specific file structures or formatting issues.

Keep a Clean Workspace: After importing and exporting data, clean up your workspace by removing temporary objects or closing database connections to prevent memory issues.

Full details available at https://strategicleap.blogspot.com/

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Social media goals

When you finally identify the main areas to deal with based on your social media strategy template research analysis, you might be prepared to offer a broad declaration that captures the overall concentrate of the your social media initiative. You may address a rising chance or a significant need or even issue for the client. This particular statement, which should be in the form of just one sentence, is the goal declaration.

Objectives

After determining the entire focus of your social media strategy, you have to set objectives which clearly state what you intend to accomplish. Creating good goals is probably one of the toughest things you can do when constructing a social networking strategic plan or strategy. Many professionals struggle with this, so don’t be frustrated if you also find it difficult. In addition , there are many classifications associated with objectives to focus on depending on the self-discipline. For example , marketing objectives provide the purpose of increasing profit, achieving a higher yield of customers, enhancing volume of sales, and getting percentage points in marketplace shares, among others. Others concentrate on engaging awareness and knowing key issues and endeavours (e. g., journalism as well as public relations). Social media experts need to be aware of these and just how they are tied to the social networking goals for each client.

All an organization’s functions should revolve around its mission, objectives, and objectives, which in turn tend to be assessed with measurements which are definitive and quantifiable. To work, goals and objectives should be simple and easy to comprehend for everyone and linked with measurable achievements. Goals and objectives must also become updated at each planning time period to ensure they are continually helping the organization’s needs as well as purpose.

Objectives can take a variety of forms. For example , marketing goals might look to increase product sales, whereas public relations objectives may be to increase awareness about a strategy and restore or refresh established relationships with crucial audience members. Social media programs can be especially challenging, simply because we have to consider where this plan of action will be housed, which experts will be part of the team making and launching the plan, and just how we will evaluate and calculate whether we have achieved our own objectives.

All objectives should fulfill certain criteria, known as the SMART criteria, to work. Using the SMART criteria is definitely an established way to categorize efficient objectives into five various categories: specific, measurable, attainable, realistic, and time-specific. Very first, all objectives must be particular. This means we have to be clear about our objectives for your social media plan. For example , we may say we are looking to improve our community on Myspace. Measurements must be aligned in what we want to accomplish, so we require specific guidance from our own objectives about how much we would like to increase or decrease a particular element.

The second criterion with regard to objectives is that they are measurable. Objectives have to be practical within nature both in expectations and time and resources without any problems. Social media professionals do not wish to promise the world to a customer or organization without completely investing in the necessary tools as well as resources. Setting forth goals with a clear mindset associated with what an individual (or team) can handle is fair towards the client and organization, along with to those who are creating as well as executing the strategic strategy.

Third, objectives must be attainable. This means we must be able to really accomplish what we set out to fatigue the social media plan. In case a client asks us to improve her followers by a mil people in the span of the week, this is unrealistic, and that we cannot achieve her goal.

Fourth, objectives must be practical. Sometimes we need to have a heart-to-heart conversation with a client concerning this. The client may want to change the globe in a day. However , it may not regarding in the time scope with this social media plan. Having truthful conversations with your clients as to what is and is not practical leads to better expectations. This is simply not always perceived as good news, therefore a certain amount of authority and stability is required for you to share this in a confident way.

Lastly, objectives should be precise within their timing. It is only fair that this people with whom you’re focusing on a social media plan understand when they can expect objectives to become achieved.

There is no magic amount of objectives needed for a specific social networking plan. The number depends on the actual scope of the campaign and also the overall goal of the customer or organization you are symbolizing.

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Delivery from the Customer Perspective

The last mile framework for omnichannel retailing was constructed by combining relevant academic literature with a review of the delivery options offered in an advanced online grocery market. Leading British retailers were investigated to understand their fulfilment and delivery methods from a customer point of view. The variables that have to be taken into account were extracted and then synthesized in the framework. The framework covers issues such as the delivery model (home delivery or Click and Collect), delivery points and their characteristics, as well as consideration of related issues, such as delivery windows, fees, and subscriptions. The framework can be used as a starting point for further academic studies, and can be applied by retailers considering their delivery options and design of logistics operations in multi- or omnichannel retailing.

