Big Companies Beat Big Data- Part 2

In our previous article, we discussed about the prominence of predictive analytics and how important it is to be followed by every company. Let's analyse it in different angle. Have you ever noticed, customers getting excited about their own data. Of course, customers have access to more data than enough through Fitness apps. Alternatively, sites like Mint.com and LearnVest allow consumers to review their spending by category and see where their money went in a given week, month or year.

Just giving customers tons of data about themselves is not enough. Companies need to put through all of the data and extract the most relevant information where the customer easily digest the new experience. Data makes a difference for customers’ in daily lives if it's done right whether it pertains to their health and fitness or to their money. Everything can make a difference on a company’s return on investment.

It is evident that giving customers data that’s useful and meaningful to them, companies are using big data to develop fandom. Out of these techniques, the customers will get habituated,  they’re more likely to continue logging in or using the product. Hence, the companies will now have become brand loyalists all along the way. Finally, the man who loves his Fitbit will perhaps buy more branded athletic gear.

For more information on analytics, please visit http://d-analysis.blogspot.com/2017/05/big-data-vs-data-analytics-vs-data.html

Big Companies Beat Big Data- Part 1

Big companies beat the market by using the complex technological solutions used from big data concepts. This is one side of the coin, on the other side, where all these companies are getting reliable customers. What tricks are they using to attract the customers and maintain the database full of loyal customers. In order to reveal the facts behind the techniques, we definitely need to know about the predictive analytics. Let's go to our old days, where you went to the same neighborhood bakery every time you needed bread. Even before you placed your order, the shopkeeper already had a loaf bagged and ready. As you paid, she would ask what was new with your family. She might remind you to order a cake soon so it would be ready in time for your daughter’s birthday. You appreciated the personalized service and wouldn’t think of shopping at any other bakery.

This is how the predictive analytics work. In technical terms, data scientist will predict what the customer needs are and what he wants. Companies gather a ton of data on customers, not only what they’ve purchased but also the information about websites they visit, where they live when they’ve contacted customer service, and if they interact with their brand on social media. It’s an overdose amount of more unrelated data, that's why it's called as big data, "COMPLEX DATA" but companies that can properly mine this to offer a more personalized and customized touch. To properly predict the future, companies must promote the right products to the right customers on the right channel.

For more information on analytics, please visit https://haneenalansari.blogspot.com/2017/05/how-big-data-advances-ecommerce.html

Future of Digital Analytics

Many challenges that we face in the current market world can be solved by big data theories. Marketers are ready to take up any challenges in order to solve the big data problems. In fact, they are digesting the latest options from both solution providers, mainly because of the scale of measurement options. Often, there is a probability of broad view of customer segments and this has become more sophisticated in deployment and reporting.

Let us look at the improvement of measurements in top companies like Google. Google made a significant announcement with Google Analytics 360 which is a suite of tools that will replace Google Analytics Premium. This kind of changes complement the current consumer-centric era. It's all about empowering customers that drive influence instead of branding.

 To make it simple, let's look at the established practice of showrooming in a Just side, the customer comparison of a product online while standing in a store location versus parallel device usage among consumers while researching online This leads to high expectations for personalized marketing that speaks to the individual’s needs.

In my point of view, knowing your customers plays a key role rather that making them as a channel of advertising for your brand.  What if we don't adapt and establish the digital foundation. Predict what will happen if we fail in doing so. The key damages are as follows:

1. Failing to adapt the solid digital foundation can ruin your business. Website updating to SEO techniques all these are important attributes. So many companies still struggle with their budget to get the basic media and supporting media in place. Fortunately, struggle creates opportunity costs in developing metrics and refining strategy to serve the right customers faster. Coming to analytics, which must be planned ahead of launching a site, planning a mobile page, and adding an app leads to the wonderful customer experience.

2. We already discussed that customers are not the channels. Big companies often value and demand the need of recognition to the customers. How we view the customer's matters the most in market world. marketers must use solutions that merge digital and offline data sources as easily as possible. Digital analytics solutions have been marching towards this horizon, but the latest changes confirm that the marketing industry has reached that horizon.

3. The lesser value will be given to the technical capability from analytics view that creates the ad-hoc analysis. Over the years many developers have created tagging ideas for web analytics solutions through modifying the code itself. But the rise of a central analytics solution has introduced tag managers and data layers that require less elaborate customization to implement. Market leaders carefully evaluate their dependency on technically narrow solutions

4. Engagement to profit. The evaluation of digital access is changing, no doubt.  Mobile devices and tablets have made the screen not only smaller, but also transportable in a convenient way. These innovations allow new context for the value of media received, and require advanced analytics to process that context quickly.

5. Finally, the most demanding market, analytics market. All the big giants like Adobe, Amazon & Google continued the evolution to central data in their suite of analytics. For example, Kenesis, a data streaming service that allows users to integrate data within the Amazon Web Services cloud for analysis and app development.

Hence, every company has to implement the above strategies and take care not to ignore the adaption of the digital foundation.

For more information on analytics, please visit http://olgaazina.blogspot.com/2017/05/who-owns-big-data-people-government-or_23.html

Beyond Ad Words?

Significance of DoubleClick for Publishers

The title itself says that there are so many tools that you can rely upon while doing the online advertising even if it's for a small company or else a big company. Today, we are going to discuss about one of the familiar tools outside in the marketing world for promoting online business. DFP is DoubleClick for Publishers, a  Small Business is a free ad management solution that helps growing publishers sell, schedule, deliver, and measure all of their digital ad inventory. Having a simple interface with rich feature set, built-in revenue optimization, and Google-powered ad delivery, we can quickly be on our way to maximize the value of your ad impressions.

