How to be a Digital Marketer?

How to be a Digital Marketer? This question seems simple and also looks difficult. As we all know, the age of big data drives changes in the whole world faster than ever before. Marketing no longer remains the same as we thought in the past. The four Ps of marketing Price, Place, Product and Promotion used for long time are less emphasized than in the past, and new Four P's even are emerged for digital marketing (but the versions seem varied among different people or parties!). So, one thing for sure is that being a digital marketer would not be the same as being a traditional marketer. The requirements of knowledge, skills and personality for a digital marketer could be a lot different than a traditional marketer.

The subject question could be simple because I can easily speak of many skill sets that is required for a digital marketer randomly. The job for a digital marketer is more digitalised. He or she should know how to use data visualization tools. Excel is only the basic skills marketers should equip with(but of course it might not really need excellent skills in it). What I am saying here is some popular tools which large corporation would pay to use and some free tools for public. For examples, SAS Data Miner, Tableau, Google Data Studio. But that may not be enough for the employers. It is better for the marketers having the certification of the data visualization tools, like mentioned SAS and Tableau they are providing certification exam. Simply say, digital marketers should be very familiar with some popular software in digital marketing field.

However, the reason I said difficult to answer because it is not that simple to be a digital marketer, or say, an outstanding marketers. Having knowledge to extract and report data is just the basic thing for a digital marketer, a good one should be able to analyze the data and make meaningful reports. Not only reporting beautiful and meaning report, but digital marketers should be also able to make good use of data, and think strategically how to use the data to help the company business in the scope of marketing. So, it is tough to answer the question. The job scope would be very wide and diversified. Also, the world is changing too fast, Digital marketers have to keep the pace of the changes in the digital marketing field could be very tough too!

Why do we use Google Data Studio?

There is a long list of tools when speaking of data visualization. Now, more and more great data visualization tools are free and they are very simple to use and easy to access. The number of tools might even make us confused and struggled to pick one that we want. In order to know if Google Data Studio is the good fit for you, we should learn the characteristics of it for comparing with other tools. First, just to have a quick talk of data visualization. It is the process of taking a data set and visualizing it in a way that can be easily understood. Sometimes called data viz, data visualization can be something as simple as a bar chart generated from an Excel file, or as complex as an interactive multimedia experience. The best data visualizations are beautiful, informative, and responsive.

1.Create Beautiful Reports

Many companies, especially large corporation, has tons of data for their businesses and their clients. The data may be already well-organized but may not be visualized. There are people out there who have created entire businesses around making data consumable, easy to read, and simple to understand. Google Data Studio could definitely help simplified the process.

Although we can visual the data on Google Analytics ,it can be kind of tough and time consuming to create spreadsheets, analyze the data, and format in a way that makes sense to shareholders in the company.  As Data Studio is built for data visualization – making it intuitive and simple to pull information into beautiful, consumable reports. The tool gives you the ability to change colors, gradients, fonts, etc. In addition, Data Studio provides a lot of different professional templates which help to make a beautiful report. Furthermore, Data Studio provides different formats or ways, such as bar chart, line graphs, pie chart, to present all the data. 

2. Pull Data From Multiple Sources

It is very amazing that you are able to import data source to Data Studio from multiple sources – even to the same report! You may pull data from some Google products such as Google AdWords and Google Analytics.

As we know, we can own many different accounts under ONE google analytics account. For example, we can have three different online stores and create three different properties under ONE google analytics accounts. Besides, we could create more than one views under one property on Google Analytics. For example, we can have one view for filtered employees' IP address, one view for members, and one view for master (all visitors). I want to point out that in Data Studio, you are able to pull out data from these different sources for your report. When you are creating a report for an online store, you may need to compare data from members and non-members which need you to pull data from two views on Google Analytics and Data Studio makes you do that!