In omnichannel retailing, customers have the opportunity to freely select what, when, and how to buy (Hübner et al. 2016a). As omnichannel retailing grew, new models of distribution emerged (Hagberg et al. 2016b). These new logistics models are heavily supported by various technologies (Hagberg et al. 2016b), especially information technologies. However, new storage and delivery solutions, such as lockers or dedicated vans, have also been developed. E-commerce has already changed logistics, moving towards small parcel sizes, frequent deliveries, and returns. Omnichannel management has also moved away from a silo mentality, where separate units, or even companies served brick & mortar and online customers. Moreover, the mobile revolution blurred the lines between store and online shopping (Piotrowicz and Cuthbertson 2014). However, building a complete omnichannel is not straightforward, as an omnichannel approach influences the whole company, thus changing from a multi- to an omnichannel approach requires restructuring and a move away from the silo structure (Picot-Coupey et al. 2016). There is a need to change structures, processes, and people. Logistic systems, delivery, and fulfilment practices are among the areas that need to be analysed to develop, test and employ new models, tools and techniques, looking for solutions that are not just modern and convenient for customers, but also profitable. Changes in the customer side of delivery might result in a complete redesign of the operations and the augmentation of new supply chain models optimised for omnichannel retailing.

This post is focused on the delivery models used in the grocery retail; home delivery as well as Click and Collect options are reviewed. However, this post is limited to the experience of leading UK grocery retailers, and is written from the customer point of view. Thus, data available to customers are analysed to identify aspects that should be considered in omnichannel grocery delivery.

The post is structured as follows. Firstly, the academic literature on the topic is reviewed. This is followed by a presentation of findings from the customer perspective. The key section is the construction of a framework for online grocery delivery in omnichannel retailing. Finally, recommendations for academia and practice are drawn.

Omnichannel Grocery Retail Design

For omnichannel grocery retail leadership development plan, an effective and efficient design for the logistical and distribution system is a must. Without this, profits from sales may be overwhelmed by the delivery costs. However, this is very challenging (Punakivi et al. 2001). Grocery retailing is still not the norm using an online channel. Its acceptance was much slower than expected (Huang and Oppewal 2006). This is partly related to the logistical challenges of providing satisfactory solutions. Delivery costs for the last mile are estimated to be at the level of 50% of total Supply Chain costs (Hübner et al. 2016b). However, failures to design delivery systems are common among companies (Boyer et al. 2009). Moreover, many attempts for online food retailing initiated in the early 2000s failed (Delfmann et al. 2011). Companies such as Webvan and Homegrocer were unable to stay in the market (Boyer and Hult 2005). Through learning such lessons, retailers are experimenting with different delivery models and technologies.

Main Delivery Models

The delivery to customer, or collection by the customer, is the last element of the whole delivery process. The earlier stages are: (1) order acceptance and (2) fulfilment, when an order is prepared for delivery (Boyer et al. 2009). Product distribution is composed of forward distribution to the store or customer, as well as backward distribution, if a product is returned (Hübner et al. 2016b). In omnichannel grocery retail, home delivery of online-ordered goods to the customer is one model. However, other less common models for home delivery exist. For example, goods may be ordered in the physical store and then delivered to the customer’s home by the retailer. This may be appropriate where the goods are particularly bulky or the customer has difficulty transporting the products bought, such as an elderly person taking the bus home.

As omnichannel is an emerging concept, retailers are experimenting with different models and designs, which are also adjusted to local market conditions and customer needs. The first necessary condition for fulfilment is customer access to the internet, the web pages, and apps available for grocery shopping. However, these issues are outside the scope of this post, which focuses on supply rather than demand issues. The second critical aspect is the retailer’s strategy and target customer. An omnichannel approach might not be suitable for all retailers and customers, for example discounters with a low-cost strategy.

[lysun-reminder]

Do I Need To Be a Geek to mine bitcoin?

One must understand the underlying principles of what they are investing in. Bitcoin is not an exception. Mining needs a good deal of technical experience. A good understanding of so many concepts and process behind those is required such as bitcoin itself, how it works, wallets, wallets security, miner hardware and software, mining service providers, ability to select an efficient mining pool, and so forth.

It is interesting to note that the difficulty level adjusts itself based on the computational power. The objective is to have a constant block rate. In short, more computational power leads to a higher level of difficulty, whereas mining becomes easier if the computational power is reduced as there is a lower level of difficulty. The presence of increasing number of miners is making bitcoin mining harder, hence a need of more sophisticated equipment. The difficulty of mining gets adjusted every 2,016 blocks that corresponds to roughly every two weeks.