All the ads we watch on YouTube are reservation ads and they run through DFP tool. This is the one platform that allows you to manage and deliver all of your web, mobile, and video advertising. It has easy-to-use interface and a simple workflow with subtle inventory management and forecasting systems make it easy to get up and running quickly. It will give the consistent results in terms of forecasting throughout the DoubleClick for publishers. We can precisely target our ads to the intended audience where we can control on where, when and how effectively we can showcase our ad to the user. We can also control the delivery of the ads requested by the advertiser.

We can extend our article to hundred of pages when explaining about DoubleClick and it's importance. If you need ton know about more information on DFP, please visit https://www.google.com/doubleclick/publishers/small-business/faq.html

Please also visit, http://olgaazina.blogspot.com/2017/05/how-airbnb-created-referral-program-to.html

Facebook Future Strategies For AD Agency

Heads up for the agencies that offers digital marketing services and training. Adhered to the fact that slow and steady wins the race. As being owned a self-startup agency, we have a systematic plan to build our business in this competitive platform. I would like to share the work about one of our partner division agency DIGI 360. To build a strong social media relationship, we want to leverage our existing traffic to the site by placing social media icons on the homepage, since it is the area where these icons could be easily seen and this move provides better click-through rate (CTR) placements. We would continue the themes and frequency of posts in a timely manner. One of our favorite feature that Facebook Pages have is the Insights. We will see the average time that our fans are online. The Content Calendar scheduling will be followed with the current themes. We slightly adjust with the timings of the post based on this feature. Alternatively, we will use Hootsuite, SocialOomph, and Sendible to schedule social media posts and updates. Using tools like these will allows the brand to monitor the level of engagement each post attracts and how many posts is enough. We would like to build community and engagement rather than revenue & website traffic. To accomplish this, we would try not to over-promote our content as this is a social media and not advertising. Being proactive on engagement, we will always encourage the other similar page content by sharing it on our page where we believe that social media is conversational, entertaining and for educational. We will build a social media marketing plan and target the desired audience in a meaningful and relevant manner on a timely basis. Our focus is mainly on Brand Awareness and Reach to the target audience. We will do the experience strategy by developing social media activities more rigorously by spreading the brand message. 

Finally, We would like to engage with other Facebook Pages where our target audience hangs out and will comment on the page which will serve as a link to our page. Additionally, by tagging our customers using @ feature enables us to build loyalty from the customers and clients.

For more useful information, please visit https://www.facebook.com/DIGI-360-1217920791623034/

Please also visit http://haneenalansari.blogspot.com/2017/05/web-analytics-implementation-2.html

Social Media Culture At Dell

Dell being a huge company dealing in the manufacture of personal computers and later to venture in the field of software and analytics apparently needed the boost of social media. The primary objectives of the development of the social media platform at Dell were to ensure that the customers received the best services and that the growth of the business could be monitored more intelligently via the social media network of feedbacks and suggestions. This trend became an excellent predictor of future shifts in tastes and how the company could adjust accordingly. The other main reason for the advantage of moving from the standard business analysis to the social media platform is that the costs were reduced remarkably. The company now has to look to the customers for their feedback and adjust accordingly. The ignorance of the customers’ grievances nearly brought Dell to its knees at the beginning of the project roll-out. This social media analysis is, therefore, an essential part of the company’s growth.

The use of the social media in the understanding of the customers needed some training on the part of the company on the use of best customer relations material and manners. The company, therefore, by 2013 had 17,000 employees that were directly linked to the clients and were able to talk to them directly instead of a proxy.

They worked directly with customers through a telephone system, mail, and their website. That eliminated the need for warehouses and saved a lot of money on overhead expenses. The result was not only a cost advantage but also direct contact with customers. Dell received immediate feedback about consumers’ needs and an idea of how to plan on advancing the new products. Partnership with the client and direct contact with them gave an opportunity to respond to market changes and create increased customer satisfaction faster than competitors, resulting in the company's sales and profits growing several times quicker in the industry on average.

Dell embraces the social media model in an entirely different way from others. They offer immediate positive or negative consumers reviews and proposals. They offer on the spot problem solutions and help in all other aspects of the computer world. Dell provides an on-line forum that shows users conversation posts for a whole variety of PC related topics. Dell covers information for all possible types of users from individual owners to small businesses and large corporations. Dell uses our more typical social media such as Facebook and Twitter to promote new products, show new technologies, and inform about their events.

Dell annually creates relationships with clients via posts in blogs, messages in Twitter, and brand-related discussions in the social media community. The purpose of these contacts is not only to increase sales but also to keep the connection with clients and develop the dialogue in which the company wants them in. Social media platforms give customers opportunities for opinions exchange with each other and with Dell. With immediate feedback, they achieve great success by knowing what their customers want to see next. Social media gave the strongest competitive edge for Dell. Being in the one-to-one social model for years which later on turned into a consulting service helped Dell to jump into social networks a lot quicker than other IT companies resulting in an excellent social business.

Dell faced some challenges that rocked it during early stages of the implementation of its social media platform. The first significant wave that shook the boat that Dell so comfortably sailed on was that they did not recognize the plight of the customers. Even when one customer pleaded to be given the right solution to his/her problems, Dell turned a blind eye. This one-sided type of conversation between the company and customers nearly ruined the company. They had to act fast before they drowned into oblivion.