3. Share easily and in real time

No more needing to give or get access to Google Analytics and navigate the UI to get what you need. Because Data Studio reports operate like any document on Google Drive — permissions can be granted to anyone — it allows for collaboration. And, it gets the real time updates, people can see the changes or updates immediately.

4. It’s free

It is free of charge and easy to access. There are some restrictions for this tool. There is also a limit of 5 reports per account (that is, the email address associated with Data Studio). The good news is, there is a bit of a workaround here. Similar to tabs on Google Sheets, Data Studio allows for additional pages on each report you create.

 Reference:

https://www.clickinsight.ca/about/blog/7-reasons-data-studio-google-analytics

What is Google Data Studio?

Speaking of data visualization, we should also look into a comparatively new tool Google Data Studio among many great tools out there. In this post, let's see what Data Studio is.

Google Data Studio allows you to turn your analytics data into informational, easy-to-understand reports - such as charts, graphs and maps, through data visualization. You can easily customize your reports to suit difference needs. Compare to the visualization function in MS Excel, Google Data Studio is much more user friendly and looks much cooler.

Another cool thing about Google Data Studio, for marketing analyst, is that it can be linked to your Google Analytics account to obtain data about your websites or digital marketing campaigns directly from Google Analytics. This make analyzing marketing activities so much easier than in the past when you have to export the google analytics data and use 3^rd party software for analysis. Furthermore, you can also import your data from external source into Google Data Studio to create professional reports.

Reports in Google Data Studio are interactive and dynamic, so that when new data available from a linked source, reports can be updated automatically to provide a real-time report. Additionally, the reports can be shared easily under a controlled environment since it allows you to edit permission on the shared report for each individual, allowing them to read or edit.

Reference:http://searchengineland.com/google-data-studio-258871

The Trend of Digital Marketing in 2017

All the way long we have been discussing big data, data analytics, and data visualization which all about digital marketing. In the digital world, things changing and new things happening all the time. We are too busy to catch up all the new trends and sometimes may get confused. Therefore, it would be god to have an idea the big trend of digital marketing in this year.

1. Marketers will increasingly adopt machine learning and data science

Machine learning and data science provide marketers with the opportunity to increase productivity effectively, enabling them to focus on the overall strategy deployment and eliminating the time spent on day-to-day data analysis and data management. Adobe recently published Adobe Sensei. Adobe Sensei, built on Adobe Cloud Platform, is a new framework and intelligent service that combines artificial intelligence (AI), machine learning and deep learning to dramatically improve the delivery of design and digital experience.

2. Videos will become dominant

Videos have been regarded as "the next big thing" over the past few years, but marketers have not yet fully understood how to use the video flexibly in marketing. Knowing how customers use video content and learning how to use video ads will provide key opportunities for marketers in 2017.

3. Content speed will become critical

High-speed and large-scale production of personalized and interactive content of the ability is the thing marketers should pay attention to. In order to do this, marketers need to bring into the customer's role, and deeply feel the experience provided by its brand. The customers interact with the brand from multiple touchpoints, so the marketers need to be aware of how these experiences affect the entire customers' consumption process.

4. Customer experience is the biggest driving force of digital transformation

The biggest driver of digital transformation is the establishment of a competitive advantage, and the core of which is the customer experience. Customer experience is a new indicator of the success or failure of the competition, it can distinguish through the digital transformation to promote their own brand and stagnation in the old business model of the brand. Today's digitized layouts are full of users who use multiple devices to interact with each other, including mobile phones, wearable devices, tablets, and even automotive dashboards, and people will want to use it when new products or new ideas are available , The increasing expectations of customers so that the brand must be customer experience for the core business.

5.2017 digital marketing first interaction

The new year's digital marketing trend is about to change, the past marketing, only the pursuit of the target audience design ads, and then put to the community, now only to consumers to see is not the best digital marketing, must also allow consumers to " Interact with you ", 2016 second half of the fame of advertising.