How to Use My Home Laptop Toward It?

In theory, a home laptop dedicated for bitcoin mining can be used. Whether it is profitable to do so is a different story altogether. A dedicated computer connected to the Internet is what anyone needs. The bitcoin mining process is very demanding in terms of processing power and electricity consumed by it. It was a common practice to use home computer for mining in its early days. However, now in 2018, bitcoin mining is rather obsolete.

Earlier in the 2009, the central processing unit (CPU) of a home computer was good enough to do bitcoin mining. On the mining of more bitcoins, it became quite difficult to do so using CPUs. Instead, graphics processing units (GPUs) gained popularity to perform the mining process. In 2013, ASICs became dominant, as these are the integrated circuits those are application specific, in this case, specifically designed for bitcoin mining. ASICs make the mining profitable compared with the use of CPUs or GPUs.

What Are the Required Software or Hardware?

Bitcoin hardware does the actual process of bitcoin mining, whereas bitcoin software is required to connect the miner with blockchain and the mining pool.

As mentioned earlier, the mining hardware has evolved from CPUs, GPUs, and then ASICs. The benefits of this evolution are better speed and lesser power consumption. The general considerations while selecting a mining hardware are the price per hash and electrical efficiency. As ASICs are designed specifically for the purpose of bitcoin mining, they become an evident option.

For the miners not interested in purchasing the hardware, they have an option to participate in the mining pool. This way, they rent the hardware on cloud subscription from the mining service providers. On that note, one can purchase simply a bitcoin cloud mining contract. Similar to altcoins, there had been numerous scams related to the mining service providers, so one needs to stay proactive by visiting bitcoin mining-related prominent forums.

The role of bitcoin software is regarding communicating information between miner and blockchain and the mining pool (if used). The software also monitors and displays various data related to hash rate, average speed, and temperature. There is no dependency on the operating systems (OS) as the mining software can run on any OS, including Windows, Mac, and Linux. There are many open-source free mining software available to perform the job.

Knowledge shared by thought leadership blog

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ARTIFICIAL NEURAL NETWORKS IN ACTION

You can use machine learning algorithms to find complex relationships or even classify data based on patterns that defy human perception. Neural networks take this to the next level. Here you can use thousands or even millions of artificial neurons to analyze data and identify subtle patterns.

Let’s look at a fairly common machine learning classification problem. Imagine you want to create a neural network that could identify a dog’s breed in a photo. You would feed a photo of a Dalmatian into the input layer, and the machine would output the dog’s breed Dalmatian. How does an artificial neural network accomplish such a feat?

Feeding Data into the Network

Think about an image the way an artificial neural network would see it — a collection of different bits of data. You can break down an image into pixels, each pixel being a tiny colored dot. Your smartphone’s camera supports a number of megapixels (thousands of pixels). The more pixels, the bigger and sharper the image.

Imagine a photo of a dog as a collection of pixels. To keep things simple, assume that the machine converts the image to grayscale. Suppose your image is 25 pixels tall and 25 pixels wide. This tiny image is composed of 625 pixels (25 x 25 = 625). Because it’s a grayscale image, some of the pixels may be totally white, others totally black, and most somewhere in between. In any given photo, the number of colors or shades of gray varies; for example, an 8-bit pixel can be white, black, or 256 shades between white and black. A 16-bit pixel supports 65,536 shades of gray.

Imagine using these 625 pixels to create an artificial neural network. Each pixel represents an individual neuron (node). We assign a value from one to zero to each node based on its shade of gray — 0 is black, and 1 is white, so medium gray is 0.5. Assuming we’re using an 8-bit pixel, shades of gray are in increments of about 0.0039; that is, each shade starting from 0.0 (black) is about 0.0039 lighter than the previous shade. (These are sigmoid neurons, because each can output a range of values between zero and one, not just one and zero or one and negative one.)

The input layer of the neural network contains 625 nodes that correspond to the 625 pixels. To keep things simple, we limit our model to ten breeds, so we have ten nodes at the output layer — one for each breed. In between are two hidden layers that perform the functions used to identify the dog’s breed. Again, to keep things simple, we use two hidden layers of 20 neurons each.