There were some obvious risks associated with moving quickly. The common one is that some disgruntled employees would use that opportunity to divulge information that was secret and that some would blatantly ruin the name of the company. The top brass of the company had to instill the value of loyalty to the customers more than to the enterprise. This loyalty, therefore, shifted the focus of the employees on listening to the customers more. The massive traffic between the company and the customers created some foreseeable problems. For instance, the company had the amalgamation of different departments as any other company. The problem was that the incoming information from the customers needed to be centralized. This centralization would, therefore, reduce the backlog and speed up the reply process.

For more information on Analytics, please visit http://d-analysis.blogspot.com/2017/05/big-data-vs-data-analytics-vs-data.html, source: Building a Social Media Culture at Dell by Michael Norris & Rohit Deshpande

Data On It's Own & It's Secret of Business Success

Data on its own, however, is nothing over 1s and 0s.

Let us keep it quick and easy. Information worldwide is growing 40 % annually, a rate of growth that's intimidating for any promoting and sales leader. firms have to be compelled to invest in an automatic “algorithmic promoting,” associate approach that permits for the process of huge amounts of information through a “self-learning” method to make higher and a lot of relevant interactions with customers. That may embody prophetic statistics, machine learning, and linguistic communication mining. These systems will track key words mechanically, for instance, and build updates each fifteen seconds supported dynamic search terms used, ad costs, or client behavior. It will build worth changes on the fly across thousands of merchandise supported client preference, worth comparisons, inventory, and prophetic analysis. One bank in geographic region remodeled itself from a little-known player into an establishment that was stratified eleventh in capitalization worldwide partially through algorithmic promoting.

That level of private interaction highlights another crossroads that is that automation doesn’t mean folks depart. Advanced analytics have to be compelled to serve front-line workers – whether or not that’s a client service operator or a sales rep within the field. To succeed firms have to be compelled to protect the line from the huge analytical quality and deliver easy pointers and suggested actions. One merchandise airline, for instance, developed a fancy model that analyzed the oftentimes dynamic dynamics of the merchandise trade and negotiating ways supported provide and demand. What it delivered to its staff, however, was an easy straightforward “dashboard” with simple pointers on flight capability, corresponding evaluation similarly as competition choices. The result was a 20 % boost in share of billfold.

For more information on Analytics and Big Data, please visit http://olgaazina.blogspot.com

Ethical Issues in Big Data Industry

Recently, I have read a case study where it stressed on ethical components used in big data industry. I always wonder, how the big data transforms to so simple data for making trendy business decisions. Big Data tailors  information from various sources to create knowledge and to make better predictions and combine the services. This article analyzes Big Data as an industry but not as a technology and  addresses the ethical issues that the current market world faces. The issue raises when the customer data has been resell. I always wonder, how the companies store the customer databases for years and retrieve the information and targets to specific customers based on the database source.  Of course, there are remedies to eradicate this issue.

Let us look at the issues and how we can foster them to replicate the issue in order to resolve it.

It receives a lot of attention  and the combination of greater size and complexity of data with advanced analytics has been effective in improving national security. It makes marketing more effective by reducing  the credit risk. I already discussed about the trends in big data industry in previous article. However, we all know the importance of big data industry yet it has also been criticized as a breach of privacy and potentially discriminated, destroying the relationship and also just leaving creepy results. While generating large and complex data sets, data scientists uses predictions and generalizations. From this, big firms makes use of Big Data that targets individuals for products where they did not know they needed. In turn, the  ignored citizens will affected a lot where they will be informed as pregnant out of their notice. Seriously, this really happened when Target targeted the teenager by sending coupons about pregnancy and post pregnancy products. This is just worse than ever, and we can imagine how the improperly blind data can affect. We are not here to complain on this, but we can raise our voice and confess our advocacy on this sensible issues. So that companies can take necessary precautions on preventing this miscommunication that happens through big data.

For more information on analytics, please visit http://eastonanalytics.blogspot.com/

ANALYST AND DATA SCIENTIST SKILL SETS IN DIGITAL MARKETING

Owing to the digitization of the consumer products economy, data scientist and analyst are highly essential to the marketing profession. Analyst skills are not as advanced as the data scientist, but they both have a similar objective which is to discover how data can be used to answer questions and solve problems.

Being a data scientist or analyst requires highly specialized skill sets which are

•                     Technical skills

•                     Business skills

Technical skills

•                     Education

Technical skills are acquired academically in disciplines like computer science, machine learning, advanced statistics, and other related fields.

•                     Technical tools usage

As an analyst, it is required of you to have an in-depth knowledge of analytical tools like SAS or R and as well be familiar with data warehousing and business intelligence concepts.

An analyst must have a better understanding about java, MySQL, python, and Hadoop-based analytics like MapReduce job developments.

It is essential for a data scientist to understand various analytical functions, median rank and to know how to use them on data sets. An analyst must be versatile with data storing and retrieving skills and be perfect in using the tools and components of data architecture.

An analyst must be familiar with various ETL tools for transforming different sources of data into analytics data stores.

Data scientist must be a perfectionist in mathematics, statistics, data mining, and predictive analysis. He should be able to give better predictions for business decisions, with deep statistical insights and working experience in machine learning techniques like Bayesian and mahout.

Data scientists should be an expert in database design, programming, data management, data consolidation, data cleansing, data modeling, data mining, and data visualization.