6. Content marketing is not extensive marketing

In the past, many of the products known as content marketing, are the name of the slogan of marketing, marketing and marketing of the real. Still to the brand point of view to send an ad text, this article can not get the favor of consumers. Those business owners who can not be rewarded in digital marketing should think about: "Are you interested in what consumers are writing about?" If you only introduce the brand, tell the selling point, and do not meet the needs of consumers, it is not content Marketing, and with the traditional advertising is no different.

Is Big Data Changing the game of Traditional Marketing?

In traditional marketing, we always were told about four Ps: Product, Price, Promotion, and Place. But the world is changing so fast and we can see the way marketing has been changing rapidly as well. Like, we can see a lot of marketing has been moving online. Are the four Ps of marketing still working in the industry? How can we apply them in today digital marketing?

One of the biggest changes is the shifting customers online and they are able to interact with the companies. In the past, customers might just walk in the physical store, shop and leave. Now, company is able to track their online shopping behavior. The age of big data is providing the chance and leading the trend for business to transit the marketing. Big data enables "personalized marketing" to become the basic service.

 The traditional marketing, cannot do very detailed personal marketing and mostly focusing public marketing or group marketing. For example, traditional marketing based on consumer demand, and the market segmentation is for the different groups. For example, a sports shoes brand has seven market segments, and then with seven marketing activities, often have to spend a lot of manpower and resources. But with big data, the marketers can get every consumer's purchase time, purchase cycle, purchase characteristics to analyze their buying behavior and shopping experience. They can launch online marketing campaign which cost much less money and resources.

Everyone's buying behavior, consumption habits are not the same, but the traditional marketing because of the limitations of resources and manpower, therefore, often can only be with people to marketing, rather than marketing to meet people; when the business can only perform seven marketing activities. But when the marketing activities have the ability to become as many as 70,000, each consumer can be matched from 70,000 activities to the most suitable for these activities, and thus move the old marketing point of view, into a person to find activities, rather than activities find someone.

Marketing activities from groups to the individual, the market segment is getting smaller and smaller, or that each customer has become a focus on the market, marketing become personalized accompany by the age of big data.

The benefits of Big Data

We have talked about data scientist skill sets in digital marketing in an old blog and we realized that how importance and necessary big data and data analytics are in today world. Many people know it is indispensable for online marketing and good for business, but may not realize the benefits of using bid data specifically. I would like to share some of the benefits here. 

Big data analysis actually can make us of big data to increase customer participation. Marketers can improve it through consumer buying behavior, personal shopping experience and other information to gain more consumer interaction. For example, marketers can get data from Google Analytics to analyze their customers' buying behavior. They may know which customer segments are interested in their products most, which customer segments are buying their products most and most frequently, when and what time their customers are most active to browse their website and online store, where and what channels their customers and website visitors come from, how the website visitors are visiting and shopping on the website, etc.

Digital media marketing staff must consider all aspects of consumer information and behavior, to create a better consumer product experience. The use of data analysis help understand the purchase behaviors of consumers and to enhance customer participation through interaction, with the analysis of the information marketers can use data to quickly enter the next target market.

Getting these kinds of data, marketers are able to have more specific, personal and effective marketing campaigns to either potential customers or current customers. Brand marketing staff use data analysis to improve the marketing process of enterprise marketing. Big data analysis has become a new insight into market trends. In the past, digital marketing staff cannot track the consumer's shopping model, and now through the data analysis to become a new way to observe the market trend for the corporate brand in the target market to get the most response.

Why Analytics?

I think all of us cannot avoid analytics in this technology world nowadays and it's time to see analytics seriously. Analytics has been at the top of Gartner’s CIO technology priorities for decades.

Let's speak analytics in marketing field. The job of modern marketers is to optimize the whole system of touch points to maximize the flow of satisfied customers. And to do that, they rely on analytics, to guide the customer at each point – “you may be interested in these other products” or “here’s a discount if you purchase now.”