At the output level, we use zero and one to identify the probability of a given breed, with zero representing no match, one representing a definite match and all numbers in between representing the probability of a match. For example, one output node may show a 0.95 or 95% probability that the photo is of German shepherd, and another output node may show a 5% probability that the photo is of a dachshund.

Although you handle the inputs and read the outputs, the machine does most of the work in between — in the hidden layers. Each neuron in the hidden layer totals its inputs, adds bias, performs a function on the result and passes its output to one or more neurons in the next layer. We assign random values, between 0 and 1 to the connections between the neurons. These random values represent the relative strengths of the connections (the weights). We also assign random values for the bias within the neurons. The machine learns by adjusting these weights and biases as it goes through training and through multiple iterations of testing. In fact, the artificial neural network never ceases to learn. It continues to improve with each photo it’s fed.

What Goes on in the Hidden Layers

At the input layer, each neuron has a number between zero and one that represents its shade of gray. Zero is black, one is white, and between zero and one are different shades of gray. When you feed a photo into the artificial neural network, the shades of gray on the photo are converted into values that are passed from the input layer to the first hidden layer.

Each input neuron connects to each and every neuron in the first hidden layer. With our dog-breed artificial neural network, the input layer contains 625 neurons, corresponding to the 625 pixels in the image. Each hidden layer has 20 neurons. Each of the 625 neurons in the input layer connects to each of the 20 neurons in the first hidden layer. That means 12,500 connections link the input layer to the first hidden layer.

These 12,500 connections are crucial, because each connection can be dialed up or down to make the connections stronger or weaker. For example, neurons that correspond to pixels near the periphery of the image, which are less likely to be part of the dog, may have strong connections to a neuron that tries to figure out what the background is and very weak connections to the other 19 neurons.

One of those remaining 19 hidden neurons may be tasked with finding patterns that identify the eyes; another, the ears; another, the shape; another, the size; another fur length, and so on. Each neuron in the first hidden layer can dial up or down its connections with the 625 input neurons feeding into it to determine what it needs to focus on in the image, just as you might focus on different parts of an image.

Then each of the neurons in the first hidden layer connects to each and every neuron in the second hidden layer (of 20 neurons), creating another 400 connections. The neurons in the second hidden layer may try to associate the patterns found in the first layer with features of the ten different breeds. It may find that the ears look like those of a Doberman, while the fur length is characteristic of German shepherd; and the coloring is characteristic of a Labrador retriever.

Each of the 20 neurons in the second hidden layer then connects to the ten neurons in the output layer, creating another 200 connections. Here, the output neurons may look at the characteristics in total and determine the likelihood that the image is of a particular breed of dog. It may conclude that there’s an 80% chance it’s a picture of a poodle, a 15% chance it’s a German shepherd, and a 5% chance it’s a dachshund.

Again, this example is oversimplified, but it gives you a general idea of how artificial neural networks operate. The key points to keep in mind are that artificial neural networks contain far more connections than they contain neurons, and it is by adjusting the weights of these connections and the bias within each neuron that the artificial neural network can learn and continue to improve its ability to classify or predict.

This is a post from social media strategy blog.

[lysun-reminder]

Growing the brand

In the growth phase, the brand intends to pursue its expansion strategy, both quantitative and qualitative. Most of the brands that are successful today are at this stage of development, and are characterized by a growth in double digits.

In quantitative terms, the sign will seek to settle in new geographic markets, expanding its presence in existing markets. Logical volume is most evident in this step; It must be sold more easily absorb the fixed costs. But since communication is usually given as a percentage of sales, more sales, more brands can communicate.

In terms of quality, brand optimizes production tools and possibly improve product distribution and use its growing reputation, to enter into new areas. These extensions through the launch of new product categories are, of course, is a growth factor, but also to enhance brand awareness, making it more accessible thanks to the many and / or distribution channels more broad. the seeds of future legitimacy in new areas are planted. The budget for communication and to strengthen the brand identity then serves as an umbrella for several product categories and easier to be profitable.

The fact that there are more sectoral development axes of growth, geographic expansion, introduction of new products, optimize internal processes and move the brand explains why this step may last for decades. With the exception of sectoral growth, these are all ways in which they can participate in the market the brand with its main competitors.

Sector growth

The most recent case of the rapid growth of the sector is the explosion of electronic tablets on the market after the release of the iPad, the model of the phenomena observed already with notebook and mobile phone. However, this single shaft can not guarantee steady growth in a volatile market or quickly reaching saturation.

geographical expansion

After a successful product in one country, it stands to reason that you should sell well in other countries. Attempts to implement multiple and take many forms.