Business skills

Problem Solving: A data scientist needs to know how to productively approach a problem by identifying the problem’s salient features, figuring out how to frame a question that will yield the desired answer, consult the right co-workers at the appropriate junctures of the analytic process and know the data science methods to apply to the problem at hand.

Communication and visualization: A good data scientists and analyst must be able to fluently interpret their technical findings to a non-technical team including the Marketing or Sales departments. It is required of a data scientist to be able to present data in a visually compelling way, this can be achieved by mastering data visualization tools also familiarize oneself with the principles of visualizing data effectively. Visualizing data is very important especially in companies where data scientists are viewed as people who help in making data-driven decisions. It is important to not just be familiar with visualizing tools like ggplot and d3, but also the principles behind visually encoding data and communicating information.

Intellectual Curiosity: A data scientist and analyst must have a curious and explorative mindset to be able to explore new territories and find creative ways to solve problems.

Industry Knowledge: As an analyst or data scientist, one must understand how the industry functions and how data are being collected, analyzed, and utilized.

Business acumen: Following technical skills, business acumen is highly desired in digital marketing, you’ll need to be cognizance of the business problems your company is trying to solve. Apart from identifying new ways in which the business could leverage its data, a data scientist must be able to discern which of the industry problems are critical to resolving for the successful running of the business.

Generally, a key requirement for analytical excellence is the right mindset. Data scientists and analyst must need to have an intrinsic, high level of curiosity and a strong appetite for intellectual challenges. They should be able to pick up new methods and mathematical techniques within a short time to solve the problem at hand.

For more information on analytics, please visit http://eastonanalytics.blogspot.com/

Big Information Is The Biggest Game

Big information is that the biggest game-changing chance for promoting and sales since the web went through nearly twenty years gone. That statement usually prompts vigorous head pendulous from executives, however, is quickly followed by head scratching. “How will we tend to build this happen?”

Origination To Current Situation

Begin with the patron call journey. Today’s channel-surfing client is snug mistreatment associated array of devices, tools, and technologies to satisfy a task. Understanding that call journey is important to characteristic battlegrounds to either win new customers or keep existing ones from defecting to competitors. Around 35% of B2B pre-purchase activities, for instance, area unit digital, which implies B2B firms have to be compelled to invest in internet sites that a lot of effectively communicate the worth of their merchandise, SEO technology to create certain potential customers area unit finding them, and social media observation to identify new sales opportunities. One on-line retail merchant, for instance, tailors its offers and discounts supported predictions of however doubtless a valued client is to defect.

Marketing and sales leaders have to be compelled to develop complete photos of their customers so that they will produce messages and merchandise that area unit relevant to them. Our analysis shows that personalization will deliver 5 to eight times the ROI on promoting pay and carry sales ten % or a lot of. Turning into ever more practical with this sort of targeting, we tend to believe (and hope), can mean the death of spam.

For more information on Analytics and Big Data, please do visit http://d-analysis.blogspot.com/2017/04/google-analytics-and-customer-journey_3.html

Analytics On How To Install Google Analytics On WordPress Website

Why Do We Need Google Analytics?

Google Analytics shows you how people find your site, how they explored it, and how you can enhance their visitor experience. With this information, you can improve your website return on investment, increase conversions, and make more money on the web.

Process Flow

The first step in the process is to get a plugin that will make it easy to install Analytics into your WordPress blog. In general, people use Joost de Valk's (Yoast.com) plugin "Google Analytics for WordPress." As far as I am concerned, Yoast is one of the foremost authorities on WordPress and it’s really very efficient.

Here are the steps to install the plugin:

1. Go to plugin tab in your dashboard

1. Search "Yoast" in the plugins search box

1. Find the Yoast plugin and click install

1. Activate the plugin

1. Add your Analytics Account ID in the box

1. Check the boxes that you would like Analytics to track

1. Save Settings

It's as simple as that. Once you have installed Google Analytics on your blog, Google will start tracking your results usually within 24 hours.

Now you can enhance your visitors experience by tweaking your blog for maximum visitor enjoyment and begin to reap the benefits of better conversions, return on investment, and making more money with your blog.  

For more information on Analytics, please visit http://d-analysis.blogspot.com/2017/04/google-analytics-and-customer-journey_3.html

STATUS AND FUTURE OF BIG DATA IN AN INDUSTRY

Current Status

We live in a world that strongly relies on data for business activities Data forms the basis of several actions and determines the fate of corporations. It can either be in a structured or unstructured form. While structured data are stored in a database like SQL, the unstructured data exist in documents file and streaming data that were gotten from sensors. The integration of different data types and their management in association with the traditional data forms BIG DATA.

In a wider sense, Big data is a term technologist employs in describing a large volume of data flooding several business organizations. Big data is much essential to the successful operation of the business organization in different industries. Financial Institution clearly understands the dynamic nature of customer needs and also deploy several alternatives to boost their satisfaction. They, therefore, need to activate big data technology to minimize both risks and frauds. Similarly, its impact is felt in the educational sector. Most educator finds it easy to identify at-risk students, make adequate progress and implement an efficient system that provides necessary support for their teachers and school principals.

Furthermore, government agencies can make significant progress when managing utilities, dealing with traffic congestion issues and develop strategies to reduce crime. The value of big data can't also be underrated in the medical sectors. Big data technology has assisted several medical personnel to uncover hidden insights and improve patient care. The technology significantly improved the efficiency and accuracy of medical job and also helped them to act in line with the regulation of the sector.