In the new world, it’s no longer about having a “customer process,” it’s about creating thousands or millions of personalized “processes” on the fly, based on the needs of each individual.

Because these new processes are analytics-powered, they can be much more agile and responsive to change – indeed, with new machine learning approaches, they can even update themselves, automatically adjusting to consumer behavior.

And this doesn’t just apply to marketing. We see the growth of similar on-the-fly processes in every other area of modern business, from production and logistics to finance and human resources.

Effectively creating and managing these kinds of flexible, on-the-fly processes is THE big new opportunity in digital business.

Reference:

http://timoelliott.com/blog/2017/03/analytics-is-the-most-important-business-process-in-your-organization.html

Big Data and Analytics in Different Industries

Travel

The travel industry has always depended on treating statistics to provide the best possible service. Using data to predict when people will travel, where and how means companies can provide the exact service their customers need at the best time and at the right price.

For example, a flight company can use historical data collected on customer journeys to predict demand for fares in different periods of time so that they know when the demand is higher and when is lower. They can set different prices depending on the predicted demand for fares. Predictive analytics can help you dig down into even greater detail and give you the edge over competitors in a tight market.

Insurance

The insurance industry has always depended on math to calculate insurance costs. However, this usually depended on the history of the client in particular and other internal data sources.

For instance, travel insurance would be calculated on risk based on accidents statistics, probability of death and injury history. However, by using more powerful data analytics tools you can incorporate an even wider array of sources to build an even more specific picture of risk-related to one customer in particular.

Energy
The energy industry needs to find a constant balance between providing the right amount of energy. Too much and you lose profit, too little supply and your customers will find another provider fast.

Most power plants have a fairly good idea of when demand is higher and lower. This is no secret, but using data insights can help make energy provisions even more efficient and significantly cut costs. Again, by studying historical demand, power plants can predict minute-by-minute, hour-by-hour energy demands depending on anything from the season to time of day, then use this to provide the exact quantity of energy required.

 

Education
Education is an enormous market in the world. Education can actually use data to help them provide better and more appropriate education to students, although many of them have not noticed or started doing by this way.

When students move from one classroom to another and meet different teachers throughout the day, it can be hard to keep track of an individual student’s progress. However, numerous apps are using data collected in school to provide teachers with a more unified insight into their students’ academic progress and allow them to spot problems and provide additional support when needed.

 

Telecoms
Telecom companies have access to a huge amount of customer data, and so by using tools to analyze this they can provide even more personalized services that users actually want.

In the past, providing telecoms was relatively straightforward – you connected a customer to the network and allowed them to contact their friends, relatives and business associates. However, with the emergence of the Internet and ever more devices for communicating, telecom providers need to offer much more diversity in the services they offer. Data analytics can help them with this by segmenting the market ever more accurately and providing the exact deals different customers will want.

 

Finance
Finance is all about numbers, but complex algorithms help inform and support trading decision. Algorithms can collect data from an ever wider number of success. By using live and historical is find new opportunities faster than humans can read and discover, and to gain a competitive edge.

 

Retail
No industry embodies the basic elements of supply and demand better than retail. Data has always been used to understand how customers are buying, but data analytics will help this become even more accurate.

Internet of Things shelf scanners are increasingly able to tell stores how empty or full their stocks are. Data analytics will then allow stores to always provide the exact amounts of product needed.

Reference:

https://www.infragistics.com/community/blogs/mobileman/archive/2016/09/08/top-10-industries-benefiting-the-most-from-data-analytics.aspx

SEO Tools

In a previous article, we talked about search engine optimization. We understand what it is and understand why companies like using it rather than using Paid Ad. In this article, we like to talk about what tools we can make good use of to do SEO more smartly!

Wayback Machine
The Wayback Machine allows you to get historical archive of the Internet. You can see what a website used to look like. If there are some odd traffic changes after your website is updated, and you don’t have a site back-up available, you can investigate into the issue by the tool.