In some cases, especially in the mass market, the same product from the same communication strategy can be effective. This is a global strategy of Coca-Cola and Pepsi Cola, for example. We are not advocates of universal communication, which now seems increasingly likely to use less, and even for those products that are based on the target populations that are affiliated by transnational values ​​(youth, dynamism, relaxed attitude to adults) is a place designed to local conditions. For some large advertisers, the central marketing team to send a set of hoses, for example, uses the same strategy, but with different approaches. Therefore, each team can choose a specific campaign that will be most applicable to your environment.

This is also what is done with all the fashion and perfume brands, a large percentage of these sales to foreign customers. Digital advertising guide will generally be identical. In some cases, you can change a little bit, ""for example, to the Persian Gulf.

In the cosmetics industry, the product will be identical, but the message may vary depending on the country. In one country, the product can not serve exactly the same function in another. In the United States, for example, Yamaha product 125 is free; in Taiwan, it is a means of transport. In these cases, the ad will be different.

There are also cases in which the product is different when communication is maintained more or less the same. For example, in Asian markets, some of the cognac producers sell sweeter versions of their products. Although the name remains the same, and your ad is similar formula can be adapted to the local taste.

There are cases of commercial cleaning, for example, if the product and communication are different, but they are generally beyond the categories of luxury and therefore responsibility for this study.

This diversity of situations is a good example of the many difficulties that may be involved in the export of brand. Geographical expansion cases are not legion. Apart from organizational related disorders with a poor understanding of local conditions and requirements, brand or its products may sometimes be simply not be exported.

These are products that have a cult in the country, but whose potential abroad is limited. Pastis 51 and Suze typically French products, which are widely consumed in France, are difficult to export. Italy Martini serves as an aperitif in the United States, but it is unlikely that its strong international and routinely consumed.

Other brands is very strong in their own country, but it's hard to be exported is the largest store witnessed the recent failure of Marks & Spencer in continental Europe. The French may wonder why the Galeries Lafayette, were not able to find anywhere else in New York, Singapore, Bangkok and Berlin. The explanation is simple. The success of Galeries Lafayette in France is associated with a certain French way of life, represented by a group of French brands which are known and valued by French consumers. Berlin and New York, French consumers are not present, and logos designed elegant as representatives of the French are not necessarily available in the store; if they are very strong brands already have a presence in this market, often through exclusive agreements with other stores or local shops. The challenge is to create a French-style living abroad, there is no serious French and the French brand customers. It is difficult to build a strong case for the existence of a department store. The only cases of successful export Japanese stores are stores like Sogo and Daimaru in Southeast Asia, they use locally with the support of many Japanese tourists and locals. French Le Printemps store in Tokyo, can store any of the great French brands, they invite French style aimed at very young girls. Offers new, unknown in Japan, and sometimes even in France and created specifically for the shop.

Zara is a special case. Development of the company in 1990, took place without publicity and based on the opening of new stores singlebrand other than Spain, relying on their ability to read trends and rapid response logistics. Twenty-five years Amancio Ortega created Inditex, owner of Zara, which has 5,044 stores worldwide, with a turnover H14 billion in 2011.

In summary, while the geographical expansion seems to be the most natural dimension of development, but also complex and requires time and considerable investment. Moreover, the results are often unpredictable French chain Sephora, which at the beginning of 2002 they closed their shops just opened in Japan and the United States learned. For these reasons, the process of international development makes the game Wideopen, but also more difficult.

[lysun-reminder]

Construction of identity and strategic social media

After all, you can say that you are everything you want in a social network."" 1. The recent scandal involving the New York Republican Congressman Christopher Lee, hiding their marital status and elected office in a personal letter the ad Craig in search of women to date , highlights the potential use of social networks on the Internet to create a virtual identity in addition, targeted program. For example, Facebook, which allowed many other personal and professional side, now also facilitates discreet Creation pages more personal, allowing users to segregate ""friends"" in the ""network"" are mutually exclusive with privacy settings that are hidden investigation. So, as a result of fraud or strategic omissions, or both, for example, you can build your online identity sterilized for consumption by the family or professional contacts and the other as a candidate for friends and relatives occasionally. In particular, gay, bisexual, transgender and queer (LGBTQ), this function helps the resurrection of the ""closet"", which allowed long sexual minorities, to avoid disapproval of conservative elements of the dominant culture, that people can be both in culture and underworld. In this chapter, the work Sedgwick in ""the closet"" as a metaphor for hiding and discovering the identity of Goffman's observations concerning the identity of people management and other pioneering work in question this practice reoccupation and its consequences.