Industry Demands

Establishing an effective customer relationship is quite important in the retail industry. Multinational retail companies have adopted Big data technology to facilitate their operation. The system is efficient in the management of their major daily transactions. This technique revived many businesses and made them compete better than other firms. Manufacturers also enjoy enormous benefits from big data. They've been able to boost their output, product quality, and service delivery. The manufacturer quickly solves complex issues and make better business decisions.

For a better understanding of the importance of Big data in business operation, it would be nice to identify organizations which have successfully incorporate Big data technology in this operation. The use of big data technology by Macy Incorporation increased the company online presence and credibility to their customers. This retailer ability to make near real-time pricing adjustment for roughly 73 million items, based on demand and inventory improved its level of customer patronage. Furthermore, Tipp24, a modern European betting platform for lotteries and predictions was developed through big data technology. The company's system analyzes billion of a transaction and hundreds of customer features. It also develops predictive models that target customers and personalize marketing messages immediately.

Walmart Stores Incorporation, a US-based retailer also adopts Big data technology on its search engine. Its search engines wholly rely on text analysis, machine and even synonyms mining to output the appropriate search results. According to the company's manager, big data has fetched the company billions of dollars through the assistance it provided in helping the online shoppers to complete their purchase.

Future Scope

Adopting big data for the creation of business value has become a reality. However, access to big data and internet connectivity can pose a big challenge to the future existence of big data, Most of the data points are yet to be connected, and companies also lack the right platform to manage data across their enterprise. Furthermore, security concerns form a major obstacle that presents big data users from enjoying the full benefits of this technology. The organization understands the effect such issues will have on their daily operation and can because of the ignore Big data technology in the nearest future. Also, the rapid development of big data technological landscape has a negative influence on organizational data. It's capable of creating fragmentation on data ownership which is not encouraging for most organizations. All these issues change bring Big data into extinction. It's necessary for big data service to critically examine these issues to avoid the complete collapse of this wonderful innovation.

For more information on Analytics and Big Data, please visit http://olgaazina.blogspot.com/2017/04/status-and-future-of-big-data-part-3.html

Communication in Analytics

The title itself says Communication, means communicating language in analytics world that drives us to the correct path of efficient data in return. The ideas and findings are often complex but yet surprising and also subtle. These qualities can make them challenging to communicate, regardless of the audience. On the other hand, analysts have a great deal of freedom over the manner in which they communicate ideas and findings – some overarching, general principles can help analysts make decisions in this regard.

Skillset Example

Analytics on its self revolves around the communication of patterns in data. Someone with huge analytics skill like mining and/or interpreting data without the ability to communicate it across have only achieve part of analytics. Analytics will not be complete until it is adequately communicated to the end users.  Let's go further into the practical, if a data scale scientist had gathered information/data, and interpreted it; He has responsibility to communicate this across to the people that need the information. For instance, if a data scientist observe a pattern of huge "bounce off" on your website and you have interpreted this situation to be as a result of poor users experience on the website. It is important to communicate this to the web designer in order to create improve users experience. The communication will be a two way form; where the data scientist ensures that the web designer communicates his understanding to him as well.

For more information on Analytics, please visit https://haneenalansari.blogspot.com/2017/04/the-power-of-business-intelligence_24.html

Challenges in Social Media by Big Companies

One of my favorite company is Dell.  I would like to share about some interesting facts that I have come across when dealing with the social media statistics stuff with the high-end companies. Dell has made significant progress since launching its social media strategy in 2006. They are regarded as a pioneer who took the risk of exposing themselves to customer feedback which most often than not is negative, and was able to turn it into their strength. At this point, they need to continue to evolve their social media program by having a presence wherever their customers are.  For example, it is known that individuals aged 14-22 drive 70% of family computer-buying decisions. This demographic spends on average 6 hours a day on their phone digesting content. To appeal to this demographic, Dell should engage in social sites they visit such as Snapchat and Instagram or music apps such as Spotify or Tidal.

Concerning communication, most people communicate with each other via text on a regular basis. Perhaps Dell should create specific emoji’s, or bitmoji’s showcasing their brand and products. This would help take their awareness to the next level by fueling endless conversations and allowing Dell to stay top of mind with current and potential customers.

            Another step could be turning the tables on their social listening.  Currently, Dell uses all the listening being conducted to better themselves from a product and service perspective.  They use sentiment analysis to proactively solve customer issues and monitor consumer trends to assist in R&D. They also analyze their industry’s social stream to stay up to date on their competitors. This “listening” alone results in a higher “demoter to promoter” score which has led to increased customer loyalty, higher resolution rates which give them a competitive edge. Imaginably, Dell could create a podcast where customers could listen to Dell speak about technology and innovation and create a platform where there is 2-way communication for ideation.

Here pops up a new question.

Could Dell’s social media model be transferred to other companies? 

            Dell is one of the few Fortune 500 companies that have been early adopters of social media and have turned it into a viable source of sales. They have indeed evolved over the past ten years into a “Social Enterprise” and are currently one of the few companies that have gotten the social media marketing right.

 I believe their model should be transferred to other companies who should adopt the customer centric mentality. Dell has created a platform where they can tap into exactly what their customers want regarding service and product and deliver to meet those needs and expectations. Their “Social Outreach Services” group converts clients who come online to rant to ravers and mostly ambassadors of the brand.  The results of this effort are evident in their sales. 