Moz
Moz is a suite of user-friendly inbound marketing tools. Moz can provide Open Site Explorer which is a backlink analysis tool with helpful metrics approximating link equity. Moz Local allows you see the state of a company’s local citations and is the first place you should go when you first start local SEO on a site. Mozbar is one of its tools, that is a Mozbar is a browser toolbar that lets you quickly get at Moz’s key features for the page you’re on. The SERP Overlay is part of the Mozbar and shows OSE metrics on individual search results.

Source:

http://www.lunametrics.com/blog/2017/01/17/2017-favorite-free-seo-tools/

Analyst and Data Scientist skill set in Digital Marketing

Accompanying the rapid development of technology and the data the past few years have brought, marketing is no longer like what it was in the past, and has become more digitized. Now, more and more companies are using data science to do the marketing or solve the marketing problems. And, more companies have different requirements for marketers from the past. They expect marketers not only familiar with digital tools, but also able to deal with Big Data. For examples, companies would expect marketers who understand websites, search engines, social media, and even better to know Google Analytics, or some analytics tools such as Tableau, or Data Miner. The tech-based economy is turning marketing industry into more analytical and more data science.

According to Forbes, there are 4 important digital skills all marketers should master in 2017:

1. Analytics

Consumer segmentation is an essential part of marketing, which help companies find out their target audience for different products or services. The very cornerstone of marketing as an industry is understanding the target audience in order to reach out to them effectively. In the modern world, that is best accomplished through collecting and analyzing data--often in large amounts. There are many data mining tools out there for digital marketers. For examples, SAS Data Miner is one of the data mining tools for digital marketers to have consumer segmentation.

Marketing analyst should have the knowledge of the analytics platforms they use. It should not only be dragging data to the software and have some graphs shown. They should be able to analyze the graphs they get and to get some answers they want to address by the tools. In addition, for e-commerce clients who may also request to get the result from digital marketers on their business key performance indexes. For instances, they may want to see how the digital marketers increase the unique visitors or how they increase the number of sign-up for newsletter.

2. SEO

Nowadays, Search Engines Optimization has become a very basic and popular skills for digital marketers. As you may notice that, a trend in the requirement listings of Digital Marketers SEO is always be included. That means many companies are now looking for people who know SEO when they hire marketers.

We all know that companies, especially big companies could pay for advertisements like Google AdWords, or pay for Google search result ranking. However, SEO is a desired skill because   organic search results have the potential to be much more powerful than paid ads, especially if they make it to the first page, and it’s been estimated that nearly 40% of customers find the company through search. Also, algorithms and best practices are constantly evolving and so SEO is one skill that requires consistent updating and refining. Because of this, many companies prefer to have a dedicated SEO expert (or a team of them) rather than more general marketing professionals who know some SEO.

3. HTML/CSS

Many marketing roles involve writing--whether it’s sales pages or blog posts. Being familiar with HTML at the very least will expedite the process of getting that content on the site and looking good. For examples, having the basics of HTML marketers can change a link color when needed or to resize a photo or video to fit within a blog frame. In addition, it makes cross-team communication much smoother: Marketers could be make conversations with IT teams so much easier if they understand more on coding.

4. WordPress (or related CMS)

Tying in with the above, blogging and publishing content is key for marketing. Therefore, as a marketer in 2017, knowing how to get around a content management system (CMS) is crucial.

WordPress is one of the largest--to the point where it actually runs 27% of entire internet (nearly 16 million sites)--so starting there is the best bet. The good news is once you understand how to get around one CMS, it’s not tricky to get around another.