anecdote Fund

Some time ago, the author was traced college friends in the building a digital media strategy for Facebook and sent a ""friend"" invitation to one that was not even for a short period of new subordinate, when the two were journalists. Profile indicated that a friend moved to the southern part of the United States, working in public relations, the company has self-identified as gay, and had a few, as well as a large network of friends. Months passed without a response to ""friend request."" One day, the author received a request for a ""friend"" by the same person. After confirming the request, the author discovered Facebook profile very different: I could remember its location, employment and training, but he had no partner and friends, one elderly woman, whose name has been suggested that the relative, Author, embarrassed, sent a message to his friend, thanking him for the invitation and for a short time to update the life of the author, because the latter were in contact and ask for an update from a friend. A friend had sent apologies for the delay in response to connect to Facebook, explaining that he found some of the cumbersome procedures. Renewal provided few details beyond the scattered information in your profile. The author decided to up the ante: in the return message, recalled his homosexuality and his recent teaching and writing on queer theory and the media. Suddenly, it is removed from the profile page spread of his friend and original, ""friend"" request for a full and frank profile was adopted.

The incident showed that the Cabinet, who spent time frame define the boundary between the known life of gays and lesbians, that all signs or symbols have been removed to be problematic in their interactions with traditional culture and their secret lives as members of the subculture is out, many assumed, that if no less overwhelming context / family after the Stonewall / post-Ellen posmodernismo, at least not in evidence, which is alive and well, and either break in cyberspace and block valves. It was the observation Sedgwick, noting that even some gay and more open and valuable women are not in the closet somebody personally, financially.

In this case the meaning was not quite normal, because it was nearly three decades since the author and his friend was in contact. The relationship between them, though multidimensional, it was not particularly a neighbor and a friend pointed staff and professional life does not depend on the consent of the author. In fact, the date and the geographical distance and the relationship between them can be an opportunity for self-revelation. Of course, the downside to disclose the cost of the transfer distant known, it seems so faint that made it worth the risk. And the fact that a good friend of previously available dose of life across the board in front of a friend's request suggests that the way homosexuals are doing their identity may be strategic, but also the most driven knee-jerk reaction as critical thinking.

Identity in the virtual space

If a person has himself / herself to others, he / she tries to maintain control over that person, and to minimize the appearance of the characters that are in conflict with their own idealized identity.19 FTF interactions, the physical presence of the unit construction avoids inadequate identity with visible physical characteristics of the person . In addition, the common knowledge of the social environment of the unit makes it difficult for him / her to pretend something he / she is not.

In his ""Theory Tacos social context"" Lee Sproull and Sara Kiesler suggested that communication on the Internet FTF available.20 differ in the amount of social information in the online environment, such as SNS or social cues, such as non-verbal behavior and ""physical environment are available. the absence of these signals, say, could lead to disinhibition behavior, such as aggression, verbal behavior and candid disclosure nonconforming. by Sherry Turkle output lying.21 also facilitates entry and exit Zhao Shanyang, Sherri and Jason Martin Grasmuck find this tendency to ""act"" and take on the role of the personality of the user, unlike the physical world of a person who is related to the degree of anonymity offered in the online environment in this sites which offer greater anonymity seemed to favor the consumption of these roles;. those with ""nonymity"" (the opposite of the nimato) N.

In general, as noted by Monica Whitty, in virtual environments boundary between public and private space is fuzzy at least best.23At, nature at the same time, the public social and private media complicates the traditional concepts of communication in common, including the construction of public identity. Danah Boyd and Jeffrey Heer noted, when people talk in the physical space, read the active contextual signals, including the assessment of the appropriateness of hearing establish communication. In virtual environments, such as the SNS, the context is produced structurally, but rather by the interaction of performative and critical part of the context of the public, it is almost impossible to assess, especially if physical space relationship between the user and the audience is outside of it. Boyd and Alice Marwick term ""context collapse"", where users can no longer assume a different set of keys contextually, to model their trade.