       However, companies must keep in mind to successfully become a “Social Enterprise”, there needs to be a complete adoption from the company to support the social media initiative. In Dell’s case, the adoption of social media is top down. It starts with their CEO, Michael Dell, who is fairly active on social media and transcends to all of their employees globally. Dell employees are trained to use social media in every aspect of their job particularly technical support and customer care. The success is in the numbers since to date they have over 10,000 employees who are certified social media ambassadors.

This movement transcends to their customers who in turn for stellar service, promote and support Dell in their social networks. Social media has today become an extension of their brand since it allows them to be a better company by delivering first class products and solutions to their customers.  To date, few companies have been able to achieve this success and Dell can be seen as one of the world’s most social companies.

For more information on Analytics, please visit http://olgaazina.blogspot.com/2017/04/status-and-future-of-big-data-in.html
Source Case Study from Building a Social Media Culture at Dell by Michael Norris & Rohit Deshpande

Impact of Marketing Analytics

Today's world is revolving around numbers. How comfortable are we dealing with numbers? Are you afraid? Are you worried about the realms of the data story? If the answer is yes, then we have to roll-up our sleeves and stand for the solution. The relation between "Numbers-Data-Analytics" is obvious and are linked to each other. How P&G is constant in their customer satisfaction. Do numbers does magic? Yes, definitely, they do so.

This is a very big business, dealing with numbers, so-called Analytics. Technically, it is called Marketing Analytics. Companies are investing millions in just knowing about the numbers. According to the most recent CMO survey, companies currently spend 6.7% of their marketing budgets on analytics and expect to spend 11.1% over the next three years. The biggest brands plan on increasing their spending on the category by a whopping 73 percent over the next three years.  The most surprising fact is all the well-known brands are high in marketing technology and investing billion dollars in data analytics. 
Before, marketers used to think that why we have to look at the data. But after looking at the overall ROI, companies are fascinated looking for the data-driven stories. Yes, data tells the story of the customer relationship with the brand. And the same data allows the brand to iterate the techniques, test the results and apply the logic in dealing with the current competitive marketing world.

For more information on Analytics, please visit http://d-analysis.blogspot.com/2017/05/big-data-vs-data-analytics-vs-data.html

Data Visualization And Reporting

Data reporting translates raw data into information. And also, reporting is about organizing data into summaries. Data alone is meaningless, and action without data is baseless. Both reporting and visualization are important or vital to adding value to data and operation. When data reporting is accurate, it gives rise to the accurate analysis of the fact at hand. An accurate analysis is a result of a rigorous data analysis. Meaningful data visualization all starts from a comprehensive and accurate reporting.

Reporting plays important roles in web analytics, but organizations need to understand that reporting is just numbers. Without drawing insights and having report aligned with the big picture of an organization, decisions can’t be made based on reports alone. Data reported should be analyzed. Data analysis is the most powerful tool to bring into businesses.

Data visualization is one of the steps in analyzing data and presenting it to users. Data visualization refers to the model used to communicate information by encoding it as visual objects (e.g. points, lines or bars) contained in graphics. The aim is to pass information clearly and efficiently to users.

The main aim of data visualization is to pass information clearly and effectively through graphical means. An ideal visualization should communicate clearly, and also encourage viewer engagement and attention. Data visualization is vital in transforming business strategy to reality as it permits understanding where an organization or division needs to focus.

Significance of data visualization and data reporting

Data reporting provides the platform for organizing data into informational summaries in order to monitor how different areas of business are performing. Data visualization is a fast, simple approach to passing on ideas in a general way. It likewise helps to recognize ranges that need consideration or change.

  

How is data visualization used?

Regardless of industry or size, a wide range of organizations is making use of data visualization. Let us look at the below components about the main tasks it does,

Comprehend data rapidly

By utilizing graphical representations of business information, organizations can see a lot of data in clear, cohesive ways and draw conclusions from that information.

Identify connections and patterns

Even extensive amounts of complicated data start to make sense when presented graphically; organizations can perceive parameters that are profoundly correlated. Some of the correlations will be obvious, however, others won't. Recognizing those connections helps organizations concentrate on areas most likely to influence their most important objectives.

Pinpoint rising trends

Using data visualization to discover trends both in the business and in the market can give businesses an edge over the competition, and eventually influence the primary concern.

Tell the story to others

Once a business has revealed new bits of knowledge from visual analytics, what follows is to convey those bits of knowledge to others. Utilizing graphs, charts or other visually impactful representations of data is important in this step since it's engaging and gets the message across quickly.

Data Visualization Tools

Here, I will be talking about two of the available tools.

Tableau

Tableau offers a suite of tools that include an online, desktop and server version. All of these versions provide an easy-to-use drag and drop interface that can help you quickly turn your data into business insights. The online and server versions give the room for your entire team to build and work with the visualization tool. Like many other data analytics and visualization tools, Tableau can connect to local or remote data of different formats. Additionally, the Tableau engine can connect to live data for up to date visualizations.

QlikView

The QlikView business discovery platform is one of a few visual analytics tools offered by Qlik. QlikView can’t create the same elegant visualizations that the other tools offer, but the software’s dynamic model means that you can analyze your data quickly in multiple dimensions. QlikView is able to work with a wide variety of data sources, including SAP, Oracle, and other legacy data files like Excel spreadsheets. What’s more, QlikView can combine these disparate data sources into a single visualization.