References:

https://www.ama.org/publications/MarketingNews/Pages/data-science-latest-in-demand-skill-marketing.aspx

https://www.forbes.com/sites/laurencebradford/2017/01/16/7-important-digital-skills-all-marketers-should-master-in-2017/#7a3c339142c1

Reasons For The Rise Of Data Science In Marketing

We know that we are in an era of digital with an explosion of data. To a certain extent, it is found out that human behaviors are predictable by analysis of the data. This has led to the rise of data science, and which now is very important for business to reach, engage, and convert potential customers. The current marketing landscape is being shaped by data science as is the future of customer interactions. Here are three reasons why:

1. Marketers need data science

Data science has made marketers to make more precise hypothesis and marketing decision. Supervised machine learning enables marketers to have prediction of future trends. Pattern-matching techniques enables marketers have identification of specific purchase behaviors. When marketers are able to make good use of the available huge amount of data, they can solve marketing problems at greater scale and with more relevant business insight.

2. Mobile continues to hold great promise

Nowadays, almost everyone has a smartphone, and even more than one. We use it for getting a map, for shopping and so many other things. Advertisers are actually getting a lot of personal data from people’s smartphones and to know consumer behaviors.

Mobile apps also hold a wealth of insight, providing additional clues about a user’s interests and behaviors, which allow for more detailed customer profiles that can be used to deliver more targeted marketing

3. Big Data requires actionable insights

Data is meaningful until it gets you insights into business, and to drive sales. To achieve these insights requires analyzing a variety of algorithms as basic as cookies to as sophisticated as store visits or foot traffic.  This area in particular continues to evolve with the emergence of new technologies and platforms to provide a more detailed picture on consumer behavior.

Reference:

https://www.mediapost.com/publications/article/272154/3-reasons-for-the-rise-of-data-science-in-marketin.html

Market Segmentation

Market segmentation is a marketing concept which divides the market into different segments with consumers with a similar demand and preference. Since consumers in the same market segment are somehow alike, difference marketing tactics can be used based on the segment properties in order to maximize the effectiveness of marketing campaigns. There are 4 major ways to segment a market.

·                Geographic Segmentation

Geographic segmentation refers to the classification of market into various geographical areas. We can classify market based on continents, countries, urbanization level or climate.

Examples:

A home appliance retailer may not carry humidifier in humid countries, instead, it may carry more dehumidifier.

People in rural area may be more concern about the durability of auto vehicles and trends to buy more trucks than cars, whereas, city people prefer more stylish vehicles.

·                Demographic segmentation

This type of segmentation divides market based on people’s income, gender, age, race, occupation, family situation, etc.   

 Examples:

Marketing for super sport cars should only targets the very high income group, since other people cannot afford such an expensive car.

Feminine product should only target female customers, but not my dad.

·                Psychographic segmentation

The basis of such segmentation is the lifestyle of the individuals. The individual’s attitude, interest and lifestyle help the marketers to classify them into small groups.

Examples:

I weight the style of clothes more than the durability, while my mon is more concern about the durability.

·                Behaviouralistic Segmentation

Customers can also be classified by their behavior, such as, loyalties to a brand, reaction to discount, buying timing and frequencies.

Examples:

Promotional discount can be very effective to my mon and less effective to me.

Con’t – Data Visualization

Although there are many techniques need to be handled well for a good data visualization, it is now way easier and simpler to do it with great tools out there. However, one thing we need to bear in mind that we better not to treat data visualization like an end goal. This is one of the common mistakes people make in data reporting. 

Most data projects start off with a standard list of calculations such as finding means, medians, ranges and minimums and maximums in the data set. But after crunching the easy numbers, it can be tricky to tell which direction to explore next.It is recommended that creating some easy visualizations, like graphs and charts within the Excel program, to help spot patterns that can lead to story ideas or more questions, so that people would not be seeing numbers alone but with some exploratory visualizations and publishing them with the story as well. 

In addition, we should not overestimate the meaning of the data we have. Before even opening the file, data reporters should think carefully about the potential limitations of a data set, and what the data can and cannot tell you about a topic. People should pay attention to where the information comes from for key database fields and make sure you can trust the source.