This leads to the creation of a new and uncertain ground for the formation and maintenance of relationships, because by Monica Whitty and J. Gavin, ideals that are important in traditional relationships such as trust, honesty and commitment which are equally important on the Internet, but points to the that these ideals are very different. For users of the National Health System, their profiles are a compromise between the potential profit associated with social relationships and establish social pain, giving up some control self.27 presentation

However, people are very flexible in their communication practices. Early research on online relationships that the differences between online and offline relationships dissipate over time.28 Despite the fact that the lack of agreement to condemn physical characteristics, makes some users overlook the barriers of social interaction, which would normally be in the physical world Nicole Ellison and his colleagues have discovered a virtual identity online dating are very similar to the ""true self"" of various users some truth which extends their appearance.

A brief note about the art of lying

There are no hints in the context of cyberspace, which are part of a routine physical context creates opportunities for profiles that are fictitious, either in whole or in part. As with most actual fiction profiles can be explicit (eg alias) or hidden names (for example, lack of photographs and lists of friends). In the end, it's relatively unlimited ability to manipulate what identity means that there is no way to know if the Facebook account was created by someone who supposedly represents.

In fact, the NHS has a history nonauthentic profiles. At first SNS Friendster, fictitious identities were so widespread that users have invented names for different categories, including ""Fakesters"" (nonbiographical profiles for recreational purposes), cheats (intentionally duplicate fake authentic profiles for fraud) and Pretendsters (profiles - recalls constructed by random realistic photograph online). While much of the motivation for creating these fake profiles was the entertainment of users, friends and the community as a whole, Heer Boyd argue that the entertainment was coincide with the most important to remember Friendster that community, ""none of this is true."" 31 In addition, at the beginning proliferation of these false identities built not only shows that the tradition of fraud in the online identity management, together with virtually SNS emerging, but also knowledge of the opportunities for users to create an online identity is more diffuse, both among its creators and their audience.

[lysun-reminder]

Figuring out the customer

2012 was a tough year for T-Mobile. They suffered a major embarrassment when their merger with AT&T failed to get the necessary regulatory approval; and due to the company’s uncertain future, lack of support for the iPhone, and poor network coverage, they lost 800,000 subscribers.EndnotesThis was a death knell for the small US wireless company, which had been trying to compete with the likes of behemoths like Verizon and AT&T. Many believed that T-Mobile’s days were numbered.

The “un-carrier” approach, with its bold colors and edgy advertising, had a strong impact on customers’ perceptions of the company. T-Mobile had tapped into many customers’ frustrations with their current providers, and appeared to be empathetic and sincere in trying to improve their situation.

T-Mobile could not compete head-to-head with its competitors when it came to device selection or network coverage, but customers were beginning to value T-Mobile as the authentic and scrappy underdog.

That year, T-Mobile grew their subscriber base for the first time in 4 years and, for the next 13 consecutive quarters, maintained over 1 million added subscribers each quarter.

Additionally, the company enjoyed outstanding customer satisfaction ratings, continually topping the list when compared to the competition.

By focusing on the motivations and desires of their customers, T-Mobile completely turned their company around. Instead of being a small wireless carrier, pushed around in a dominated industry, they became a customer-driven contender. Eventually, Verizon and AT&T had to modify their offerings because many of their customers were leaving for T-Mobile’s simple, contract-free pricing.

Formulating a Customer Hypothesis

Like T-Mobile, the most successful companies are continually trying to answer three fundamental questions about their customers:

Who is the customer?

What do they want to achieve?

How can we help them?

During the Customer stage of the HPF, we’re trying to answer the first two questions (the Concept stage helps us answer the third question). We do this by formulating hypotheses that reflect our assumptions and then test these beliefs with our customers. (More at social media marketing plan pdf)

Let’s look at the hypothesis template that is applied at the Customer stage:

We believe [type of customers] are motivated to [motivation] when doing [job-to-be-done].

Through validating and invalidating your Customer hypotheses, you’ll have a better understanding of who your customer is, what they’re trying to do, and why they’re motivated to do it. Let’s look at the three parameters of the Customer hypothesis template more closely.

Types of Customers

No two people are alike. So we shouldn’t group all our customers into two simple buckets: those who are using our products and those who are not. If we do that, we will miss all the nuances in between.

When we formulate our Customer hypothesis, we want to be sure that the [type of customers] parameter isn’t defined by the customer’s problem, the task they’re doing, or the product they’re using. This parameter should reflect the customer’s identity.