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Data Visualization

Data visualization is taken by many disciplines as a modern equipment of visual communication. The important objective of data visualization is to address data unmistakably and proficiently through statistical graphics, plots and graphics. The data that is in numbers is coded and decoded by utilizing dots  dots, lines, or bars, to visually impart a quantitative message. The interpretation of visualization helps users test and reason about data and proof. It makes complex data more available, reasonable and usable. Users may have specific analytical tasks, for example, comparing or understanding causality, and the design principle of the graphicfollows the task. In my point of view, tables are the most utilized version where users will look into a particular measurement, while charts of different sorts are utilized to show examples or connections in the data for one or more variables. Data visualization is however important in transforming business strategy to reality as it permits understanding where an organization or division needs to focus.

One of my Favorite tool is SAS Visual Analytics. SAS Visual Analytics empowers business users, business analysts, and IT administrators to accomplish tasks from an integrated suite of applications that are accessed from a home page. The central entry point for SAS Visual Analytics enables users to perform a wide variety of tasks such as preparing data sources, exploring data, designing reports, as well as analyzing and interpreting data. Most important, reports can be displayed on a mobile device or in the SAS Visual Analytics Viewer (the viewer). 

So, what is your favorite business Visual Analytics tool. Please do share your thoughts in comments.

Source: SAS Website

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Web Analytics And Their Benefits

If you wаnt to knоw whо vіѕіtѕ уоur ѕіtе, whаt thеу do whіlе thеу аrе оn thеіr ѕіtе and whу thеу lеаvе, then уоu need tо bе соnсеrnеd wіth wеb аnаlуtісѕ. Wеb аnаlуtісѕ аrе еѕѕеntіаl іf уоu wаnt tо fіnd оut іnfоrmаtіоn аbоut реорlе whо vіѕіt your ѕіtе. Wеb аnаlуtісѕ can аlѕо hеlр уоu dеtеrmіnе whісh раgеѕ of your site аrе реrfоrmіng wеll and whісh оnеѕ аrе nоt. Lаѕtlу, wеb analytics hеlр уоu dеtеrmіnе whісh kеуwоrdѕ аrе drіvіng the mоѕt trаffіс to уоur ѕіtе. Thеrе аrе mаnу bеnеfіtѕ fоr wеb аnаlуtісѕ but below аrе thе tор 5 bеnеfіtѕ.

Bеnеfіt #1 - Trаffіс Cоunt

Hаvе уоu ѕееn соuntеrѕ оn thе bоttоm оf web раgеѕ thаt ѕhоwѕ hоw mаnу vіѕіtоrѕ have соmе tо уоur ѕіtе? Thе gооd thing аbоut wеb аnаlуtісѕ іѕ thаt уоu саn get muсh mоrе precise іnfоrmаtіоn. Yоu саn brеаkdоwn уоur visitors bу hоw mаnу аrе nеw vіѕіtоrѕ аnd how mаnу аrе rереаt vіѕіtоrѕ. Yоu саn аlѕо dеtеrmіnе whаt раgеѕ thеу have vіеwеd frоm уоur wеbѕіtе.

Bеnеfіt #2 - Indіvіduаl Vіѕіtѕ

Nоw thаt уоu knоw how mаnу vіѕіtоrѕ hаvе соmе tо уоur ѕіtе аnd whеthеr thеу аrе nеw оr rереаt visitors, you саn gаthеr іnfоrmаtіоn аbоut іndіvіduаlѕ thаt vіѕіt уоur wеbѕіtе. Fоr еасh реrѕоn that vіѕіtѕ уоur wеbѕіtе, уоu саn fіnd оut whаt wаѕ the fіrѕt раgе thеу vіѕіtеd аnd whаt wаѕ thе lаѕt раgе thеу vіѕіtеd рrіоr tо lеаvіng уоur ѕіtе.

Bеnеfіt #3 - Tоtаl Tіmе

Now thаt wе hаvе a gооd іdеа of thе vіѕіtоrѕ to оur ѕіtе, уоu would wаnt tо know thе total tіmе vіѕіtоrѕ аrе ѕреndіng оn уоur ѕіtе as wеll as thе раth they tооk thrоugh your site. Yоu саn use thіѕ іnfоrmаtіоn tо dеtеrmіnе hоw реорlе nаvіgаtе through уоur ѕіtе.

Bеnеfіt #4 - Vіѕіtоrѕ

Thе fоurth bеnеfіt оf wеb analytics іѕ that уоu can dеtеrmіnе thе lіnkѕ thаt brought уоur vіѕіtоrѕ tо your ѕіtе. Visitors еіthеr соmе tо уоur ѕіtе from ѕоmе оthеr lіnk оr thеу соmе directly to уоur ѕіtе.

Bеnеfіt #5 - Kеуwоrdѕ

Lаѕtlу аnd mоѕt іmроrtаntlу іѕ dеtеrmіnіng the kеуwоrdѕ thаt реорlе аrе uѕіng tо gеt tо уоur wеbѕіtе. If уоu dеtеrmіnе thаt visitors аrе uѕіng раrtісulаr kеуwоrdѕ tо fіnd уоur ѕіtе, thеn уоu wаnt tо орtіmіzе your site for thоѕе kеуwоrdѕ. Thіѕ іѕ grеаt орроrtunіtу to орtіmіzе уоur соntеnt tо whаt your vіѕіtоrѕ аrе looking for whеn thеу visit уоur ѕіtе.

Aѕ уоu саn ѕее, thеrе аrе mаnу bеnеfіtѕ оf wеb аnаlуtісѕ. Ultіmаtеlу, thе benefit оf Wеb Analytics іѕ tо mаkе уоur ѕіtе mоrе rеlеvаnt fоr уоur vіѕіtоrѕ.