For more common mistakes in data reporting, please click here to read:
https://www.americanpressinstitute.org/publications/data-reporting-common-mistakes/

Data Visualization and Reporting

Data is not meaningful unless people can understand it. Collecting and analyzing data are not enough, data has to be presented to concerned parties. That is the reason data visualization is such important. Here are seven key tips to help turn data into insights people will understand:

1.     Keep the audience and their information needs in mind.
We have to know who our target audience is and find out good ways to present to them. It is vital to customize any data visualization to meet the audience and their information needs. Think of who is in that audience and then think about the questions they would like answered. Knowing what we are addressing help us select right data out of tons of data and make it meaningful to audience.

2.     Choose the right chart.
There are so many different types of charts available in the data visualization tools, such as bar chart, line graph, pie chart, etc. Bar chart might be the most common chart type. However, we need to choose the right type depends on what kinds of information because not all charts are created equal. Some do a better job than others at displaying different kinds of information. We need to choose the best chart type to display the information.

3.     Go beyond Excel or PowerPoint templates. 
Speaking of data visualization, many people may first think of excel which is a very nice tool for visualizing data. But when it comes to big data, utilizing other great tools such as Tableau, Data Miner, would make the life easier. Another popular visualization tool is PowerPoint, but its built-in templates may not be doing your data any favors. Instead of trying to get fancy, keep your visualizations simple and uncluttered to be as clear as possible.

4.     Provide context.
The purpose of data visualization is not only showing the data we have in our data base, but we need to use the data to have storytelling.  Making good use of color, size and other visual cues to provide context and include short narratives that highlight the key insights. A good visualization will make the user understand what’s going go with the data, prompt the user to act on the data being presented, which may be deciding location on a new business, or may be about executing marketing campaign, or other important decisions making on company.

5.     Direct people to the most important information.
A good data reporting should be able to draw people’s attention to significant points on information and lead people to get insights from the data presented. When designing data visualizations, use sensory details like color, size, fonts, and graphics to direct attention to the most important pieces of information would be a great idea.

6.     Axis labels and numbers should be clear.
Avoid fancy labels and gauges that can get in the way of clarity. Label the axis of a graph or chart clearly and start at zero—unless you have a strong reason not to—e.g. when all the data is clustered at much higher values.

7.     Provide interactivity when appropriate.
New generations of data-visualization tools make it possible to build interactivity into many visualizations that can benefit the end user. But again, remember that this isn’t a parlor trick, and should be used when interactivity can clarify, rather than confuse, the presentation of data.

Reference:

http://data-informed.com/the-top-12-tips-for-data-visualization/

What is Data Visualization

Data visualization is not only about showing the graphs or bar charts in excel, although it is one of the parts, but is much more than that. Data visualization is graphical presentation of information. Its advantage is to enable decision makers to see analytics presented visually and to provide decision makers insights into complex data set, so they can grasp difficult concepts or identify new patterns. With data visualization, people can take the concept a step further by using technology to drill down into charts and graphs for more detail, interactively changing what data you see and how it’s processed.

Not long ago, data visualization was not a necessary skill to have for managers. But nowadays, many things have gone digital, so many decisions making relies on data, data visualization becomes a must-have skills set. In this Big Data generation, data comes in overwhelming velocity and extremely huge volume that we cannot comprehend it without filtering. Data becomes the primary force behind this changing. The ability to create smart visualization become a need for managers, because it is the way to make the work they do meaningful. There are a lot of different tools out there for data visualization, such as SAS Data Miner and Tableau, which help people way easier to visualize the complex data. People can pick the tool they feel comfortable and match with the needs of company to use. However, there are some techniques in common for people who want to visualize data set and we will talk about it in the next article. 

Search Engine Optimization

The purpose of doing SEO is to use a series of methods that allow the "search engine" to understand the content of your site and then make your site rank appear in front of the natural search results and achieve high traffic. The ultimate goal of SEO is to let the site in the first page, ranking the better in front of the better.