Identifying motivations, interests, unique perspectives, and behaviors is much more powerful and insightful than a list of generic demographic information. Therefore, being specific about the type of customer will lead to greater clarity when you’re making sense of the data you’ve collected and sharing what you’ve learned. Let’s look at an example.

Imagine we’re members of a team working on a desktop publishing tool. Our tool, called StarDoc, allows customers to create flyers, newsletters, calendars, and business documents like memos and letters. Our team is looking for new opportunities to help small businesses with document creation.

When creating Customer hypotheses, we want to make sure that we’re separating the customer from the product.

For example, we shouldn’t begin our Customer hypothesis by saying:

We believe StarDoc users are motivated to [motivation] when doing [job-to-be-done].

We would say:

We believe office administrators working for small businesses are motivated to [motivation] when doing [job-to-be-done].

Effectively, the customer has an identity beyond the fact that they use StarDoc. It’s important to capture that identity so we know, specifically, whom we’re talking about when we refer to this segment of our customer base.

Motivation

Throughout our day, we make thousands of tiny little decisions to achieve an outcome. Sometimes these decisions are made in a blink of an eye, and others are thoughtfully mulled over and considered.

The underlying stream that supports these decisions is our motivation. We use products and purchase services such as social media development services because we’re motivated to achieve a certain outcome. T-Mobile understood that customers were motivated to avoid lengthy and complex contracts, and this understanding helped the company stand out from their competitors.

Let’s go back to our example of office administrators working for small businesses. We think that these administrators have a strong desire to create promotional brochures for their businesses. We might be inclined to continue our Customer hypothesis by saying:

We believe office administrators working for small businesses are motivated to make a promotional brochure when doing [job-to-be-done].

However, when you look at this hypothesis, it feels like it’s missing a higher-level motivation. Sure, the customer’s goal is to make a promotional brochure, but the first questions that come to mind are, “Why do they want to create a brochure? What are they hoping it will accomplish?”

After talking with office administrators about their desire to create brochures, we learn that many of them are struggling to find low-cost ways to promote their business offerings. So, we revise our Customer hypothesis to capture that motivation:

We believe office administrators working for small businesses are motivated to promote their business offerings when doing [job-to-be-done].

By capturing the higher-level motivation, we’ve opened our hypothesis up to many more opportunities. This will help us explore various jobs our office administrators will “hire,” using our product, to advance their goal of promoting their business.

Job-to-Be-Done

Let’s consider our office administrators trying to create promotional brochures. Under the Jobs Theory, we would say the product that the office administrators “hired” to complete the job of creating a brochure was StarDoc.

At this point, you may be thinking, “This seems like a lot of wordplay and semantics,” and you’d be right. However, the words we use strongly affect our understanding of what we’re trying to help customers achieve. Therefore, it’s important for us to clarify, with language as specific as possible, what we are (and are not) doing to help a customer achieve their goal.

So, let’s try to plug StarDoc into our job-to-be-done, within our Customer hypothesis:

We believe office administrators working for small businesses are motivated to promote their business offerings when using StarDoc.

You may have noticed we’ve changed the verb from doing tousing. From time to time, you’ll find that you need to change the HPF templates to make them easier to read or understand. Again, these templates should serve only as an example. You’re free to rework them however you’d like; it’s the hypothesis parameters we strongly encourage you to keep.

The job-to-be-done in this hypothesis focuses on the product (StarDoc) rather than the task (creating a promotional brochure). Therefore, we want to articulate what job the customer is “hiring” to promote their business offering. In this case, we believe the customer has chosen a brochure to achieve their goal:

We believe office administrators working for small businesses are motivated to promote their business offerings when creating promotional brochures.

This completed Customer hypothesis sheds light on the type of customer, their motivation, and the job they’re engaged in. We could now run an experiment on this hypothesis by talking with office administrators about how they promote their businesses. We could then determine if they engage in activities like creating brochures.We could have several variants of this hypothesis with different job-to-be-done parameters, such as creating posters, creating flyers, or creating newsletters. These variants could happen with any one of the Customer parameters.

The StarDoc team could identify many types of customers, motivations, and jobs and made a plan on social media marketing for restaurants from the inputs. Some of the motivations and jobs may be unique to a specific customer type; others may be shared across multiple customer types.

This is why segmenting your customer base is so important: so you don’t mix the signals you’re hearing from one group and generalize them to other groups.