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