If you are running a website, search results are important. When you have a higher ranking of a page, it will help more people find you. The key to getting a higher ranking is whether your site has a "raw material" that meets the "recipe" developed by the search engine.

In fact, many of the main "raw materials" are all we know. First, the text is important. The search engine includes all the text on the web. When a user searches for "repair shoes", the search engine can narrow the search results to only those pages related to these keywords.

Second, the title is important. Each page on the web has a formal title. But you may never have seen it because it is hidden in the code. The search engine is very important to the title, because the title is often a web page content summary, like a book title.

Third, the link between the site and the site is important. When a page is linked to another page, it is usually a recommendation that the reader is connected to the page that has good information. As a result, the search engine will be optimistic about a lot of links to get a web page. But some people will be on the Internet a lot of manufacturing or purchase fake links, connected to their own website, trying to deceive the search engine. Usually, when a website has a lot of such links, the search engine will be found. Their countermeasure is to give more links to the links from creditworthy websites.

Fourth, the text used in the link is also important. If your page mentions that "Amazon has a lot of books" and "books" are a link, then the search engine will determine that Amazon is related to the "books" website. So, when someone searches for "books", Amazon will have a good ranking.

Finally, the search engine value reputation. Continued to update high-quality content, and continue to get more links to the site, will be regarded as a network star and get a good search rankings.

How to Monetize Data

As discussed in the previous article, data may be a company’s valuable and precious asset. However, not every company is maximizing its economic benefit. It is important to figure out how to derive a profit from the data which can also help distinguish your company in the marketplace. InformationWeek talks about several ways to monetize data. Let’s look at five of those ways and see how people who want to monetize data should do for their business.

Help Decision Making and Strategy Planning

Management is responsible for setting out company’s direction and strategy. Analyzing customer data can be the solid foundation for every decision, such as, production, R&D and marketing. For example, a car manufacturer wants to set its next year production level. It will need to obtain data regarding the economic environment for next year, customers preference trending, market competition, the trend of material price and other production cost, and a lot more other data to assess the demand and supply of the market. In addition, it will also need internal data, such as financial and budgeting to determine the level of production and whether extra capacity investment will be required.

Improve Marketing ROI
This part should be the most concerned and interested part by every company. The ultimate goal of business is always gaining profit. In fact, using data to accurately target customers and improve ROI of marketing campaigns by companies is not a new thing. However, simple website clickstream analysis, though still important, is just one source of data. In today's environment, the same organizations need to understand customer behavior across channels using more data from within the enterprise and from third parties. Companies keep tracking their customers on the websites and in their stores to get a whole picture of the customers. For example, you can tell a lot about a person by looking at their credit card information, such as shopping patterns

Retain Customer Satisfaction

Retaining customer is one of the most concerned part of corporations. It is crucial part to have business successful. Having customer satisfaction for company is one of the great way to retain loyal customers. Organizations can understand customer satisfaction levels by conducting surveys and social medial sentiment analysis. For example, gathering and integrating all those collected data from different sources, restaurants are able to figure out how satisfied a customer likely is based on factors such as quality of food and quality of staff service.

Embrace a new revenue model

Data is actually changing the business models. And, data is changing the relationship between companies and their customers. Using data analytics, companies are able to provide products or services at higher levels of personalization.  For examples, new economic models are being explored, such as replacing automobile ownership with fleets of self-driving cars and supplementing traditional insurance with micro-insurance options. There is a lot of data out there for free. However, the value of data comes from marrying that data, understanding the missions of a business, and what problem that business is trying to solve.

Detect Fraud and Piracy

Data analytics is a great thing for ecommerce or online retailers. As they are probably selling their products on a lot of different sites. The sales channels often includes Amazon, eBay and online marketplaces maintained by large retailers such as Walmart and Target. Data is available online and easy to access. Selling through all of those channels is very data-intensive, because the pricing, products, and customer types often vary across channels. Sometimes the price discrepancies are so significant they signal potential fraud or piracy.