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Web Analytics Implementation

In this digital marketing world, web analytics is not just a measuring tool for getting results of web traffic but also a very powerful tool for testing, analyzing the business and marketing research approaches. Website analytics is essential in optimizing your online presence, especially when entrepreneurs are not satisfied with just more visitors to their sites and demanding the return on investment (ROI) hence, there is the need of website analytical strategy and implementation.

For effective implementation of your web analytics, you need to understand what the analysis is and determine your business objectives; you have to understand the relevance of the information provided by your analytical program and consult other members of your team to ensure that the information supplied is effectively the information needed. Finally, after defining the specific needs of interdependence, defining the framework for the support and installing the tracking code, you need to test the implementation of the analysis.

Various analytical programs allow you to set the "test mode", while others allow you to block certain IP addresses or certain sources of traffic. Know your options before you installed the test and know their support options if the test phase does not produce the expected data. After successful implementation of website analytics, the current task will be to examine the data, use the ideas to improve your business and increase your income which is the general objective of web analytics.

Monetization of Analytics Data

Data is not just new because of its size; it is new because it is not possible to analyze it using common methods. Analytics are necessary to profile big data sets. For organizations to become proficient, they need to understand the personality of analytics. This would not happen without building analytical capacity. Analytics will smooth the way toward data monetization.

These days, a lot of people log on to the Internet, allowing organizations access to more engagement data. But if an organization does not have trained data analysts to modernize the way data is collected, stored, and analyzed regularly, there would not be any business rewards. Organizations are now eager to figure out how their business can be driven forward to create new strategies while increasing their income and growth by overcoming biggest dilemma associated with data monetization.

Among the major questions, they ask their service providers are around how they can trace the risks and investments needed to build a data monetization strategy. These organizations either struggle between understanding how to invest raw data for distribution and handling the sophistication around analytics or data processing.

In today’s digital world, data is more readily available and easily got, than before. With the potential to track most customer interactions and transactions across devices and channels, organizations are looking at and leveraging their data in new and innovative ways. And these companies are becoming increasingly mindful that they are sitting on massive amounts of under-utilized data and seeking ways to increase its value. The conditions for data monetization are ripe: large volumes of structured and unstructured data; lowering storage costs; data-driven advertising campaigns that create relevant customer experiences; and boosting business intelligence and processes by applying data analytics.

Analytics is currently making customers’ lives easier and building a more happy and loyal client base. It also allows organizations to maximize the variety and volume of their data, enabling them to conveniently access, enhance and de-identify data sets to be packaged as a new data service offering for their customers. In the absence of data analytics, organizations are actually blind and deaf, roaming out onto the internet like deer on a freeway. These words lay stress on the importance of analytics when it comes to helping decision-making and driving profits.

So, with this reliance upon analytics and data, monetization of data is no more an improbable reality. There is certainly still an excessive amount of unexplored information in customer feedback comments, video footage, conversations on the social media, and locational GPS data, which needs to be studied and put into use. Innovative and nimble approaches to applying analytics to data will surely bring in loyal customers as well as generate higher revenue without downturns.

Nevertheless, organizations seem to harbor many individual data stores thereby it hard to access data for monetization purpose. In the process of monetizing data, acquiring an external perspective is essential. Benchmarking of other organizations and effective data monetization approaches can help in framing new ideas and gaining valuable insights. Though, transforming data into actionable insights and generating new revenue streams is a challenge. However, data monetization has opened eyes to the idea of analytics as a strategic capability, beyond basic financial analysis, reporting, and basic marketing optimization.

Analytics has unveiled how incredible data deluge can be when tracked at the right time. In the long run, it all depends on how you are turning data into information, and information into insight. So, it is up to you, will you indulge data as an opportunity and invest, or will you allow it to go musty? Roll up your sleeves now and start planning a strategy and carving a vision around the monetization of data and analytics.

Marketing Analytics Scope

This blog focuses mainly on the analytics and data insights in the current marketing world. Marketing organizations are becoming more data-driven, and more focused on marketing analytics, digital attribution and big data in general. We concentrate on the current trends in the market about the development of better analytical tools used by the marketers. We will also deep dive into the job opportunities where many companies are specifically seeking to hire marketers with data and analytical skills and experience. How widespread is this trend now? Do you want to know? Seriously companies embracing analytics practice are backing up now with best hiring techniques. All these indications now point to a tectonic shift.

In July 2013, there were 23, 118 job postings that included analytics, marketing analytics. Now, the growth rate in marketing analytics increased to 67% over the past year and 136% over the past three years. Surprisingly, the number of jobs with “big data” as a requirement increased to 63%, so the marketing side even beats that.

Real World Scope

All of us are really afraid of numbers, but when it comes to business decisions, the whole business world revolves around the numbers and metrics where business leaders will come up with the new decision making firepower. Eventually, calls for a more sophisticated approach for the diverse activities and audiences that marketing dollars typically support along with the variety of investment time horizons. According to Mc Kinsey review, more than 400 diverse client engagements from the past eight years, across industries and regions, found that an integrated analytics approach can free up some 15% to 20% of marketing spending. Worldwide, that equates to as much as $200 billion that can be reinvested by companies or drop straight to the bottom line.

Please visit our blog every week for more insights on current analytics trend. 

References: http://www.mckinsey.com, www.forbes.com